Connect public, paid and private patent data with Google Patents Public Datasets

Collecting sleep quality information via a medical device

Download PDF

Info

Publication number
US20050215847A1
US20050215847A1 US11081811 US8181105A US2005215847A1 US 20050215847 A1 US20050215847 A1 US 20050215847A1 US 11081811 US11081811 US 11081811 US 8181105 A US8181105 A US 8181105A US 2005215847 A1 US2005215847 A1 US 2005215847A1
Authority
US
Grant status
Application
Patent type
Prior art keywords
patient
sleep
quality
values
parameter
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US11081811
Inventor
Kenneth Heruth
Keith Miesel
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Medtronic Inc
Original Assignee
Medtronic Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date

Links

Images

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00Electrotherapy; Circuits therefor
    • A61N1/18Applying electric currents by contact electrodes
    • A61N1/32Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/3605Implantable neurostimulators for stimulating central or peripheral nerve system
    • A61N1/36128Control systems
    • A61N1/36135Control systems using physiological parameters
    • A61N1/36139Control systems using physiological parameters with automatic adjustment
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00Apparatus for testing the eyes; Instruments for examining the eyes
    • A61B3/10Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
    • A61B3/113Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for determining or recording eye movement
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/01Measuring temperature of body parts; Diagnostic temperature sensing, e.g. for malignant or inflammed tissue
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body or parts thereof
    • A61B5/0402Electrocardiography, i.e. ECG
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/04Detecting, measuring or recording bioelectric signals of the body or parts thereof
    • A61B5/0476Electroencephalography
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/103Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1116Determining posture transitions
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/103Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1118Determining activity level
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/48Other medical applications
    • A61B5/4806Sleep evaluation
    • A61B5/4815Sleep quality
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6846Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be brought in contact with an internal body part, i.e. invasive
    • A61B5/6847Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be brought in contact with an internal body part, i.e. invasive mounted on an invasive device
    • A61B5/686Permanently implanted devices, e.g. pacemakers, other stimulators, biochips
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M5/00Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests
    • A61M5/14Infusion devices, e.g. infusing by gravity; Blood infusion; Accessories therefor
    • A61M5/142Pressure infusion, e.g. using pumps
    • A61M5/14244Pressure infusion, e.g. using pumps adapted to be carried by the patient, e.g. portable on the body
    • A61M5/14276Pressure infusion, e.g. using pumps adapted to be carried by the patient, e.g. portable on the body specially adapted for implantation
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61MDEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
    • A61M5/00Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm-rests
    • A61M5/14Infusion devices, e.g. infusing by gravity; Blood infusion; Accessories therefor
    • A61M5/168Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body
    • A61M5/172Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body electrical or electronic
    • A61M5/1723Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body electrical or electronic using feedback of body parameters, e.g. blood-sugar, pressure
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00Electrotherapy; Circuits therefor
    • A61N1/18Applying electric currents by contact electrodes
    • A61N1/32Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/3605Implantable neurostimulators for stimulating central or peripheral nerve system
    • A61N1/3606Implantable neurostimulators for stimulating central or peripheral nerve system adapted for a particular treatment
    • A61N1/36071Pain
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00Electrotherapy; Circuits therefor
    • A61N1/18Applying electric currents by contact electrodes
    • A61N1/32Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/3605Implantable neurostimulators for stimulating central or peripheral nerve system
    • A61N1/3606Implantable neurostimulators for stimulating central or peripheral nerve system adapted for a particular treatment
    • A61N1/36078Inducing or controlling sleep or relaxation
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00Electrotherapy; Circuits therefor
    • A61N1/18Applying electric currents by contact electrodes
    • A61N1/32Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/3605Implantable neurostimulators for stimulating central or peripheral nerve system
    • A61N1/36128Control systems
    • A61N1/36135Control systems using physiological parameters
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00Electrotherapy; Circuits therefor
    • A61N1/18Applying electric currents by contact electrodes
    • A61N1/32Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/362Heart stimulators
    • A61N1/365Heart stimulators controlled by a physiological parameter, e.g. heart potential
    • A61N1/36514Heart stimulators controlled by a physiological parameter, e.g. heart potential controlled by a physiological quantity other than heart potential, e.g. blood pressure
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00Electrotherapy; Circuits therefor
    • A61N1/18Applying electric currents by contact electrodes
    • A61N1/32Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/362Heart stimulators
    • A61N1/37Monitoring; Protecting
    • A61N1/3702Physiological parameters
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00Electrotherapy; Circuits therefor
    • A61N1/18Applying electric currents by contact electrodes
    • A61N1/32Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/372Arrangements in connection with the implantation of stimulators
    • A61N1/37211Means for communicating with stimulators
    • A61N1/37235Aspects of the external programmer
    • A61N1/37247User interfaces, e.g. input or presentation means
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Detecting, measuring or recording for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6813Specially adapted to be attached to a specific body part
    • A61B5/6825Hand
    • A61B5/6826Finger
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00Electrotherapy; Circuits therefor
    • A61N1/18Applying electric currents by contact electrodes
    • A61N1/32Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/362Heart stimulators
    • A61N1/365Heart stimulators controlled by a physiological parameter, e.g. heart potential
    • A61N1/36514Heart stimulators controlled by a physiological parameter, e.g. heart potential controlled by a physiological quantity other than heart potential, e.g. blood pressure
    • A61N1/36521Heart stimulators controlled by a physiological parameter, e.g. heart potential controlled by a physiological quantity other than heart potential, e.g. blood pressure the parameter being derived from measurement of an electrical impedance
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00Electrotherapy; Circuits therefor
    • A61N1/18Applying electric currents by contact electrodes
    • A61N1/32Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/362Heart stimulators
    • A61N1/365Heart stimulators controlled by a physiological parameter, e.g. heart potential
    • A61N1/36514Heart stimulators controlled by a physiological parameter, e.g. heart potential controlled by a physiological quantity other than heart potential, e.g. blood pressure
    • A61N1/36542Heart stimulators controlled by a physiological parameter, e.g. heart potential controlled by a physiological quantity other than heart potential, e.g. blood pressure controlled by body motion, e.g. acceleration
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61NELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
    • A61N1/00Electrotherapy; Circuits therefor
    • A61N1/18Applying electric currents by contact electrodes
    • A61N1/32Applying electric currents by contact electrodes alternating or intermittent currents
    • A61N1/36Applying electric currents by contact electrodes alternating or intermittent currents for stimulation
    • A61N1/362Heart stimulators
    • A61N1/365Heart stimulators controlled by a physiological parameter, e.g. heart potential
    • A61N1/36514Heart stimulators controlled by a physiological parameter, e.g. heart potential controlled by a physiological quantity other than heart potential, e.g. blood pressure
    • A61N1/36557Heart stimulators controlled by a physiological parameter, e.g. heart potential controlled by a physiological quantity other than heart potential, e.g. blood pressure controlled by chemical substances in blood

Abstract

At least one of a medical device, such as an implantable medical device, a monitor, and a computing device determines values for one or more metrics that indicate the quality of a patient's sleep. Sleep efficiency, sleep latency, and time spent in deeper sleep states are example sleep quality metrics for which values may be determined. In some embodiments, determined sleep quality metric values are associated with a current therapy parameter set. In some embodiments, a programming device presents sleep quality information to a user based on determined sleep quality metric values values. A clinician, for example, may use the sleep quality information presented by the programming device to evaluate the effectiveness of therapy delivered to the patient by the medical device, to adjust the therapy delivered by the medical device, or to prescribe a therapy not delivered by the medical device in order to improve the quality of the patient's sleep.

Description

  • [0001]
    This application is a continuation-in-part of U.S. application Ser. No. 10/826,925, filed Apr. 15, 2004, which claims the benefit of U.S. Provisional Application No. 60/553,783, filed Mar. 16, 2004. The entire content of both applications is incorporated herein by reference.
  • TECHNICAL FIELD
  • [0002]
    The invention relates to medical devices and, more particularly, to medical devices that monitor physiological parameters.
  • BACKGROUND
  • [0003]
    In some cases, an ailment that a patient has may affect the quality of the patient's sleep. For example, chronic pain may cause a patient to have difficulty falling asleep, and may disturb the patient's sleep, e.g., cause the patient to wake. Further, chronic pain may cause the patient to have difficulty achieving deeper sleep states, such as one or more of the nonrapid eye movement (NREM) sleep states. Other ailments that may negatively affect patient sleep quality include movement disorders, psychological disorders, sleep apnea, congestive heart failure, gastrointestinal disorders and incontinence. In some cases, these ailments are treated via an implantable medical device (IMD), such as an implantable stimulator or drug delivery device.
  • [0004]
    Further, in some cases, poor sleep quality may increase the symptoms experienced by a patient due to an ailment. For example, poor sleep quality has been linked to increased pain symptoms in chronic pain patients. The link between poor sleep quality and increased symptoms is not limited to ailments that negatively impact sleep quality, such as those listed above. Nonetheless, the condition of a patient with such an ailment may progressively worsen when symptoms disturb sleep quality, which in turn increases the frequency and/or intensity of symptoms.
  • SUMMARY
  • [0005]
    In general, the invention is directed to techniques for collecting information that relates to the quality of patient sleep via a medical device, such as an implantable medical device (IMD). In particular, values for one or more metrics that indicate the quality of the patient's sleep are determined based on physiological parameters monitored by a medical device. In some embodiments, sleep quality information is presented to a user based on the sleep quality metric values. A clinician, for example, may use the presented sleep quality information to evaluate the effectiveness of therapy delivered to the patient by the medical device, to adjust the therapy delivered by the medical device, or to prescribe a therapy not delivered by the medical device in order to improve the quality of the patient's sleep.
  • [0006]
    The medical device that delivers the therapy or a separate monitoring device monitors one or more physiological parameters of the patient. Example physiological parameters that the medical device may monitor include activity level, posture, heart rate, electrocardiogram (ECG) morphology, respiration rate, respiratory volume, blood pressure, blood oxygen saturation, partial pressure of oxygen within blood, partial pressure of oxygen within cerebrospinal fluid, muscular activity and tone, core temperature, subcutaneous temperature, arterial blood flow, melatonin level within one or more bodily fluids, brain electrical activity, eye motion, and galvanic skin response. In order to monitor one or more of these parameters, the medical device or monitoring device may include, or be coupled to one or more sensors, each of which generates a signal as a function of one or more of these physiological parameters.
  • [0007]
    The medical device or monitoring device may determine a value of one or more sleep quality metrics based on the one or more monitored physiological parameters, and/or the variability of one or more of the monitored physiological parameters. In other embodiments, one or both of the medical device or monitoring device records values of the one or more physiological parameters, and provides the physiological parameter values to a programming device, such as a clinician programming device or a patient programming device, or another computing device. In such embodiments, the programming or other computing device determines values of one or more sleep quality metrics based on the physiological parameter values received from the medical device and/or the variability of one or more of the physiological parameters. The medical device or monitoring device may provide the recorded physiological parameter values to the programming or other computing device in real time, or may provide physiological parameter values recorded over a period of time to the programming or other computing device when interrogated.
  • [0008]
    Sleep efficiency and sleep latency are example sleep quality metrics for which a medical device or programming device may determine values. Sleep efficiency may be measured as the percentage of time while the patient is attempting to sleep that the patient is actually asleep. Sleep latency may be measured as the amount of time between a first time when the patient begins attempting to fall asleep and a second time when the patient falls asleep, and thereby indicates how long a patient requires to fall asleep.
  • [0009]
    The time when the patient begins attempting to fall asleep may be determined in a variety of ways. For example, the patient may provide an indication that he or she is trying to fall asleep, e.g., via a patient programming device. In other embodiments, the medical device or monitoring may monitor the activity level of the patient, and the time when the patient is attempting to fall asleep may be identified by determining whether the patient has remained inactive for a threshold period of time, and identifying the time at which the patient became inactive. In still other embodiments, the medical device or monitoring device may monitor patient posture, and the medical device or a programming device may identify the time when the patient is recumbent, e.g., lying down, as the time when the patient is attempting to fall asleep. In these embodiments, the medical device or monitoring device may also monitor patient activity, and either the medical device, monitoring device, programming device, or other computing device may confirm that the patient is attempting to sleep based on the patient's activity level.
  • [0010]
    As another example, the medical device or monitoring device may determine the time at which the patient begins attempting to fall asleep based on the level of melatonin within one or more bodily fluids, such as the patient's blood, cerebrospinal fluid (CSF), or interstitial fluid. The medical device or monitoring device may also determine a melatonin level based on metabolites of melatonin located in the saliva or urine of the patient. Melatonin is a hormone secreted by the pineal gland into the bloodstream and the CSF as a function of exposure of the optic nerve to light, which synchronizes the patient's circadian rhythm. In particular, increased levels of melatonin during evening hours may cause physiological changes in the patient, which, in turn, may cause the patient to attempt to fall asleep. The medical device or monitoring device may, for example, detect an increase in the level of melatonin, and estimate the time that the patient will attempt to fall asleep based on the detection.
  • [0011]
    The time at which the patient has fallen asleep may be determined based on the activity level of the patient and/or one or more of the other physiological parameters that may be monitored by the medical device as indicated above. For example, a discernable change, e.g., a decrease, in one or more physiological parameters, or the variability of one or more physiological parameters, may indicate that the patient has fallen asleep. In some embodiments, a sleep probability metric value may be determined based on a value of a physiological parameter monitored by the medical device. In such embodiments, the sleep probability metric value may be compared to a threshold to identify when the patient has fallen asleep. In some embodiments, a plurality of sleep probability metric values are determined based on a value of each of a plurality of physiological parameters, the sleep probability values are averaged or otherwise combined to provide an overall sleep probability metric value, and the overall sleep probability metric value is compared to a threshold to identify the time that the patient falls asleep.
  • [0012]
    Other sleep quality metrics that may be determined include total time sleeping per day, the amount or percentage of time sleeping during nighttime or daytime hours per day, and the number of apnea and/or arousal events per night. In some embodiments, which sleep state the patient is in, e.g., rapid eye movement (REM), or one of the nonrapid eye movement (NREM) states (S1, S2, S3, S4) may be determined based on physiological parameters monitored by the medical device, and the amount of time per day spent in these various sleep states may be a sleep quality metric. Because they provide the most “refreshing” type of sleep, the amount of time spent in one or both of the S3 and S4 sleep states, in particular, may be determined as a sleep quality metric. In some embodiments, average or median values of one or more sleep quality metrics over greater periods of time, e.g., a week or a month, may be determined as the value of the sleep quality metric. Further, in embodiments in which values for a plurality of the sleep quality metrics are determined, a value for an overall sleep quality metric may be determined based on the values for the plurality of individual sleep quality metrics.
  • [0013]
    In some embodiments, the medical device delivers a therapy. At any given time, the medical device delivers the therapy according to a current set of therapy parameters. For example, in embodiments in which the medical device is a neurostimulator, a therapy parameter set may include a pulse amplitude, a pulse width, a pulse rate, a duty cycle, and an indication of active electrodes. Different therapy parameter sets may be selected, e.g., by the patient via a programming device or a the medical device according to a schedule, and parameters of one or more therapy parameter sets may be adjusted by the patient to create new therapy parameter sets. In other words, over time, the medical device delivers the therapy according to a plurality of therapy parameter sets.
  • [0014]
    In embodiments in which the medical device determines sleep quality metric values, the medical device may identify the current therapy parameter set when a value of one or more sleep quality metrics is collected, and may associate that value with the therapy parameter set. For example, for each available therapy parameter set the medical device may store a representative value of each of one or more sleep quality metrics in a memory with an indication of the therapy programs with which that representative value is associated. A representative value of sleep quality metric for a therapy parameter set may be the mean or median of collected sleep quality metric values that have been associated with that therapy parameter set. In other embodiments in which a programming device or other computing device determines sleep quality metric values, the medical device may associate recorded physiological parameter values with the current therapy parameter set in the memory. Further, in embodiments in which a separate monitoring device records physiological parameter values or determines sleep quality metric values, the monitoring device may mark recorded physiological parameter values or sleep quality metric values with a current time in a memory, and the medical device may store an indication of a current therapy parameter set and time in a memory. A programming device of other computing device may receive indications of the physiological parameter values or sleep quality metrics and associated times from the monitoring device, and indications of the therapy parameter sets and associated times from the medical device, and may associate the physiological parameter values or sleep quality metrics with the therapy parameter set that was delivered by the medical device when the physiological parameter values or sleep quality metrics were collected.
  • [0015]
    A programming device or other computing device according to the invention may be capable of wireless communication with the medical device, and may receive sleep quality metric values or recorded physiological parameter values from the medical device or a separate monitoring device. In either case, when the computing device either receives or determines sleep quality metric values, the computing device may provide sleep quality information to a user based on the sleep quality metric values. For example, the computing device may be a patient programmer, and may provide a message to the patient related to sleep quality. The patient programmer may, for example, suggest that the patient visit a clinician for prescription of sleep medication or for an adjustment to the therapy delivered by the medical device. As other examples, the patient programmer may suggest that the patient increase the intensity of therapy delivered by the medical device during nighttime hours relative to previous nights, or select a different therapy parameter set for use during sleep than the patient had selected during previous nights. Further, the patient programmer may provide a message that indicates the quality of sleep to the patient to, for example, provide the patient with an objective indication of whether his or her sleep quality is good, adequate, or poor.
  • [0016]
    In other embodiments, the computing device is a clinician programmer that presents information relating to the quality of the patient's sleep to a clinician. The clinician programmer may present, for example, a trend diagram of values of one or more sleep quality metrics over time. As other examples, the clinician programmer may present a histogram or pie chart illustrating percentages of time that a sleep quality metric was within various value ranges.
  • [0017]
    As indicated above, the computing device may receive representative values for one or more sleep quality metrics or the physiological parameter values from the therapy delivering medical device or separate monitoring device. The computing device may receive information identifying the therapy parameter set with which the representative values are associated, or may itself associate received physiological parameter or sleep quality metric values with therapy parameter sets based on time information received from one or more devices. In embodiments in which the computing device receives physiological parameter values, the computing device may determine sleep quality metric values associated with the plurality of parameter sets based on the physiological parameter values, and representative sleep quality metric values for each of the therapy parameter sets based on the sleep quality metric values associated with the therapy parameter sets. In some embodiments, the computing device may determine the variability of one or more of the physiological parameters based on the physiological parameter values received from the medical device or monitoring device, and may determine sleep quality metric values based on the physiological parameter variabilities.
  • [0018]
    The computing device may display a list of the therapy parameter sets to the clinician ordered according to their associated representative sleep quality metric values. Such a list may be used by the clinician to identify effective or ineffective therapy parameter sets. Where a plurality of sleep quality metric values are determined, the programming device may order the list according to values of a user-selected one of the sleep quality metrics.
  • [0019]
    In other embodiments, a system according to the invention does not include a programming or other computing device. For example, an external medical device according to the invention may include a display, determine sleep quality metric values, and display sleep quality information to a user via the display based on the sleep quality metric values.
  • [0020]
    In one embodiment, the invention is directed to a method in which at least one physiological parameter of a patient is monitored. A value of a metric that is indicative of sleep quality is determined based on the at least one physiological parameter. A current therapy parameter set used by a medical device to delivery a therapy to the patient is identified, and the sleep quality metric value is associated with the current therapy parameter set.
  • [0021]
    In another embodiment, the invention is directed to a medical system comprising a medical device, and monitor, and a processor. The medical device delivers a therapy to a patient, and the monitor monitors at least one physiological parameter of a patient based on a signal received from at least one sensor. The processor determines a value of a metric that is indicative of sleep quality based on the at least one physiological parameter, identifies a current therapy parameter set, and associates the sleep quality metric value with the current therapy parameter set. The medical device may comprise the monitor.
  • [0022]
    In another embodiment, the invention is directed to a medical system comprising means for monitoring at least one physiological parameter of a patient, means for determining a value of a metric that is indicative of sleep quality based on the at least one physiological parameter, means for identifying a current therapy parameter set used by a medical device to delivery therapy to the patient, and means for associating the sleep quality metric value with the current therapy parameter set.
  • [0023]
    In another embodiment, the invention is directed to a medical system comprising an implantable medical device and an external programming device including a display. The implantable medical device delivers a therapy to a patient, monitors at least one physiological parameter of the patient, and determines a plurality of values of a metric that is indicative of sleep quality based on the at least one physiological parameter. The external programming device receives sleep quality metric values from the implantable medical device, and presents sleep quality information to a user via the display based on the sleep quality metric values.
  • [0024]
    In another embodiment, the invention is directed to a programming device comprising a telemetry circuit, a user interface including a display, and a processor. The processor receives sleep quality metric values from a medical device via the telemetry circuit. The medical device delivers therapy according to a plurality of therapy parameter sets, and associates each of the sleep quality metric values with a current therapy parameter set. The processor receives information identifying the plurality of therapy parameter sets and the sleep quality metric values associated with the therapy parameter sets from the medical device, presents a list of the therapy parameter sets and the associated sleep quality metric values to a user, and orders the list according to the associated sleep quality metric values.
  • [0025]
    In another embodiment, the invention is directed to a computer-readable medium comprising program instructions. The program instructions cause a programmable processor to receive sleep quality metric values from a medical device that delivers therapy according to a plurality of parameter sets, and associates each of the sleep quality metric values with a current therapy parameter set. The instructions further cause a processor to receive information identifying the plurality of therapy parameter sets and the sleep quality metric values associated with the therapy parameter sets from the medical device, present a list of the therapy parameter sets and the associated sleep quality metric values to a user, and order the list of therapy parameter sets according to the associated sleep quality metric values.
  • [0026]
    In another embodiment, the invention is directed to a method in which a plurality of signals are monitored, each of the signals generated by a sensor as a function of at least one physiological parameter of a patient. When the patient is attempting to sleep is identified. When the patient is asleep is identified based on at least one of the signals. A value of a metric that is indicative of sleep quality is determined based on the identifications of when the patient is attempting to sleep and asleep.
  • [0027]
    In another embodiment, the invention is directed to a medical system comprising a plurality of sensors and a processor. Each of the plurality of sensors generates a signal as a function of at least one physiological parameter of a patient. The processor monitors the signals generated by the sensors, identifies when the patient is attempting to sleep, identifies when the patient is asleep based on at least one of the signals, and determines a value of a metric that is indicative of sleep quality based on the identifications of when the patient is attempting to sleep and asleep.
  • [0028]
    The invention may be capable of providing one or more advantages. For example, by providing information related to the quality of a patient's sleep to a clinician and/or the patient, a system according to the invention can improve the course of treatment of an ailment of the patient, such as chronic pain. Using the sleep quality information provided by the system, the clinician and/or patient can, for example, make changes to the therapy provided by a medical device in order to better address symptoms which are disturbing the patient's sleep. Further, a clinician may choose to prescribe a therapy that will improve the patient's sleep, such as a sleep inducing medication, in situations where poor sleep quality is increasing symptoms experienced by the patient.
  • [0029]
    The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.
  • BRIEF DESCRIPTION OF DRAWINGS
  • [0030]
    FIG. 1 is a conceptual diagram illustrating an example system that includes an implantable medical device that collects sleep quality information according to the invention.
  • [0031]
    FIG. 2 is a block diagram further illustrating the example system and implantable medical device of FIG. 1.
  • [0032]
    FIG. 3 is a block diagram illustrating an example memory of the implantable medical device of FIG. 1.
  • [0033]
    FIG. 4 is a flow diagram illustrating an example method for collecting sleep quality information that may be employed by an implantable medical device.
  • [0034]
    FIG. 5 is a flow diagram illustrating an example method for associating sleep quality information with therapy parameter sets that may be employed by an implantable medical device.
  • [0035]
    FIG. 6 is a block diagram illustrating an example clinician programmer.
  • [0036]
    FIG. 7 is a flow diagram illustrating an example method for presenting sleep quality information to a clinician that may be employed by a clinician programmer.
  • [0037]
    FIG. 8 illustrates an example list of therapy parameter sets and associated sleep quality information that may be presented by a clinician programmer.
  • [0038]
    FIG. 9 is a flow diagram illustrating an example method for displaying a list of therapy parameter sets and associated sleep quality information that may be employed by a clinician programmer.
  • [0039]
    FIG. 10 is a block diagram illustrating an example patient programmer.
  • [0040]
    FIG. 11 is a flow diagram illustrating an example method for presenting a sleep quality message to a patient that may be employed by a patient programmer.
  • [0041]
    FIG. 12 is a conceptual diagram illustrating a monitor that monitors values of one or more physiological parameters of the patient instead of, or in addition to, a therapy delivering medical device.
  • DETAILED DESCRIPTION
  • [0042]
    FIG. 1 is a conceptual diagram illustrating an example system 10 that includes an implantable medical device (IMD) 14 that collects information relating to the quality of sleep experienced by a patient 12 according to the invention. Sleep quality information collected by IMD 14 is provided to a user, such as a clinician or the patient. Using the sleep quality information collected by IMD 14, a current course of therapy for an ailment of patient 12 may be evaluated, and an improved course of therapy for the ailment may be identified.
  • [0043]
    In the illustrated example system 10, IMD 14 takes the form of an implantable neurostimulator that delivers neurostimulation therapy in the form of electrical pulses to patient 12. However, the invention is not limited to implementation via an implantable neurostimulator. For example, in some embodiments of the invention, an implantable pump or implantable cardiac rhythm management device, such as a pacemaker, may collect sleep quality information. Further, the invention is not limited to implementation via an IMD. In other words, any implantable or external medical device may collect sleep quality information according to the invention.
  • [0044]
    In the example of FIG. 1, IMD 14 delivers neurostimulation therapy to patient 12 via leads 16A and 16B (collectively “leads 16”). Leads 16 may, as shown in FIG. 1, be implanted proximate to the spinal cord 18 of patient 12, and IMD 14 may deliver spinal cord stimulation (SCS) therapy to patient 12 in order to, for example, reduce pain experienced by patient 12. However, the invention is not limited to the configuration of leads 16 shown in FIG. 1 or the delivery of SCS therapy. For example, one or more leads 16 may extend from IMD 14 to the brain (not shown) of patient 12, and IMD 14 may deliver deep brain stimulation (DBS) therapy to patient 12 to, for example, treat tremor or epilepsy. As further examples, one or more leads 16 may be implanted proximate to the pelvic nerves (not shown) or stomach (not shown), and IMD 14 may deliver neurostimulation therapy to treat incontinence or gastroparesis.
  • [0045]
    IMD 14 delivers therapy according to a set of therapy parameters, i.e., a set of values for a number of parameters that define the therapy delivered according to that therapy parameter set. In embodiments where IMD 14 delivers neurostimulation therapy in the form of electrical pulses, the parameters in each parameter set may include voltage or current pulse amplitudes, pulse widths, pulse rates, and the like. Further, each of leads 16 includes electrodes (not shown in FIG. 1), and a therapy parameter set may include information identifying which electrodes have been selected for delivery of pulses, and the polarities of the selected electrodes. Therapy parameter sets used by IMD 14 may include a number of parameter sets programmed by a clinician (not shown), and parameter sets representing adjustments made by patient 12 to these preprogrammed sets.
  • [0046]
    System 10 also includes a clinician programmer 20. A clinician (not shown) may use clinician programmer 20 to program therapy for patient 12, e.g., specify a number of therapy parameter sets and provide the parameter sets to IMD 14. The clinician may also use clinician programmer 20 to retrieve information collected by IMD 14. The clinician may use clinician programmer 20 to communicate with IMD 14 both during initial programming of IMD 14, and for collection of information and further programming during follow-up visits.
  • [0047]
    Clinician programmer 20 may, as shown in FIG. 1, be a handheld computing device. Clinician programmer 20 includes a display 22, such as a LCD or LED display, to display information to a user. Clinician programmer 20 may also include a keypad 24, which may be used by a user to interact with clinician programmer 20. In some embodiments, display 22 may be a touch screen display, and a user may interact with clinician programmer 20 via display 22. A user may also interact with clinician programmer 20 using peripheral pointing devices, such as a stylus or mouse. Keypad 24 may take the form of an alphanumeric keypad or a reduced set of keys associated with particular functions.
  • [0048]
    System 10 also includes a patient programmer 26, which also may, as shown in FIG. 1, be a handheld computing device. Patient 12 may use patient programmer 26 to control the delivery of therapy by IMD 14. For example, using patient programmer 26, patient 12 may select a current therapy parameter set from among the therapy parameter sets preprogrammed by the clinician, or may adjust one or more parameters of a preprogrammed therapy parameter set to arrive at the current therapy parameter set.
  • [0049]
    Patient programmer 26 may include a display 28 and a keypad 30, to allow patient 12 to interact with patient programmer 26. In some embodiments, display 28 may be a touch screen display, and patient 12 may interact with patient programmer 26 via display 28. Patient 12 may also interact with patient programmer 26 using peripheral pointing devices, such as a stylus, mouse, or the like.
  • [0050]
    However, clinician and patient programmers 20, 26 are not limited to the hand-held computer embodiments illustrated in FIG. 1. Programmers 20, 26 according to the invention may be any sort of computing device. For example, a programmer 20, 26 according to the invention may be a tablet-based computing device, a desktop computing device, or a workstation.
  • [0051]
    IMD 14, clinician programmer 20 and patient programmer 26 may, as shown in FIG. 1, communicate via wireless communication. Clinician programmer 20 and patient programmer 26 may, for example, communicate via wireless communication with IMD 14 using radio frequency (RF) telemetry techniques known in the art. Clinician programmer 20 and patient programmer 26 may communicate with each other using any of a variety of local wireless communication techniques, such as RF communication according to the 802.11 or Bluetooth specification sets, infrared communication according to the IRDA specification set, or other standard or proprietary telemetry protocols.
  • [0052]
    Clinician programmer 20 and patient programmer 26 need not communicate wirelessly, however. For example, programmers 20 and 26 may communicate via a wired connection, such as via a serial communication cable, or via exchange of removable media, such as magnetic or optical disks, or memory cards or sticks. Further, clinician programmer 20 may communicate with one or both of IMD 14 and patient programmer 26 via remote telemetry techniques known in the art, communicating via a local area network (LAN), wide area network (WAN), public switched telephone network (PSTN), or cellular telephone network, for example.
  • [0053]
    As mentioned above, IMD 14 collects information relating to the quality of sleep experienced by patient 12. Specifically, as will be described in greater detail below, IMD 14 monitors one or more physiological parameters of patient 12, and determines values for one or more metrics that indicate the quality of sleep based on values of the physiological parameters. Example physiological parameters that IMD 14 may monitor include activity level, posture, heart rate, ECG morphology, respiration rate, respiratory volume, blood pressure, blood oxygen saturation, partial pressure of oxygen within blood, partial pressure of oxygen within cerebrospinal fluid (CSF), muscular activity and tone, core temperature, subcutaneous temperature, arterial blood flow, the level of melatonin within one or more bodily fluids, brain electrical activity, and eye motion. In some external medical device embodiments of the invention, galvanic skin response may additionally or alternatively be monitored. Further, in some embodiments, IMD 14 additionally or alternatively monitors the variability of one or more of these parameters. In order to monitor one or more of these parameters, IMD 14 may include or be coupled to one or more sensors (not shown in FIG. 1), each of which generates a signal as a function of one or more of these physiological parameters.
  • [0054]
    For example, IMD 14 may determine sleep efficiency and/or sleep latency values. Sleep efficiency and sleep latency are example sleep quality metrics. IMD 14 may measure sleep efficiency as the percentage of time while patient 12 is attempting to sleep that patient 12 is actually asleep. IMD 14 may measure sleep latency as the amount of time between a first time when patient 12 begins attempting to fall asleep and a second time when patient 12 falls asleep.
  • [0055]
    IMD 14 may identify the time at which patient begins attempting to fall asleep in a variety of ways. For example, IMD 14 may receive an indication from the patient that the patient is trying to fall asleep via patient programmer 26. In other embodiments, IMD 14 may monitor the activity level of patient 12, and identify the time when patient 12 is attempting to fall asleep by determining whether patient 12 has remained inactive for a threshold period of time, and identifying the time at which patient 12 became inactive. In still other embodiments, IMD 14 may monitor the posture of patient 12, and may identify the time when the patient 12 becomes recumbent, e.g., lies down, as the time when patient 12 is attempting to fall asleep. In these embodiments, IMD 14 may also monitor the activity level of patient 12, and confirm that patient 12 is attempting to sleep based on the activity level.
  • [0056]
    As another example, IMD 14 may determine the time at which patient 12 is attempting to fall asleep based on the level of melatonin within one or more bodily fluids of patient 12, such as the patient's blood, cerebrospinal fluid (CSF), or interstitial fluid. IMD 14 may also determine a melatonin level based on metabolites of melatonin located in the saliva or urine of the patient. Melatonin is a hormone secreted by the pineal gland into the bloodstream and the CSF as a function of exposure of the optic nerve to light, which synchronizes the patient's circadian rhythm. In particular, increased levels of melatonin during evening hours may cause physiological changes in patient 12, which, in turn, may cause patient 12 to attempt to fall asleep.
  • [0057]
    IMD 14 may, for example, detect an increase in the level of melatonin in a bodily fluid, and estimate the time that patient 12 will attempt to fall asleep based on the detection. For example, IMD 14 may compare the melatonin level or rate of change in the melatonin level to a threshold level, and identify the time that threshold value is exceeded. IMD 14 may identify the time that patient 12 is attempting to fall asleep as the time that the threshold is exceeded, or some amount of time after the threshold is exceeded.
  • [0058]
    IMD 14 may identify the time at which patient 12 has fallen asleep based on the activity level of the patient and/or one or more of the other physiological parameters that may be monitored by IMD 14 as indicated above. For example, IMD 14 may identify a discernable change, e.g., a decrease, in one or more physiological parameters, or the variability of one or more physiological parameters, which may indicate that patient 12 has fallen asleep. In some embodiments, IMD 14 determines a sleep probability metric value based on a value of a physiological parameter monitored by the medical device. In such embodiments, the sleep probability metric value may be compared to a threshold to identify when the patient has fallen asleep. In some embodiments, a sleep probability metric value is determined based on a value of each of a plurality of physiological parameters, the sleep probability values are averaged or otherwise combined to provide an overall sleep probability metric value, and the overall sleep probability metric value is compared to a threshold to identify the time that the patient falls asleep.
  • [0059]
    Other sleep quality metrics include total time sleeping per day, and the amount or percentage of time sleeping during nighttime or daytime hours per day. In some embodiments, IMD 14 may be able to detect arousal events and apneas occurring during sleep based on one or more monitored physiological parameters, and the number of apnea and/or arousal events per night may be determined as a sleep quality metric. Further, in some embodiments IMD 14 may be able to determine which sleep state patient 12 is in based on one or more monitored physiological parameters, e.g., rapid eye movement (REM), S1, S2, S3, or S4, and the amount of time per day spent in these various sleep states may be a sleep quality metric.
  • [0060]
    The S3 and S4 sleep states may be of particular importance to the quality of sleep experienced by patient 12. Interruption from reaching these states, or inadequate time per night spent in these states, may cause patient 12 to not feel rested. For this reason, the S3 and S4 sleep states are believed to provide the “refreshing” part of sleep.
  • [0061]
    In some cases, interruption from reaching the S3 and S4 sleep states, or inadequate time per night spent in these states has been demonstrated to cause normal subjects to exhibit some symptoms of fibromyalgia. Also, subjects with fibromyalgia usually do not reach these sleep states. For these reasons, in some embodiments, IMD 14 may determine an amount or percentage of time spent in one or both of the S3 and S4 sleep states as a sleep quality metric.
  • [0062]
    In some embodiments, IMD 14 may determine average or median values of one or more sleep quality metrics over greater periods of time, e.g., a week or a month, as the value of the sleep quality metric. Further, in embodiments in which IMD 14 collects values for a plurality of the sleep quality metrics identified above, IMD 14 may determine a value for an overall sleep quality metric based on the collected values for the plurality of sleep quality metrics. IMD 14 may determine the value of an overall sleep quality metric by applying a function or look-up table to a plurality of sleep quality metric values, which may also include the application of weighting factors to one or more of the individual sleep quality metric values.
  • [0063]
    In some embodiments, IMD 14 may identify the current set of therapy parameters when a value of one or more sleep quality metrics is collected, and may associate that value with the current therapy parameter sets. For example, for each of a plurality therapy parameter sets used over time by IMD 14 to deliver therapy to patient 12, IMD 14 may store a representative value of each of one or more sleep quality metrics in a memory with an indication of the therapy parameter set with which that representative value is associated. A representative value of sleep quality metric for a therapy parameter set may be the mean or median of collected sleep quality metric values that have been associated with that therapy parameter set.
  • [0064]
    One or both of programmers 20, 26 may receive sleep quality metric values from IMD 14, and may provide sleep quality information to a user based on the sleep quality metric values. For example, patient programmer 26 may provide a message to patient 12, e.g., via display 28, related to sleep quality based on received sleep quality metric values. Patient programmer 26 may, for example, suggest that patient 12 visit a clinician for prescription of sleep medication or for an adjustment to the therapy delivered by IMD 14. As other examples, patient programmer 26 may suggest that patient 12 increase the intensity of therapy delivered by IMD 14 during nighttime hours relative to previous nights, or select a different therapy parameter set for use by IMD 14 than the patient had selected during previous nights. Further, patient programmer 26 may report the quality of the patient's sleep to patient 12 to, for example, provide patient 12 with an objective indication of whether his or her sleep quality is good, adequate, or poor.
  • [0065]
    Clinician programmer 20 may receive sleep quality metric values from IMD 14, and present a variety of types of sleep information to a clinician, e.g., via display 22, based on the sleep quality metric values. For example, clinician programmer 20 may present a graphical representation of the sleep quality metric values, such as a trend diagram of values of one or more sleep quality metrics over time, or a histogram or pie chart illustrating percentages of time that a sleep quality metric was within various value ranges.
  • [0066]
    In embodiments in which IMD 14 associates sleep quality metric values with therapy parameter sets, clinician programmer 20 may receive representative values for one or more sleep quality metrics from IMD 14 and information identifying the therapy parameter sets with which the representative values are associated. Using this information, clinician programmer 20 may display a list of the therapy parameter sets to the clinician ordered according to their associated representative sleep quality metric values. The clinician may use such a list to identify effective or ineffective therapy parameter sets. Where a plurality of sleep quality metric values are collected, clinician programmer 20 may order the list according to values of a user-selected one of the sleep quality metrics. In this manner, the clinician may quickly identify the therapy parameter sets producing the best results in terms of sleep quality.
  • [0067]
    FIG. 2 is a block diagram further illustrating system 10. In particular, FIG. 2 illustrates an example configuration of IMD 14 and leads 16A and 16B. FIG. 2 also illustrates sensors 40A and 40B (collectively “sensors 40”) that generate signals as a function of one or more physiological parameters of patient 12. As will be described in greater detail below, IMD 14 monitors the signals to determine values for one or more metrics that are indicative of sleep quality.
  • [0068]
    IMD 14 may deliver neurostimulation therapy via electrodes 42A-D of lead 16A and electrodes 42E-H of lead 16B (collectively “electrodes 42”). Electrodes 42 may be ring electrodes. The configuration, type and number of electrodes 42 illustrated in FIG. 2 are merely exemplary. For example, leads 16A and 16B may each include eight electrodes 42, and the electrodes 42 need not be arranged linearly on each of leads 16A and 16B.
  • [0069]
    Electrodes 42 are electrically coupled to a therapy delivery module 44 via leads 16A and 16B. Therapy delivery module 44 may, for example, include an output pulse generator coupled to a power source such as a battery. Therapy delivery module 44 may deliver electrical pulses to patient 12 via at least some of electrodes 42 under the control of a processor 46, which controls therapy delivery module 44 to deliver neurostimulation therapy according to to a current therapy parameter set. However, the invention is not limited to implantable neurostimulator embodiments or even to IMDs that deliver electrical stimulation. For example, in some embodiments a therapy delivery module 44 of an IMD may include a pump, circuitry to control the pump, and a reservoir to store a therapeutic agent for delivery via the pump.
  • [0070]
    Processor 46 may include a microprocessor, a controller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), discrete logic circuitry, or the like. Memory 48 may include any volatile, non-volatile, magnetic, optical, or electrical media, such as a random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), electrically-erasable programmable ROM (EEPROM), flash memory, and the like. In some embodiments, memory 48 stores program instructions that, when executed by processor 46, cause IMD 14 and processor 46 to perform the functions attributed to them herein.
  • [0071]
    Each of sensors 40 generates a signal as a function of one or more physiological parameters of patient 12. IMD 14 may include circuitry (not shown) that conditions the signals generated by sensors 40 such that they may be analyzed by processor 46. For example, IMD 14 may include one or more analog to digital converters to convert analog signals generated by sensors 40 into digital signals usable by processor 46, as well as suitable filter and amplifier circuitry. Although shown as including two sensors 40, system 10 may include any number of sensors.
  • [0072]
    Further, as illustrated in FIG. 2, sensors 40 may be included as part of IMD 14, or coupled to IMD 14 via leads 16. Sensors 40 may be coupled to IMD 14 via therapy leads 16A and 16B, or via other leads 16, such as lead 16C depicted in FIG. 2. In some embodiments, a sensor 40 located outside of IMD 14 may be in wireless communication with processor 46. Wireless communication between sensors 40 and IMD 14 may, as examples, include RF communication or communication via electrical signals conducted through the tissue and/or fluid of patient 12.
  • [0073]
    As discussed above, exemplary physiological parameters of patient 12 that may be monitored by IMD 14 to determine values of one or more sleep quality metrics include activity level, posture, heart rate, ECG morphology, respiration rate, respiratory volume, blood pressure, blood oxygen saturation, partial pressure of oxygen within blood, partial pressure of oxygen within cerebrospinal fluid, muscular activity and tone, core temperature, subcutaneous temperature, arterial blood flow, the level of melatonin within a bodily fluid of patient 12, electrical activity of the brain of the patient, and eye motion. Further, as discussed above, in some external medical device embodiments of the invention, galvanic skin response may additionally or alternatively be monitored. Sensors 40 may be of any type known in the art capable of generating a signal as a function of one or more of these parameters.
  • [0074]
    In some embodiments, in order to determine one or more sleep quality metric values, processor 46 determines when patient 12 is attempting to fall asleep. For example, processor 46 may identify the time that patient begins attempting to fall asleep based on an indication received from patient 12, e.g., via clinician programmer 20 and a telemetry circuit 50. In other embodiments, processor 46 identifies the time that patient 12 begins attempting to fall asleep based on the activity level of patient 12.
  • [0075]
    In such embodiments, IMD 14 may include one or more sensors 40 that generate a signal as a function of patient activity. For example, sensors 40 may include one or more accelerometers, gyros, mercury switches, or bonded piezoelectric crystals that generates a signal as a function of patient activity, e.g., body motion, footfalls or other impact events, and the like. Additionally or alternatively, sensors 40 may include one or more electrodes that generate an electromyogram (EMG) signal as a function of muscle electrical activity, which may indicate the activity level of a patient. The electrodes may be, for example, located in the legs, abdomen, chest, back or buttocks of patient 12 to detect muscle activity associated with walking, running, or the like. The electrodes may be coupled to IMD 14 wirelessly or by leads 16 or, if IMD 14 is implanted in these locations, integrated with a housing of IMD 14.
  • [0076]
    However, bonded piezoelectric crystals located in these areas generate signals as a function of muscle contraction in addition to body motion, footfalls or other impact events. Consequently, use of bonded piezoelectric crystals to detect activity of patient 12 may be preferred in some embodiments in which it is desired to detect muscle activity in addition to body motion, footfalls, or other impact events. Bonded piezoelectric crystals may be coupled to IMD 14 wirelessly or via leads 16, or piezoelectric crystals may be bonded to the can of IMD 14 when the IMD is implanted in these areas, e.g., in the back, chest, buttocks or abdomen of patient 12.
  • [0077]
    Processor 46 may identify a time when the activity level of patient 12 falls below a threshold activity level value stored in memory 48, and may determine whether the activity level remains substantially below the threshold activity level value for a threshold amount of time stored in memory 48. In other words, patient 12 remaining inactive for a sufficient period of time may indicate that patient 12 is attempting to fall asleep. If processor 46 determines that the threshold amount of time is exceeded, processor 46 may identify the time at which the activity level fell below the threshold activity level value as the time that patient 12 began attempting to fall asleep.
  • [0078]
    In some embodiments, processor 46 determines whether patient 12 is attempting to fall asleep based on whether patient 12 is or is not recumbent, e.g., lying down. In such embodiments, sensors 40 may include a plurality of accelerometers, gyros, or magnetometers oriented orthogonally that generate signals which indicate the posture of patient 12. In addition to being oriented orthogonally with respect to each other, each of sensors 40 used to detect the posture of patient 12 may be generally aligned with an axis of the body of patient 12. In exemplary embodiments, IMD 14 includes three orthogonally oriented posture sensors 40.
  • [0079]
    When sensors 40 include accelerometers, for example, that are aligned in this manner, processor 46 may monitor the magnitude and polarity of DC components of the signals generated by the accelerometers to determine the orientation of patient 12 relative to the Earth's gravity, e.g., the posture of patient 12. In particular, the processor 46 may compare the DC components of the signals to respective threshold values stored in memory 48 to determine whether patient 12 is or is not recumbent. Further information regarding use of orthogonally aligned accelerometers to determine patient posture may be found in a commonly assigned U.S. Pat. No. 5,593,431, which issued to Todd J. Sheldon.
  • [0080]
    Other sensors 40 that may generate a signal that indicates the posture of patient 12 include electrodes that generate an electromyogram (EMG) signal, or bonded piezoelectric crystals that generate a signal as a function of contraction of muscles. Such sensors 40 may be implanted in the legs, buttocks, chest, abdomen, or back of patient 12, as described above. The signals generated by such sensors when implanted in these locations may vary based on the posture of patient 12, e.g., may vary based on whether the patient is standing, sitting, or laying down.
  • [0081]
    Further, the posture of patient 12 may affect the thoracic impedance of the patient. Consequently, sensors 40 may include an electrode pair, including one electrode integrated with the housing of IMD 14 and one of electrodes 42, that generates a signal as a function of the thoracic impedance of patient 12, and processor 46 may detect the posture or posture changes of patient 12 based on the signal. The electrodes of the pair may be located on opposite sides of the patient's thorax. For example, the electrode pair may include one of electrodes 42 located proximate to the spine of a patient for delivery of SCS therapy, and IMD 14 with an electrode integrated in its housing may be implanted in the abdomen of patient 12.
  • [0082]
    Additionally, changes of the posture of patient 12 may cause pressure changes with the cerebrospinal fluid (CSF) of the patient. Consequently, sensors 40 may include pressure sensors coupled to one or more intrathecal or intracerebroventricular catheters, or pressure sensors coupled to IMD 14 wirelessly or via lead 16. CSF pressure changes associated with posture changes may be particularly evident within the brain of the patient, e.g., may be particularly apparent in an intracranial pressure (ICP) waveform.
  • [0083]
    In some embodiments, processor 46 considers both the posture and the activity level of patient 12 when determining whether patient 12 is attempting to fall asleep. For example, processor 46 may determine whether patient 12 is attempting to fall asleep based on a sufficiently long period of sub-threshold activity, as described above, and may identify the time that patient began attempting to fall asleep as the time when patient 12 became recumbent.
  • [0084]
    In other embodiments, processor 46 determines when patient 12 is attempting to fall asleep based on the level of melatonin in a bodily fluid. In such embodiments, a sensor 40 may take the form of a chemical sensor that is sensitive to the level of melatonin or a metabolite of melatonin in the bodily fluid, and estimate the time that patient 12 will attempt to fall asleep based on the detection. For example, processor 46 may compare the melatonin level or rate of change in the melatonin level to a threshold level stored in memory 48, and identify the time that threshold value is exceeded. Processor 46 may identify the time that patient 12 is attempting to fall asleep as the time that the threshold is exceeded, or some amount of time after the threshold is exceeded. Any of a variety of combinations or variations of the above-described techniques may be used to determine when patient 12 is attempting to fall asleep, and a specific one or more techniques may be selected based on the sleeping and activity habits of a particular patient.
  • [0085]
    Processor 46 may also determine when patient 12 is asleep, e.g., identify the times that patient 12 falls asleep and wakes up, in order to determine one or more sleep quality metric values. The detected values of physiological parameters of patient 12, such as activity level, heart rate, ECG morphological features, respiration rate, respiratory volume, blood pressure, blood oxygen saturation, partial pressure of oxygen within blood, partial pressure of oxygen within cerebrospinal fluid, muscular activity and tone, core temperature, subcutaneous temperature, arterial blood flow, brain electrical activity, eye motion and galvanic skin response may discernibly change when patient 12 falls asleep or wakes up. Some of these physiological parameters may be at low values when patient 12 is asleep. Further, the variability of at least some of these parameters, such as heart rate and respiration rate, may be at a low value when the patient is asleep.
  • [0086]
    Consequently, in order to detect when patient 12 falls asleep and wakes up, processor 46 may monitor one or more of these physiological parameters, or the variability of these physiological parameters, and detect the discernable changes in their values associated with a transition between a sleeping state and an awake state. In some embodiments, processor 46 may determine a mean or median value for a parameter based on values of a signal over time, and determine whether patient 12 is asleep or awake based on the mean or median value. Processor 46 may compare one or more parameter or parameter variability values to thresholds stored in memory 48 to detect when patient 12 falls asleep or awakes. The thresholds may be absolute values of a physiological parameter, or time rate of change values for the physiological parameter, e.g., to detect sudden changes in the value of a parameter or parameter variability. In some embodiments, a threshold used by processor 46 to determine whether patient 12 is asleep may include a time component. For example, a threshold may require that a physiological parameter be above or below a threshold value for a period of time before processor 46 determines that patient is awake or asleep.
  • [0087]
    In some embodiments, in order to determine whether patient 12 is asleep, processor 46 monitors a plurality of physiological parameters, and determines a value of a metric that indicates the probability that patient 12 is asleep for each of the parameters based on a value of the parameter. In particular, the processor 46 may apply a function or look-up table to the current, mean or median value, and/or the variability of each of a plurality of physiological parameters to determine a sleep probability metric for each of the plurality of physiological parameters. A sleep probability metric value may be a numeric value, and in some embodiments may be a probability value, e.g., a number within the range from 0 to 1, or a percentage value.
  • [0088]
    Processor 46 may average or otherwise combine the plurality of sleep probability metric values to provide an overall sleep probability metric value. In some embodiments, processor 46 may apply a weighting factor to one or more of the sleep probability metric values prior to combination. Processor 46 may compare the overall sleep probability metric value to one or more threshold values stored in memory 48 to determine when patient 12 falls asleep or awakes. Use of sleep probability metric values to determine when a patient is asleep based on a plurality of monitored physiological parameters is described in greater detail in a commonly-assigned and copending U.S. patent application Ser. No. ______ by Ken Heruth and Keith Miesel, entitled “DETECTING SLEEP,” which was assigned Attorney Docket No. 1023-360US02 and filed on Mar. 16, 2005, and is incorporated herein by reference in its entirety.
  • [0089]
    To enable processor 46 to determine when patient 12 is asleep or awake, sensors 40 may include, for example, activity sensors as described above. In some embodiments, the activity sensors may include electrodes or bonded piezoelectric crystals, which may be implanted in the back, chest, buttocks, or abdomen of patient 12 as described above. In such embodiments, processor 46 may detect the electrical activation and contractions of muscles associated with gross motor activity of the patient, e.g., walking, running or the like via the signals generated by such sensors. Processor 46 may also detect spasmodic or pain related muscle activation via the signals generated by such sensors. Spasmodic or pain related muscle activation may indicate that patient 12 is not sleeping, e.g., unable to sleep, or if patient 12 is sleeping, may indicate a lower level of sleep quality.
  • [0090]
    As another example, sensors 40 may include electrodes located on leads or integrated as part of the housing of IMD 14 that generate an electrogram signal as a function of electrical activity of the heart of patient 12, and processor 46 may monitor the heart rate of patient 12 based on the electrogram signal. In other embodiments, a sensor may include an acoustic sensor within IMD 14, a pressure or flow sensor within the bloodstream or cerebrospinal fluid of patient 12, or a temperature sensor located within the bloodstream of patient 12. The signals generated by such sensors may vary as a function of contraction of the heart of patient 12, and can be used by IMD 14 to monitor the heart rate of patient 12.
  • [0091]
    In some embodiments, processor 46 may detect, and measure values for one or more ECG morphological features within an electrogram generated by electrodes as described above. ECG morphological features may vary in a manner that indicates whether patient 12 is asleep or awake. For example, the amplitude of the ST segment of the ECG may decrease when patient 12 is asleep. Further, the amplitude of QRS complex or T-wave may decrease, and the widths of the QRS complex and T-wave may increase when patient 12 is asleep. The QT interval and the latency of an evoked response may increase when patient 12 is asleep, and the amplitude of the evoked response may decrease when patient 12 is asleep.
  • [0092]
    In some embodiments, sensors 40 may include an electrode pair, including one electrode integrated with the housing of IMD 14 and one of electrodes 42, that generates a signal as a function of the thoracic impedance of patient 12, as described above. The thoracic impedance signal varies as a function of respiration by patient 12. In other embodiments, sensors 40 may include a strain gage, bonded piezoelectric element, or pressure sensor within the blood or cerebrospinal fluid that generates a signal that varies based on patient respiration. An electrogram generated by electrodes as discussed above may also be modulated by patient respiration, and may be used as an indirect representation of respiration rate.
  • [0093]
    Sensors 40 may include electrodes that generate an electromyogram (EMG) signal as a function of muscle electrical activity, as described above, or may include any of a variety of known temperature sensors to generate a signal as a function of a core or subcutaneous temperature of patient 12. Such electrodes and temperature sensors may be incorporated within the housing of IMD 14, or coupled to IMD 14 wirelessly via leads. Sensors 40 may also include a pressure sensor within, or in contact with, a blood vessel. The pressure sensor may generate a signal as a function of the a blood pressure of patient 12, and may, for example, comprise a Chronicle Hemodynamic Monitor™ commercially available from Medtronic, Inc. of Minneapolis, Minn. Further, certain muscles of patient 12, such as the muscles of the patient's neck, may discernibly relax when patient 12 is asleep or within certain sleep states. Consequently, sensors 40 may include strain gauges or EMG electrodes implanted in such locations that generate a signal as a function of muscle tone.
  • [0094]
    Sensors 40 may also include optical pulse oximetry sensors or Clark dissolved oxygen sensors located within, as part of a housing of, or outside of IMD 14, which generate signals as a function of blood oxygen saturation and blood oxygen partial pressure respectively. In some embodiments, system 10 may include a catheter with a distal portion located within the cerebrospinal fluid of patient 12, and the distal end may include a Clark dissolved oxygen sensor to generate a signal as a function of the partial pressure of oxygen within the cerebrospinal fluid. Embodiments in which an IMD comprises an implantable pump, for example, may include a catheter with a distal portion located in the cerebrospinal fluid.
  • [0095]
    In some embodiments, sensors 40 may include one or more intraluminal, extraluminal, or external flow sensors positioned to generate a signal as a function of arterial blood flow. A flow sensor may be, for example, an electromagnetic, thermal convection, ultrasonic-Doppler, or laser-Doppler flow sensor. Further, in some external medical device embodiments of the invention, sensors 40 may include one or more electrodes positioned on the skin of patient 12 to generate a signal as a function of galvanic skin response.
  • [0096]
    Additionally, in some embodiments, sensors 40 may include one or more electrodes positioned within or proximate to the brain of patient 12, which detect electrical activity of the brain. For example, in embodiments in which IMD 14 delivers stimulation or therapeutic agents to the brain, processor 46 may be coupled to electrodes implanted on or within the brain via a lead 16. In other embodiments, processor 46 may be wirelessly coupled to electrodes that detect brain electrical activity.
  • [0097]
    For example, one or more modules may be implanted beneath the scalp of the patient, each module including a housing, one or more electrodes, and circuitry to wirelessly transmit the signals detected by the one or more electrodes to IMD 14. In other embodiments, the electrodes may be applied to the patient's scalp, and electrically coupled to a module that includes circuitry for wirelessly transmitting the signals detected by the electrodes to IMD 14. The electrodes may be glued to the patient's scalp, or a head band, hair net, cap, or the like may incorporate the electrodes and the module, and may be worn by patient 12 to apply the electrodes to the patient's scalp when, for example, the patient is attempting to sleep. The signals detected by the electrodes and transmitted to IMD 14 may be electroencephalogram (EEG) signals, and processor 46 may process the EEG signals to detect when patient 12 is asleep using any of a variety of known techniques, such as techniques that identify whether a patient is asleep based on the amplitude and/or frequency of the EEG signals.
  • [0098]
    Also, the motion of the eyes of patient 12 may vary depending on whether the patient is sleeping and which sleep state the patient is in. Consequently, sensors 40 may include electrodes place proximate to the eyes of patient 12 to detect electrical activity associated with motion of the eyes, e.g., to generate an electro-oculography (EOG) signal. Such electrodes may be coupled to IMD 14 via one or more leads 16, or may be included within modules that include circuitry to wirelessly transmit detected signals to IMD 14. Wirelessly coupled modules incorporating electrodes to detect eye motion may be worn externally by patient 12, e.g., attached to the skin of patient 12 proximate to the eyes by an adhesive when the patient is attempting to sleep.
  • [0099]
    Processor 46 may also detect arousals and/or apneas that occur when patient 12 is asleep based on one or more of the above-identified physiological parameters. For example, processor 46 may detect an arousal based on an increase or sudden increase in one or more of heart rate, heart rate variability, respiration rate, respiration rate variability, blood pressure, or muscular activity as the occurrence of an arousal. Processor 46 may detect an apnea based on a disturbance in the respiration rate of patient 12, e.g., a period with no respiration.
  • [0100]
    Processor 46 may also detect arousals or apneas based on sudden changes in one or more of the ECG morphological features identified above. For example, a sudden elevation of the ST segment within the ECG may indicate an arousal or an apnea. Further, sudden changes in the amplitude or frequency of an EEG signal, EOG signal, or muscle tone signal may indicate an apnea or arousal. Memory 48 may store thresholds used by processor 46 to detect arousals and apneas. Processor 46 may determine, as a sleep quality metric value, the number of apnea events and/or arousals during a night.
  • [0101]
    Further, in some embodiments, processor 46 may determine which sleep state patient 12 is in during sleep, e.g., REM, S1, S2, S3, or S4, based on one or more of the monitored physiological parameters. In some embodiments, memory 48 may store one or more thresholds for each of sleep states, and processor 46 may compare physiological parameter or sleep probability metric values to the thresholds to determine which sleep state patient 12 is currently in. Further, in some embodiments, processor 46 may use any of a variety of known techniques for determining which sleep state patient is in based on an EEG signal, which processor 46 may receive via electrodes as described above, such as techniques that identify sleep state based on the amplitude and/or frequency of the EEG signals. In some embodiments, processor 46 may also determine which sleep state patient is in based on an EOG signal, which processor 46 may receive via electrodes as described above, either alone or in combination with an EEG signal, using any of a variety of techniques known in the art. Processor 46 may determine, as sleep quality metric values, the amounts of time per night spent in the various sleep states. As discussed above, inadequate time spent in deeper sleep states, e.g., S3 and S4, is an indicator of poor sleep quality. Consequently, in some embodiments, processor 46 may determine an amount or percentage of time spent in one or both of the S3 and S4 sleep states as a sleep quality metric.
  • [0102]
    FIG. 3 further illustrates memory 48 of IMD 14. As illustrated in FIG. 3, memory 48 stores information describing a plurality of therapy parameter sets 60. Therapy parameter sets 60 may include parameter sets specified by a clinician using clinician programmer 20. Therapy parameter sets 60 may also include parameter sets that are the result of patient 12 changing one or more parameters of one of the preprogrammed therapy parameter sets via patient programmer 26.
  • [0103]
    Memory 48 may also include parameter information 62 recorded by processor 46, e.g., physiological parameter values, or mean or median physiological parameter values. Memory 48 stores threshold values 64 used by processor 46 in the collection of sleep quality metric values, as discussed above. In some embodiments, memory 48 also stores one or more functions or look-up tables (not shown) used by processor 46 to determine sleep probability metric values, or to determine an overall sleep quality metric value.
  • [0104]
    Further, processor 46 stores determined values 66 for one or more sleep quality metrics within memory 48. Processor 46 may collect sleep quality metric values 66 each time patient 12 sleeps, or only during selected times that patient 12 is asleep. Processor 46 may store each sleep quality metric value determined within memory 48 as a sleep quality metric value 66, or may store mean or median sleep quality metric values over periods of time such as weeks or months as sleep quality metric values 66. Further, processor 46 may apply a function or look-up table to a plurality of sleep quality metric values to determine overall sleep quality metric value, and may store the overall sleep quality metric values within memory 48. The application of a function or look-up table by processor 46 for this purpose may involve the use or weighting factors for one or more of the individual sleep quality metric values.
  • [0105]
    In some embodiments, processor 46 identifies which of therapy parameter sets 60 is currently selected for use in delivering therapy to patient 12 when a value of one or more sleep quality metrics is collected, and may associate that value with the current therapy parameter set. For example, for each of the plurality of therapy parameter sets 60, processor 46 may store a representative value of each of one or more sleep quality metrics within memory 48 as a sleep quality metric value 66 with an indication of which of the therapy parameter sets that representative value is associated with. A representative value of sleep quality metric for a therapy parameter set may be the mean or median of collected sleep quality metric values that have been associated with that therapy parameter set.
  • [0106]
    As shown in FIG. 2, IMD 14 also includes a telemetry circuit 50 that allows processor 46 to communicate with clinician programmer 20 and patient programmer 26. Processor 46 may receive information identifying therapy parameter sets 60 preprogrammed by the clinician and threshold values 64 from clinician programmer 20 via telemetry circuit 50 for storage in memory 48. Processor 46 may receive an indication of the therapy parameter set 60 selected by patient 12 for delivery of therapy, or adjustments to one or more of therapy parameter sets 60 made by patient 12, from patient programmer 26 via telemetry circuit 50. Programmers 20, 26 may receive sleep quality metric values 66 from processor 46 via telemetry circuit 50.
  • [0107]
    FIG. 4 is a flow diagram illustrating an example method for collecting sleep quality information that may be employed by IMD 14. IMD 14 monitors the posture, activity level, and/or melatonin level of patient 12, or monitors for an indication from patient 12, e.g., via patient programmer 26 (70), and determines whether patient 12 is attempting to fall asleep based on the posture, activity level, melatonin level, and/or a patient indication, as described above (72). If IMD 14 determines that patient 12 is attempting to fall asleep, IMD 14 identifies the time that patient 12 began attempting to fall asleep using any of the techniques described above (74), and monitors one or more of the various physiological parameters of patient 12 discussed above to determine whether patient 12 is asleep (76, 78).
  • [0108]
    In some embodiments, IMD 14 compares parameter values or parameter variability values to one or more threshold values 64 to determine whether patient 12 is asleep. In other embodiments, IMD 14 applies one or more functions or look-up tables to determine one or more sleep probability metric values based on the physiological parameter values, and compares the sleep probability metric values to one or more threshold values 64 to determine whether patient 12 is asleep. While monitoring physiological parameters (76) to determine whether patient 12 is asleep (78), IMD 14 may continue to monitor the posture and/or activity level of patient 12 (70) to confirm that patient 12 is still attempting to fall asleep (72).
  • [0109]
    When IMD 14 determines that patient 12 is asleep, e.g., by analysis of the various parameters contemplated herein, IMD 14 will identify the time that patient 12 fell asleep (80). While patient 12 is sleeping, IMD 14 will continue to monitor physiological parameters of patient 12 (82). As discussed above, IMD 14 may identify the occurrence of arousals and/or apneas based on the monitored physiological parameters (84). Further, IMD 14 may identify the time that transitions between sleep states, e.g., REM, S1, S2, S3, and S4, occur based on the monitored physiological parameters (84).
  • [0110]
    Additionally, while patient 12 is sleeping, IMD 14 monitors physiological parameters of patient 12 (82) to determine whether patient 12 has woken up (86). When IMD 14 determines that patient 12 is awake, IMD 14 identifies the time that patient 12 awoke (88), and determines sleep quality metric values based on the information collected while patient 12 was asleep (90).
  • [0111]
    For example, one sleep quality metric value IMD 14 may calculate is sleep efficiency, which IMD 14 may calculate as a percentage of time during which patient 12 is attempting to sleep that patient 12 is actually asleep. IMD 14 may determine a first amount of time between the time IMD 14 identified that patient 12 fell asleep and the time IMD 14 identified that patient 12 awoke. IMD 14 may also determine a second amount of time between the time IMD 14 identified that patient 12 began attempting to fall asleep and the time IMD 14 identified that patient 12 awoke. To calculate the sleep efficiency, IMD 14 may divide the first time by the second time.
  • [0112]
    Another sleep quality metric value that IMD 14 may calculate is sleep latency, which IMD 14 may calculate as the amount of time between the time IMD 14 identified that patient 12 was attempting to fall asleep and the time IMD 14 identified that patient 12 fell asleep. Other sleep quality metrics with values determined by IMD 14 based on the information collected by IMD 14 in the illustrated example include: total time sleeping per day, at night, and during daytime hours; number of apnea and arousal events per occurrence of sleep; and amount of time spent in the various sleep states, e.g., one or both of the S3 and S4 sleep states. IMD 14 may store the determined values as sleep quality metric values 66 within memory 48.
  • [0113]
    IMD 14 may perform the example method illustrated in FIG. 4 continuously, e.g., may monitor to identify when patient 12 is attempting to sleep and asleep any time of day, each day. In other embodiments, IMD 14 may only perform the method during evening hours and/or once every N days to conserve battery and memory resources. Further, in some embodiments, IMD 14 may only perform the method in response to receiving a command from patient 12 or a clinician via one of programmers 20, 26. For example, patient 12 may direct IMD 14 to collect sleep quality information at times when the patient believes that his or her sleep quality is low or therapy is ineffective.
  • [0114]
    FIG. 5 is a flow diagram illustrating an example method for associating sleep quality information with therapy parameter sets 60 that may be employed by IMD 14. IMD 14 determines a value of a sleep quality metric according to any of the techniques described above (100). IMD 14 also identifies the current therapy parameter set, e.g., the therapy parameter set 60 used by IMD 14 to control delivery of therapy when patient 12 was asleep (102), and associates the newly determined value with the current therapy parameter set 60.
  • [0115]
    Among sleep quality metric values 66 within memory 48, IMD 14 stores a representative value of the sleep quality metric, e.g., a mean or median value, for each of the plurality of therapy parameter sets 60. IMD 14 updates the representative values for the current therapy parameter set based on the newly determined value of the sleep quality metric. For example, a newly determined sleep efficiency value may be used to determine a new average sleep efficiency value for the current therapy parameter set 60.
  • [0116]
    FIG. 6 is a block diagram further illustrating clinician programmer 20. A clinician may interact with a processor 110 via a user interface 112 in order to program therapy for patient 12. Further, processor 110 may receive sleep quality metric values 66 from IMD 14 via a telemetry circuit 114, and may generate sleep quality information for presentation to the clinician via user interface 112. User interface 112 may include display 22 and keypad 24, and may also include a touch screen or peripheral pointing devices as described above. Processor 110 may include a microprocessor, a controller, a DSP, an ASIC, an FPGA, discrete logic circuitry, or the like.
  • [0117]
    Clinician programmer 20 also includes a memory 116. Memory 116 may include program instructions that, when executed by processor 110, cause clinician programmer 20 to perform the functions ascribed to clinician programmer 20 herein. Memory 116 may include any volatile, non-volatile, fixed, removable, magnetic, optical, or electrical media, such as a RAM, ROM, CD-ROM, hard disk, removable magnetic disk, memory cards or sticks, NVRAM, EEPROM, flash memory, and the like.
  • [0118]
    FIG. 7 is a flow diagram illustrating an example method for presenting sleep quality information to a clinician that may be employed by clinician programmer 20. Clinician programmer 20 receives sleep quality metric values 66 from IMD 14, e.g., via telemetry circuit 114 (120). The sleep quality metric values 66 may be daily values, or mean or median values determined over greater periods of time, e.g., weeks or months.
  • [0119]
    Clinician programmer 20 may simply present the values to the clinician via display 22 in any form, such as a table of average values, or clinician programmer 20 may generate a graphical representation of the sleep quality metric values (122). For example, clinician programmer 20 may generate a trend diagram illustrating sleep quality metric values 66 over time, or a histogram, pie chart, or other graphic illustration of percentages of sleep quality metric values 66 collected by IMD 14 that were within ranges. Where clinician programmer 20 generates a graphical representation of the sleep quality metric values 66, clinician programmer 20 presents the graphical representation to the clinician via display 22 (124).
  • [0120]
    FIG. 8 illustrates an example list 130 of therapy parameter sets and associated sleep quality metric values that may be presented to a clinician by clinician programmer 20. Each row of example list 130 includes an identification of one of therapy parameter sets 60, the parameters of the set, and a representative value for one or more sleep quality metrics associated with the identified therapy parameter set, such as sleep efficiency, sleep latency, or both. The example list 130 includes representative values for sleep efficiency, sleep latency, and “deep sleep,” e.g., the average amount of time per night spent in either of the S3 and S4 sleep states.
  • [0121]
    FIG. 9 is a flow diagram illustrating an example method for displaying a list 130 of therapy parameter sets and associated sleep quality information that may be employed by clinician programmer 20. According to the example method, clinician programmer 20 receives information identifying the plurality of therapy parameter sets 60 stored in memory 48 of IMD 14, and one or more representative sleep quality metric values associated with each of the therapy parameter sets (140). Clinician programmer 20 generates a list 130 of the therapy parameter sets 60 and any associated representative sleep quality metric values (142), and orders the list according to a selected sleep quality metric (144). For example, in the example list 130 illustrated in FIG. 8, the clinician may select whether list 130 should be ordered according to sleep efficiency or sleep latency via user interface 112 of clinician programmer 20.
  • [0122]
    FIG. 10 is a block diagram further illustrating patient programmer 26. Patient 12 may interact with a processor 150 via a user interface 152 in order to control delivery of therapy, i.e., select or adjust one or more of therapy parameter sets 60 stored by IMD 14. Processor 150 may also receive sleep quality metric values 66 from IMD 14 via a telemetry circuit 154, and may provide messages related to sleep quality to patient 12 via user interface 152 based on the received values. User interface 152 may include display 28 and keypad 30, and may also include a touch screen or peripheral pointing devices as described above.
  • [0123]
    In some embodiments, processor 150 may determine whether to provide a message related to sleep quality to patient 12 based on the received sleep quality metric values. For example, processor 150 may periodically receive sleep quality metric values 66 from IMD 14 when placed in telecommunicative communication with IMD 14 by patient 12, e.g., for therapy selection or adjustment. Processor 150 may compare these values to one or more thresholds 156 stored in a memory 158 to determine whether the quality of the patient's sleep is poor enough to warrant a message.
  • [0124]
    Processor 150 may present messages to patient 12 as text via display, and/or as audio via speakers included as part of user interface 152. The message may, for example, direct patient 12 to see a physician, increase therapy intensity before sleeping, or select a different therapy parameter set before sleeping than the patient had typically selected previously. In some embodiments, the message may indicate the quality of sleep to patient 12 to, for example, provide patient 12 with an objective indication of whether his or her sleep quality is good, adequate, or poor. Further, in some embodiments processor 150 may, like clinician programmer 20, receive representative sleep quality metric values. In such embodiments, processor 150 may identify a particular one or more of therapy parameter sets 60 to recommend to patient 12 based on representative sleep quality metric values associated with those programs.
  • [0125]
    Processor 150 may include a microprocessor, a controller, a DSP, an ASIC, an FPGA, discrete logic circuitry, or the like. Memory 158 may also include program instructions that, when executed by processor 150, cause patient programmer 26 to perform the functions ascribed to patient programmer 26 herein. Memory 158 may include any volatile, non-volatile, fixed, removable, magnetic, optical, or electrical media, such as a RAM, ROM, CD-ROM, hard disk, removable magnetic disk, memory cards or sticks, NVRAM, EEPROM, flash memory, and the like.
  • [0126]
    FIG. 11 is a flow diagram illustrating an example method for presenting a sleep quality message to patient 12 that may be employed by patient programmer 26. According to the illustrated example method, patient programmer 26 receives a sleep quality metric value from IMD 14 (160), and compares the value to a threshold value 156 (162). Patient programmer 26 determines whether the comparison indicates poor sleep quality (164). If the comparison indicates that the quality of sleep experienced by patient 12 is poor, patient programmer 26 presents a message related to sleep quality to patient 12 (166).
  • [0127]
    Various embodiments of the invention have been described. However, one skilled in the art will recognize that various modifications may be made to the described embodiments without departing from the scope of the invention. For example, although described herein primarily in the context of treatment of pain with an implantable neurostimulator, the invention is not so limited. The invention may be embodied in any implantable medical device, such as a cardiac pacemaker, an implantable pump, or an implantable monitor that does not itself deliver a therapy to the patient. Further, the invention may be implemented via an external, e.g., non-implantable, medical device.
  • [0128]
    Additionally, the invention is not limited to embodiments in which a programming device receives information from the medical device, or presents information to a user. Other computing devices, such as handheld computers, desktop computers, workstations, or servers. May receive information from the medical device and present information to a user as described herein with reference to programmers 20, 26. A computing device, such as a server, may receive information from the medical device and present information to a user via a network, such as a local area network (LAN), wide area network (WAN), or the Internet. In some embodiments, the medical device is an external medical device, and may itself include a display to present information to a user.
  • [0129]
    As another example, the invention may be embodied in a trial neurostimulator, which is coupled to percutaneous leads implanted within the patient to determine whether the patient is a candidate for neurostimulation, and to evaluate prospective neurostimulation therapy parameter sets. Similarly, the invention may be embodied in a trial drug pump, which is coupled to a percutaneous catheter implanted within the patient to determine whether the patient is a candidate for an implantable pump, and to evaluate prospective therapeutic agent delivery parameter sets. Sleep quality metric values collected by the trial neurostimulator or pump may be used by a clinician to evaluate the prospective therapy parameter sets, and select parameter sets for use by the later implanted non-trial neurostimulator or pump. In particular, a trial neurostimulator or pump may determine representative values of one or more sleep quality metrics for each of a plurality of prospective therapy parameter sets, and a computing device, such as a clinician programmer, may present a list of prospective parameter sets and associated representative values to a clinician. The clinician may use the list to identify potentially efficacious parameter sets, and may program a permanent implantable neurostimulator or pump for the patient with the identified parameter sets.
  • [0130]
    Further, the invention is not limited to embodiments in which an implantable or external medical device that delivers therapy to a patient determines sleep quality metric values. Instead a medical device according to the invention may record values for one or more physiological parameters, and provide the physiological parameter values to a computing device, such as one or both of programmers 20, 26. In such embodiments, the computing device, and more particularly a processor of the computing device, e.g., processors 110, 150, employs any of the techniques described herein with reference to IMD 14 in order to determine sleep quality metric values based on the physiological parameter values received from the medical device. The computing device may receive physiological parameter values from the medical device in real time, or may monitor physiological parameters of the patient by receiving and analyzing physiological parameter values recorded by the medical device over a period of time. In some embodiments, in addition to physiological parameter values, the medical device provides the computing device information identifying times at which the patient indicated that he or she was attempting to fall asleep, which the computing device may use to determine one or more sleep quality metric values as described herein.
  • [0131]
    In some embodiments, the medical device may associate recorded physiological parameter values with current therapy parameter sets. The medical device may provide information indicating the associations of recorded physiological parameter values and therapy parameter sets to the computing device, e.g., programmer 20 or 26. The computing device may determine sleep quality metric values and representative sleep quality metric values for each of the plurality of therapy parameter sets based on the physiological parameter values associated with the therapy parameter sets, as described herein with reference to IMD 14.
  • [0132]
    Additionally, the invention is not limited to embodiments in which the therapy delivering medical device monitors the physiological parameters of the patient described herein. In some embodiments, a separate monitoring device monitors values of one or more physiological parameters of the patient instead of, or in addition to, a therapy delivering medical device. The monitor may include a processor 46 and memory 48, and may be coupled to sensors 40, as illustrated above with reference to IMD 14 and FIGS. 2 and 3. The monitor may identify sleep quality metric values based on the values of the monitored physiological parameter values, or may transmit the physiological parameter values to a computing device for determination of the sleep quality metric values. In some embodiments, an external computing device, such as a programming device, may incorporate the monitor.
  • [0133]
    FIG. 12 is a conceptual diagram illustrating a monitor 170 that monitors values of one or more physiological parameters of the patient instead of, or in addition to, a therapy delivering medical device. In the illustrated example, monitor 170 is configured to be attached to or otherwise carried by a belt 172, and may thereby be worn by patient 12. FIG. 12 also illustrates various sensors 40 that may be coupled to monitor 170 by leads, wires, cables, or wireless connections, such as EEG electrodes 174A-C placed on the scalp of patient 12, a plurality of EOG electrodes 176A and 176B placed proximate to the eyes of patient 12, and one or more EMG electrodes 178 placed on the chin or jaw the patient. The number and positions of electrodes 174, 176 and 178 illustrated in FIG. 12 are merely exemplary. For example, although only three EEG electrodes 174 are illustrated in FIG. 1, an array of between 16 and 25 EEG electrodes 174 may be placed on the scalp of patient 12, as is known in the art. EEG electrodes 174 may be individually placed on patient 12, or integrated within a cap or hair net worn by the patient.
  • [0134]
    In the illustrated example, patient 12 wears an ECG belt 180. ECG belt 180 incorporates a plurality of electrodes for sensing the electrical activity of the heart of patient 12. The heart rate and, in some embodiments, ECG morphology of patient 12 may monitored by monitor 170 based on the signal provided by ECG belt 180. Examples of suitable belts 180 for sensing the heart rate of patient 12 are the “M” and “F” heart rate monitor models commercially available from Polar Electro. In some embodiments, instead of belt 180, patient 12 may wear of plurality of ECG electrodes attached, e.g., via adhesive patches, at various locations on the chest of the patient, as is known in the art. An ECG signal derived from the signals sensed by such an array of electrodes may enable both heart rate and ECG morphology monitoring, as is known in the art.
  • [0135]
    As shown in FIG. 12, patient 12 may also wear a respiration belt 182 that outputs a signal that varies as a function of respiration of the patient. Respiration belt 182 may be a plethysmograpy belt, and the signal output by respiration belt 182 may vary as a function of the changes is the thoracic or abdominal circumference of patient 12 that accompany breathing by the patient. An example of a suitable belt 182 is the TSD201 Respiratory Effort Transducer commercially available from Biopac Systems, Inc. Alternatively, respiration belt 182 may incorporate or be replaced by a plurality of electrodes that direct an electrical signal through the thorax of the patient, and circuitry to sense the impedance of the thorax, which varies as a function of respiration of the patient, based on the signal. In some embodiments, ECG and respiration belts 180 and 182 may be a common belt worn by patient 12, and the relative locations of belts 180 and 182 depicted in FIG. 12 are merely exemplary.
  • [0136]
    In the example illustrated by FIG. 12, patient 12 also wears a transducer 184 that outputs a signal as a function of the oxygen saturation of the blood of patient 12. Transducer 184 may be an infrared transducer. Transducer 184 may be located on one of the fingers or earlobes of patient 12. Sensors 40 coupled to monitor 170 may additionally or alternatively include any of the variety of sensors described above that monitor any one or more of activity level, posture, heart rate, ECG morphology, respiration rate, respiratory volume, blood pressure, blood oxygen saturation, partial pressure of oxygen within blood, partial pressure of oxygen within cerebrospinal fluid, muscular activity and tone, core temperature, subcutaneous temperature, arterial blood flow, brain electrical activity, eye motion, and galvanic skin response.
  • [0137]
    The invention may also be embodied as a computer-readable medium that includes instructions to cause a processor to perform any of the methods described herein. These and other embodiments are within the scope of the following claims.

Claims (18)

1. A method comprising:
monitoring at least one physiological parameter of a patient;
determining a value of a metric that is indicative of sleep quality based on the at least one physiological parameter;
identifying a current therapy parameter used by a medical device to deliver a therapy to a patient; and
associating the sleep quality metric value with the current therapy parameter set.
2. The method of claim 1, wherein monitoring at least one physiological parameter comprises monitoring at least one of electrocardiogram morphology, subcutaneous temperature, muscular tone, electrical activity of a brain of the patient or eye motion.
3. A medical system comprising:
a medical device that delivers a therapy to a patient;
a monitor that monitors at least one physiological parameter of the patient based on a signal received from at least one sensor; and
a processor that determines a value of a metric that is indicative of sleep quality based on the at least one physiological parameter, identifies a current therapy parameter set used by the medical device to deliver the therapy to the patient, and associates the sleep quality metric value with the current therapy parameter set.
4. The medical system of claim 3, wherein the monitor monitors at least one of electrocardiogram morphology, subcutaneous temperature, muscular tone, electrical activity within a brain of the patient or eye motion.
5. The medical system of claim 3, further comprising a computing device to present sleep quality information to a user based on the sleep quality metric values determined by the processor.
6. The medical system of claim 5, wherein the user comprises a clinician, and the computing device comprises a clinician programmer that presents at least one of a trend diagram, a histogram or a pie chart to the clinician based on the sleep quality metric values.
7. The medical system of claim 5, wherein the user comprises a patient, and the computing device comprises a patient programmer that presents a message related to sleep quality to the patient based on the sleep quality metric values.
8. The medical system of claim 3,
wherein the processor determines a plurality of values of the sleep quality metric over time, and associates each of the determined values of the sleep quality metric with a current therapy parameter set, and
wherein, for each of a plurality of therapy parameter sets, the processor determines a representative value of the sleep quality metric based on the values of the sleep quality metric associated with the therapy parameter set,
the system further comprising a computing device that presents a list of the therapy parameter sets and the associated representative values to a user, and orders the list of therapy parameter sets according to the associated representative values.
9. The medical system of claim 3,
wherein the processor determines a plurality of values over time for each of a plurality of metrics that are indicative of sleep quality, and associates each of the determined values with a current therapy parameter set, and
wherein, for each of the plurality of therapy parameter sets, the processor determines a representative value for each of the sleep quality metrics based on the values of that sleep quality metric associated with the therapy parameter set,
the system further comprising a computing device that presents a list of the therapy parameter sets and the associated representative values to a user, and orders the list of therapy parameter sets according to the representative values of a user-selected one of the sleep quality metrics.
10. The medical system of claim 3, wherein the processor comprises a processor of at least one of the medical device and the monitor.
11. The medical system of claim 3, further comprising a computing device, wherein the processor comprises a processor of the computing device.
12. The medical system of claim 3, wherein the medical device comprises the monitor.
13. A method comprising:
monitoring a plurality of signals, each of the signals generated by a sensor as a function of at least one physiological parameter of a patient;
identifying when the patient is attempting to sleep;
identifying when the patient is asleep based on at least one of the signals; and
determining a value of a metric that is indicative of sleep quality based on the identifications of when the patient is attempting to sleep and asleep,
wherein identifying when the patient is asleep comprises identifying when the patient is asleep based on at least one of electrocardiogram morphology, subcutaneous temperature, muscular tone, electrical activity within a brain of the patient or eye motion.
14. A medical system comprising:
a plurality of sensors, each of the sensors generating a signal as a function of at least one physiological parameter of a patient; and
a processor that monitors the signals generated by the sensors, identifies when the patient is attempting to sleep, identifies when the patient is asleep based on at least one of the signals, and determines a value of a metric that is indicative of sleep quality based on the identifications of when the patient is attempting to sleep and asleep, wherein the processor identifies when the patient is asleep based on at least one of electrocardiogram morphology, subcutaneous temperature, muscular tone, electrical activity within a brain of the patient or eye motion.
15. A medical system comprising:
a plurality of sensors, each of the sensors generating a signal as a function of at least one physiological parameter of a patient;
a computing device that monitors the signals generated by the sensors, identifies when the patient is attempting to sleep, identifies when the patient is asleep based on at least one of the signals, and determines a value of a metric that is indicative of sleep quality based on the identifications of when the patient is attempting to sleep and asleep.
16. The medical system of claim 15, wherein the computing device comprises a programming device.
17. The medical system of claim 15, wherein the computing device receives the signals generated by the sensors via a network.
18. The medical system of claim 17, wherein the computing device comprises a server.
US11081811 2004-03-16 2005-03-16 Collecting sleep quality information via a medical device Abandoned US20050215847A1 (en)

Priority Applications (3)

Application Number Priority Date Filing Date Title
US55378304 true 2004-03-16 2004-03-16
US10826925 US7717848B2 (en) 2004-03-16 2004-04-15 Collecting sleep quality information via a medical device
US11081811 US20050215847A1 (en) 2004-03-16 2005-03-16 Collecting sleep quality information via a medical device

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US11081811 US20050215847A1 (en) 2004-03-16 2005-03-16 Collecting sleep quality information via a medical device
US11591286 US8725244B2 (en) 2004-03-16 2006-10-31 Determination of sleep quality for neurological disorders
US11691376 US20070276439A1 (en) 2004-03-16 2007-03-26 Collecting sleep quality information via a medical device
US14247923 US20140222101A1 (en) 2004-03-16 2014-04-08 Determination of sleep quality for neurological disorders
US15160455 US20160263382A1 (en) 2004-03-16 2016-05-20 Collecting sleep quality information via a medical device

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
US10826925 Continuation-In-Part US7717848B2 (en) 2004-03-16 2004-04-15 Collecting sleep quality information via a medical device

Related Child Applications (3)

Application Number Title Priority Date Filing Date
US11591286 Continuation-In-Part US8725244B2 (en) 2004-03-16 2006-10-31 Determination of sleep quality for neurological disorders
US11691376 Continuation-In-Part US20070276439A1 (en) 2004-03-16 2007-03-26 Collecting sleep quality information via a medical device
US15160455 Continuation US20160263382A1 (en) 2004-03-16 2016-05-20 Collecting sleep quality information via a medical device

Publications (1)

Publication Number Publication Date
US20050215847A1 true true US20050215847A1 (en) 2005-09-29

Family

ID=34962791

Family Applications (6)

Application Number Title Priority Date Filing Date
US10826925 Active 2028-08-17 US7717848B2 (en) 2004-03-16 2004-04-15 Collecting sleep quality information via a medical device
US11081811 Abandoned US20050215847A1 (en) 2004-03-16 2005-03-16 Collecting sleep quality information via a medical device
US12723501 Active 2026-06-23 US8758242B2 (en) 2004-03-16 2010-03-12 Collecting sleep quality information via a medical device
US14276516 Active US9205264B2 (en) 2004-03-16 2014-05-13 Collecting sleep quality information via a medical device
US14961344 Active US9623248B2 (en) 2004-03-16 2015-12-07 Collecting sleep quality information via a medical device
US15160455 Pending US20160263382A1 (en) 2004-03-16 2016-05-20 Collecting sleep quality information via a medical device

Family Applications Before (1)

Application Number Title Priority Date Filing Date
US10826925 Active 2028-08-17 US7717848B2 (en) 2004-03-16 2004-04-15 Collecting sleep quality information via a medical device

Family Applications After (4)

Application Number Title Priority Date Filing Date
US12723501 Active 2026-06-23 US8758242B2 (en) 2004-03-16 2010-03-12 Collecting sleep quality information via a medical device
US14276516 Active US9205264B2 (en) 2004-03-16 2014-05-13 Collecting sleep quality information via a medical device
US14961344 Active US9623248B2 (en) 2004-03-16 2015-12-07 Collecting sleep quality information via a medical device
US15160455 Pending US20160263382A1 (en) 2004-03-16 2016-05-20 Collecting sleep quality information via a medical device

Country Status (2)

Country Link
US (6) US7717848B2 (en)
WO (1) WO2005089649A1 (en)

Cited By (53)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050209643A1 (en) * 2004-03-16 2005-09-22 Heruth Kenneth T Controlling therapy based on sleep quality
US20050209512A1 (en) * 2004-03-16 2005-09-22 Heruth Kenneth T Detecting sleep
US20050209644A1 (en) * 2004-03-16 2005-09-22 Heruth Kenneth T Collecting activity information to evaluate therapy
US20050209645A1 (en) * 2004-03-16 2005-09-22 Heruth Kenneth T Collecting posture information to evaluate therapy
US20050209513A1 (en) * 2004-03-16 2005-09-22 Heruth Kenneth T Collecting sleep quality information via a medical device
US20050209511A1 (en) * 2004-03-16 2005-09-22 Heruth Kenneth T Collecting activity and sleep quality information via a medical device
US20050216064A1 (en) * 2004-03-16 2005-09-29 Heruth Kenneth T Sensitivity analysis for selecting therapy parameter sets
US20050245988A1 (en) * 2004-04-14 2005-11-03 Medtronic, Inc. Collecting posture and activity information to evaluate therapy
US20070015976A1 (en) * 2005-06-01 2007-01-18 Medtronic, Inc. Correlating a non-polysomnographic physiological parameter set with sleep states
US20070123758A1 (en) * 2004-03-16 2007-05-31 Medtronic, Inc. Determination of sleep quality for neurological disorders
US20070129769A1 (en) * 2005-12-02 2007-06-07 Medtronic, Inc. Wearable ambulatory data recorder
US20070250134A1 (en) * 2006-03-24 2007-10-25 Medtronic, Inc. Collecting gait information for evaluation and control of therapy
US20070276439A1 (en) * 2004-03-16 2007-11-29 Medtronic, Inc. Collecting sleep quality information via a medical device
US20080071326A1 (en) * 2004-03-16 2008-03-20 Medtronic, Inc. Detecting sleep to evaluate therapy
US20080071150A1 (en) * 2004-03-16 2008-03-20 Medtronic, Inc. Collecting activity and sleep quality information via a medical device
US20080195166A1 (en) * 2007-02-09 2008-08-14 Felice Sun Devices and methods for monitoring physiological information relating to sleep with an implantable device
US20090082639A1 (en) * 2007-09-25 2009-03-26 Pittman Stephen D Automated Sleep Phenotyping
US20090156908A1 (en) * 2007-12-14 2009-06-18 Transoma Medical, Inc. Deriving Patient Activity Information from Sensed Body Electrical Information
US7792583B2 (en) 2004-03-16 2010-09-07 Medtronic, Inc. Collecting posture information to evaluate therapy
US7805196B2 (en) 2004-03-16 2010-09-28 Medtronic, Inc. Collecting activity information to evaluate therapy
US7809420B2 (en) 2003-06-25 2010-10-05 Nellcor Puritan Bennett Llc Hat-based oximeter sensor
US7822453B2 (en) 2002-10-01 2010-10-26 Nellcor Puritan Bennett Llc Forehead sensor placement
US7881798B2 (en) 2004-03-16 2011-02-01 Medtronic Inc. Controlling therapy based on sleep quality
US20110257466A1 (en) * 2008-12-19 2011-10-20 Koninklijke Philips Electronics N.V. System and method for increasing the of relaxation of a person
US8135473B2 (en) 2004-04-14 2012-03-13 Medtronic, Inc. Collecting posture and activity information to evaluate therapy
US8150531B2 (en) 2008-07-11 2012-04-03 Medtronic, Inc. Associating therapy adjustments with patient posture states
US8175720B2 (en) 2009-04-30 2012-05-08 Medtronic, Inc. Posture-responsive therapy control based on patient input
US8209028B2 (en) 2008-07-11 2012-06-26 Medtronic, Inc. Objectification of posture state-responsive therapy based on patient therapy adjustments
US8219206B2 (en) 2008-07-11 2012-07-10 Medtronic, Inc. Dwell time adjustments for posture state-responsive therapy
US8231555B2 (en) 2009-04-30 2012-07-31 Medtronic, Inc. Therapy system including multiple posture sensors
US8257274B2 (en) 2008-09-25 2012-09-04 Nellcor Puritan Bennett Llc Medical sensor and technique for using the same
US8280517B2 (en) 2008-09-19 2012-10-02 Medtronic, Inc. Automatic validation techniques for validating operation of medical devices
US8332041B2 (en) 2008-07-11 2012-12-11 Medtronic, Inc. Patient interaction with posture-responsive therapy
US8364220B2 (en) 2008-09-25 2013-01-29 Covidien Lp Medical sensor and technique for using the same
US8388555B2 (en) 2010-01-08 2013-03-05 Medtronic, Inc. Posture state classification for a medical device
US8396565B2 (en) 2003-09-15 2013-03-12 Medtronic, Inc. Automatic therapy adjustments
US8401666B2 (en) 2008-07-11 2013-03-19 Medtronic, Inc. Modification profiles for posture-responsive therapy
US8412297B2 (en) 2003-10-01 2013-04-02 Covidien Lp Forehead sensor placement
US8437861B2 (en) 2008-07-11 2013-05-07 Medtronic, Inc. Posture state redefinition based on posture data and therapy adjustments
US8504150B2 (en) 2008-07-11 2013-08-06 Medtronic, Inc. Associating therapy adjustments with posture states using a stability timer
US8515515B2 (en) 2009-03-25 2013-08-20 Covidien Lp Medical sensor with compressible light barrier and technique for using the same
US8579834B2 (en) 2010-01-08 2013-11-12 Medtronic, Inc. Display of detected patient posture state
US8708934B2 (en) 2008-07-11 2014-04-29 Medtronic, Inc. Reorientation of patient posture states for posture-responsive therapy
US8781548B2 (en) 2009-03-31 2014-07-15 Covidien Lp Medical sensor with flexible components and technique for using the same
US20150038804A1 (en) * 2013-07-30 2015-02-05 Magdy Younes Method, non-transitory computer readable medium and apparatus for arousal intensity scoring
US20150112155A1 (en) * 2013-10-23 2015-04-23 Quanttus, Inc. Sleep parameters
US9050471B2 (en) 2008-07-11 2015-06-09 Medtronic, Inc. Posture state display on medical device user interface
US20150196766A1 (en) * 2014-01-15 2015-07-16 Pacesetter, Inc. Wireless closed-loop and system to detect and treat sleep apnea
US9327070B2 (en) 2009-04-30 2016-05-03 Medtronic, Inc. Medical device therapy based on posture and timing
US9333351B2 (en) 2013-12-16 2016-05-10 Pacesetter, Inc. Neurostimulation method and system to treat apnea
US9357949B2 (en) 2010-01-08 2016-06-07 Medtronic, Inc. User interface that displays medical therapy and posture data
US9566441B2 (en) 2010-04-30 2017-02-14 Medtronic, Inc. Detecting posture sensor signal shift or drift in medical devices
US9737719B2 (en) 2012-04-26 2017-08-22 Medtronic, Inc. Adjustment of therapy based on acceleration

Families Citing this family (73)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7225013B2 (en) * 2003-05-15 2007-05-29 Widemed Ltd. Adaptive prediction of changes of physiological/pathological states using processing of biomedical signals
US7896812B2 (en) * 2003-08-14 2011-03-01 New York University System and method for diagnosis and treatment of a breathing pattern of a patient
US9033920B2 (en) 2003-10-02 2015-05-19 Medtronic, Inc. Determining catheter status
US7320676B2 (en) * 2003-10-02 2008-01-22 Medtronic, Inc. Pressure sensing in implantable medical devices
US9138537B2 (en) * 2003-10-02 2015-09-22 Medtronic, Inc. Determining catheter status
US20060253100A1 (en) 2004-10-22 2006-11-09 Medtronic, Inc. Systems and Methods to Treat Pain Locally
US20060074453A1 (en) * 2004-10-04 2006-04-06 Cvrx, Inc. Baroreflex activation and cardiac resychronization for heart failure treatment
US7644714B2 (en) 2005-05-27 2010-01-12 Apnex Medical, Inc. Devices and methods for treating sleep disorders
US7957809B2 (en) * 2005-12-02 2011-06-07 Medtronic, Inc. Closed-loop therapy adjustment
WO2007123764A3 (en) * 2006-04-06 2008-01-31 Medtronic Inc Systems and methods of identifying catheter malfunctions using pressure sensing
US8617068B2 (en) * 2006-09-27 2013-12-31 ResMed Limitied Method and apparatus for assessing sleep quality
US7809442B2 (en) 2006-10-13 2010-10-05 Apnex Medical, Inc. Obstructive sleep apnea treatment devices, systems and methods
US9186511B2 (en) 2006-10-13 2015-11-17 Cyberonics, Inc. Obstructive sleep apnea treatment devices, systems and methods
US8333696B2 (en) * 2006-12-13 2012-12-18 Watermark Medical, Inc. Systems and methods for automated prediction of risk for perioperative complications based on the level of obstructive sleep apnea
US9044537B2 (en) 2007-03-30 2015-06-02 Medtronic, Inc. Devices and methods for detecting catheter complications
US8323244B2 (en) * 2007-03-30 2012-12-04 Medtronic, Inc. Catheter malfunction determinations using physiologic pressure
US7996076B2 (en) * 2007-04-02 2011-08-09 The Regents Of The University Of Michigan Automated polysomnographic assessment for rapid eye movement sleep behavior disorder
US8805508B2 (en) * 2007-05-30 2014-08-12 Medtronic, Inc. Collecting activity data for evaluation of patient incontinence
US8204597B2 (en) * 2007-05-30 2012-06-19 Medtronic, Inc. Evaluating patient incontinence
US8170609B2 (en) * 2007-06-20 2012-05-01 Qualcomm Incorporated Personal virtual assistant providing advice to a user regarding physiological information received about the user
US8630704B2 (en) 2007-06-25 2014-01-14 Cardiac Pacemakers, Inc. Neural stimulation with respiratory rhythm management
US20090264967A1 (en) * 2008-04-18 2009-10-22 Medtronic, Inc. Timing therapy evaluation trials
WO2009129480A3 (en) * 2008-04-18 2010-03-25 Medtronic, Inc. Psychiatric disorder therapy control
WO2009129493A1 (en) * 2008-04-18 2009-10-22 Medtronic, Inc. Analyzing a washout period characteristic for psychiatric disorder therapy delivery
CA2724335A1 (en) * 2008-05-15 2009-11-19 Inspire Medical Systems, Inc. Method and apparatus for sensing respiratory pressure in an implantable stimulation system
US8788042B2 (en) 2008-07-30 2014-07-22 Ecole Polytechnique Federale De Lausanne (Epfl) Apparatus and method for optimized stimulation of a neurological target
CA2743575C (en) 2008-11-12 2017-01-31 Ecole Polytechnique Federale De Lausanne Microfabricated neurostimulation device
JP5575789B2 (en) 2008-11-19 2014-08-20 インスパイア・メディカル・システムズ・インコーポレイテッドInspire Medical Systems, Inc. A method of treatment of sleep-disordered breathing
US9744354B2 (en) 2008-12-31 2017-08-29 Cyberonics, Inc. Obstructive sleep apnea treatment devices, systems and methods
US8355769B2 (en) 2009-03-17 2013-01-15 Advanced Brain Monitoring, Inc. System for the assessment of sleep quality in adults and children
US20100249624A1 (en) * 2009-03-27 2010-09-30 Platinum Team Co., Ltd. Device for analyzing quality of sleep
EP2416845B1 (en) 2009-03-31 2015-03-18 Inspire Medical Systems, Inc. Percutaneous access for systems of treating sleep-related disordered breathing
WO2010141893A3 (en) 2009-06-05 2011-04-21 Advanced Brain Monitoring, Inc. Systems and methods for controlling position
JP5798553B2 (en) * 2009-07-16 2015-10-21 レスメド・リミテッドResMedLimited Detection of sleep state
GB0912465D0 (en) 2009-07-17 2009-08-26 Sharp Kk System and method for improving sleep quality in children
GB0912462D0 (en) * 2009-07-17 2009-08-26 Sharp Kk System and method for improving sleep quality
WO2011067297A9 (en) 2009-12-01 2012-04-05 ECOLE POLYTECHNIQUE FéDéRALE DE LAUSANNE Microfabricated surface neurostimulation device and methods of making and using the same
EP2545475A1 (en) * 2010-03-08 2013-01-16 Koninklijke Philips Electronics N.V. System and method for obtaining an objective measure of dyspnea
JP5927176B2 (en) 2010-04-01 2016-06-01 エコーレ ポリテクニーク フェデラーレ デ ローザンヌ (イーピーエフエル) Device for interacting with nerve tissue, and methods of making and using it
US8831732B2 (en) 2010-04-29 2014-09-09 Cyberonics, Inc. Method, apparatus and system for validating and quantifying cardiac beat data quality
US8649871B2 (en) 2010-04-29 2014-02-11 Cyberonics, Inc. Validity test adaptive constraint modification for cardiac data used for detection of state changes
US8562536B2 (en) 2010-04-29 2013-10-22 Flint Hills Scientific, Llc Algorithm for detecting a seizure from cardiac data
US8641646B2 (en) 2010-07-30 2014-02-04 Cyberonics, Inc. Seizure detection using coordinate data
US8571643B2 (en) 2010-09-16 2013-10-29 Flint Hills Scientific, Llc Detecting or validating a detection of a state change from a template of heart rate derivative shape or heart beat wave complex
US8382667B2 (en) 2010-10-01 2013-02-26 Flint Hills Scientific, Llc Detecting, quantifying, and/or classifying seizures using multimodal data
US8337404B2 (en) 2010-10-01 2012-12-25 Flint Hills Scientific, Llc Detecting, quantifying, and/or classifying seizures using multimodal data
US8684921B2 (en) 2010-10-01 2014-04-01 Flint Hills Scientific Llc Detecting, assessing and managing epilepsy using a multi-variate, metric-based classification analysis
US8983572B2 (en) 2010-10-29 2015-03-17 Inspire Medical Systems, Inc. System and method for patient selection in treating sleep disordered breathing
US20120123503A1 (en) * 2010-11-15 2012-05-17 Medtronic, Inc. Patient programmer with customizable programming
US8855771B2 (en) 2011-01-28 2014-10-07 Cyberonics, Inc. Screening devices and methods for obstructive sleep apnea therapy
US20120192874A1 (en) 2011-01-28 2012-08-02 Apnex Medical, Inc. Obstructive sleep apnea treatment devices, systems and methods
US9205262B2 (en) 2011-05-12 2015-12-08 Cyberonics, Inc. Devices and methods for sleep apnea treatment
US9504390B2 (en) 2011-03-04 2016-11-29 Globalfoundries Inc. Detecting, assessing and managing a risk of death in epilepsy
US8725239B2 (en) 2011-04-25 2014-05-13 Cyberonics, Inc. Identifying seizures using heart rate decrease
US9402550B2 (en) 2011-04-29 2016-08-02 Cybertronics, Inc. Dynamic heart rate threshold for neurological event detection
US8934992B2 (en) 2011-09-01 2015-01-13 Inspire Medical Systems, Inc. Nerve cuff
US9681836B2 (en) 2012-04-23 2017-06-20 Cyberonics, Inc. Methods, systems and apparatuses for detecting seizure and non-seizure states
US20150128353A1 (en) * 2012-09-10 2015-05-14 Boyd Thomas Kildey Sleep monitoring system and method
US9446243B2 (en) 2012-12-07 2016-09-20 Boston Scientific Neuromodulation Corporation Patient posture determination and stimulation program adjustment in an implantable stimulator device using impedance fingerprinting
JP6121044B2 (en) 2013-03-14 2017-04-26 セレクト コンフォート コーポレーションSelect Comfort Corporation System architecture of an inflatable air mattress
EP2967223B1 (en) 2013-03-14 2017-11-15 SleepIQ Labs Inc. Inflatable air mattress with light controls
CA2905834A1 (en) 2013-03-14 2014-10-02 Select Comfort Corporation Inflatable air mattress snoring detection and response
WO2014151854A1 (en) 2013-03-14 2014-09-25 Nunn Rob Inflatable air mattress autofill and off bed pressure adjustment
EP2967224B1 (en) 2013-03-14 2018-01-17 Select Comfort Corporation Inflatable air mattress system with detection techniques
US9504416B2 (en) 2013-07-03 2016-11-29 Sleepiq Labs Inc. Smart seat monitoring system
US9445751B2 (en) 2013-07-18 2016-09-20 Sleepiq Labs, Inc. Device and method of monitoring a position and predicting an exit of a subject on or from a substrate
EP3065635A4 (en) * 2013-11-01 2017-08-30 Medtronic Monitoring Inc Congestive heart failure risk status determination methods and related devices
EP3089623A4 (en) 2013-12-30 2017-09-13 Select Comfort Corp Inflatable air mattress with integrated control
US9403011B2 (en) 2014-08-27 2016-08-02 Aleva Neurotherapeutics Leadless neurostimulator
US9474894B2 (en) 2014-08-27 2016-10-25 Aleva Neurotherapeutics Deep brain stimulation lead
EP3212072A1 (en) * 2014-12-05 2017-09-06 Beddit Oy Sleep measurement computer system
US9692874B2 (en) * 2015-09-30 2017-06-27 Apple Inc. Adjusting alarms based on sleep onset latency
CN106308752A (en) * 2016-08-23 2017-01-11 广东小天才科技有限公司 Sleep monitoring method based on wearable equipment and sleep monitoring system based on wearable equipment

Citations (84)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4297685A (en) * 1979-05-31 1981-10-27 Environmental Devices Corporation Apparatus and method for sleep detection
US5125412A (en) * 1990-07-23 1992-06-30 Thornton William E Musculoskeletal activity monitor
US5275159A (en) * 1991-03-22 1994-01-04 Madaus Schwarzer Medizintechnik Gmbh & Co. Kg Method and apparatus for diagnosis of sleep disorders
US5335657A (en) * 1991-05-03 1994-08-09 Cyberonics, Inc. Therapeutic treatment of sleep disorder by nerve stimulation
US5337758A (en) * 1991-01-11 1994-08-16 Orthopedic Systems, Inc. Spine motion analyzer and method
US5469861A (en) * 1992-04-17 1995-11-28 Mark F. Piscopo Posture monitor
US5514162A (en) * 1994-06-07 1996-05-07 Pacesetter, Inc. System and method for automatically determining the slope of a transfer function for a rate-responsive cardiac pacemaker
US5593431A (en) * 1995-03-30 1997-01-14 Medtronic, Inc. Medical service employing multiple DC accelerometers for patient activity and posture sensing and method
US5645053A (en) * 1991-11-14 1997-07-08 University Technologies International, Inc. Auto CPAP system and method for preventing patient disturbance using airflow profile information
US5713923A (en) * 1996-05-13 1998-02-03 Medtronic, Inc. Techniques for treating epilepsy by brain stimulation and drug infusion
US5732696A (en) * 1992-03-17 1998-03-31 New York University Polysomnograph scoring
US5833709A (en) * 1996-04-25 1998-11-10 Medtronic, Inc. Method of treating movement disorders by brain stimulation
US5895371A (en) * 1996-08-27 1999-04-20 Sabratek Corporation Medical treatment apparatus and method
US5904708A (en) * 1998-03-19 1999-05-18 Medtronic, Inc. System and method for deriving relative physiologic signals
US5919149A (en) * 1996-03-19 1999-07-06 Allum; John H. Method and apparatus for angular position and velocity based determination of body sway for the diagnosis and rehabilitation of balance and gait disorders
US5999846A (en) * 1995-11-08 1999-12-07 Oxford Medical Limited Physiological monitoring
US6045513A (en) * 1998-05-13 2000-04-04 Medtronic, Inc. Implantable medical device for tracking patient functional status
US6059576A (en) * 1997-11-21 2000-05-09 Brann; Theodore L. Training and safety device, system and method to aid in proper movement during physical activity
US6091973A (en) * 1995-04-11 2000-07-18 Resmed Limited Monitoring the occurrence of apneic and hypopneic arousals
US6095991A (en) * 1998-07-23 2000-08-01 Individual Monitoring Systems, Inc. Ambulatory body position monitor
US6120467A (en) * 1998-04-30 2000-09-19 Medtronic Inc. Spinal cord simulation systems with patient activity monitoring and therapy adjustments
US6165143A (en) * 1998-03-17 2000-12-26 Van Lummel; R. C. Method for measuring and indicating the extent to which an individual is limited in daily life activities
US6227203B1 (en) * 1998-02-12 2001-05-08 Medtronic, Inc. Techniques for controlling abnormal involuntary movements by brain stimulation and drug infusion
US6273856B1 (en) * 1999-10-19 2001-08-14 Cardiac Pacemakers, Inc. Apparatus and methods for METS measurement by accelerometer and minute ventilation sensors
US6296606B1 (en) * 1993-12-17 2001-10-02 Charles Goldberg Patient thermal support device
US20010031930A1 (en) * 1999-12-19 2001-10-18 Roizen Michael F. Alarm upon detection of impending sleep state
US6366813B1 (en) * 1998-08-05 2002-04-02 Dilorenzo Daniel J. Apparatus and method for closed-loop intracranical stimulation for optimal control of neurological disease
US20020077562A1 (en) * 2000-12-15 2002-06-20 James Kalgren System and method for correlation of patient health information and implant device data
US6416471B1 (en) * 1999-04-15 2002-07-09 Nexan Limited Portable remote patient telemonitoring system
US20020091308A1 (en) * 2001-01-09 2002-07-11 Kipshidze Nicholas N. Method and apparatus for the synchronized therapeutic treatment of a life form
US6459934B1 (en) * 2000-07-21 2002-10-01 Cardiac Pacemakers, Inc. Estimate of efficiency using acceleration-heart rate ratio
US20020161412A1 (en) * 2001-04-25 2002-10-31 Cardiac Pacemakers, Inc. Determination of long-term condition of cardiac patients
US20020169485A1 (en) * 1995-10-16 2002-11-14 Neuropace, Inc. Differential neurostimulation therapy driven by physiological context
US20020193697A1 (en) * 2001-04-30 2002-12-19 Cho Yong Kyun Method and apparatus to detect and treat sleep respiratory events
US20020193839A1 (en) * 2001-06-07 2002-12-19 Cho Yong Kyun Method for providing a therapy to a patient involving modifying the therapy after detecting an onset of sleep in the patient, and implantable medical device embodying same
US20030004423A1 (en) * 2000-03-02 2003-01-02 Itamar Medical Ltd. Method and apparatus for the non-invasive detection of particular sleep-state conditions by monitoring the peripheral vascular system
US6514218B2 (en) * 2000-01-07 2003-02-04 Minolta Co., Ltd. Posture detecting device and breathing function measuring device
US6539249B1 (en) * 1998-05-11 2003-03-25 Cardiac Pacemakers, Inc. Method and apparatus for assessing patient well-being
US6597954B1 (en) * 1997-10-27 2003-07-22 Neuropace, Inc. System and method for controlling epileptic seizures with spatially separated detection and stimulation electrodes
US20030139692A1 (en) * 2000-02-04 2003-07-24 Eric Barrey Method for analysing irregularities in human locomotion
US20030135917A1 (en) * 2002-01-24 2003-07-24 Ruane Joseph J. Reconfigurable orthopedic sleep aids
US20030149457A1 (en) * 2002-02-05 2003-08-07 Neuropace, Inc. Responsive electrical stimulation for movement disorders
US20030153953A1 (en) * 2002-02-14 2003-08-14 Euljoon Park Stimulation device for sleep apnea prevention, detection and treatment
US20030163059A1 (en) * 2001-12-07 2003-08-28 Yann Poezevera Discriminating between an awake phase and a sleep phase of a patient in an active implantable medical device
US20030195588A1 (en) * 2002-04-16 2003-10-16 Neuropace, Inc. External ear canal interface for the treatment of neurological disorders
US20030204219A1 (en) * 2002-04-29 2003-10-30 Frans Gielen Stimulation control for brain stimulation
US20030212445A1 (en) * 2002-05-13 2003-11-13 Weinberg Lisa P. Implantable neural stimulation device providing activity, rest, and long term closed-loop peripheral vascular disease therapy and method
US6659968B1 (en) * 2000-06-01 2003-12-09 Advanced Bionics Corporation Activity monitor for pain management efficacy measurement
US20040002742A1 (en) * 2002-06-27 2004-01-01 Florio Joseph J. Using activity-based rest disturbance as a metric of sleep apnea
US20040015103A1 (en) * 2000-10-05 2004-01-22 Kamiar Aminian Body movement monitoring system and method
US20040049132A1 (en) * 2000-06-15 2004-03-11 The Procter & Gamble Company Device for body activity detection and processing
US20040102814A1 (en) * 2002-11-22 2004-05-27 Chris Sorensen Physician programmer system with telemetered sensor waveform
US20040111040A1 (en) * 2002-12-04 2004-06-10 Quan Ni Detection of disordered breathing
US6752766B2 (en) * 2001-01-30 2004-06-22 Peter Kowallik Method and device for sleep monitoring
US20040199217A1 (en) * 2003-04-02 2004-10-07 Lee Michael T. Management of neurostimulation therapy using parameter sets
US20040215269A1 (en) * 2003-04-25 2004-10-28 Medtronic, Inc. System and method for supplying a patient reminder alert from an implantable medical device
US20050021103A1 (en) * 1998-08-05 2005-01-27 Dilorenzo Daniel John Apparatus and method for closed-loop intracranial stimulation for optimal control of neurological disease
US20050021104A1 (en) * 1998-08-05 2005-01-27 Dilorenzo Daniel John Apparatus and method for closed-loop intracranial stimulation for optimal control of neurological disease
US20050039745A1 (en) * 2003-08-18 2005-02-24 Stahmann Jeffrey E. Adaptive therapy for disordered breathing
US20050042589A1 (en) * 2003-08-18 2005-02-24 Hatlestad John D. Sleep quality data collection and evaluation
US20050065560A1 (en) * 2003-09-18 2005-03-24 Cardiac Pacemakers, Inc. Snoring detection system and method
US20050061320A1 (en) * 2003-09-18 2005-03-24 Cardiac Pacemakers, Inc. Coordinated use of respiratory and cardiac therapies for sleep disordered breathing
US6878121B2 (en) * 2002-11-01 2005-04-12 David T. Krausman Sleep scoring apparatus and method
US20050080463A1 (en) * 2003-09-18 2005-04-14 Stahmann Jeffrey E. System and method for detecting an involuntary muscle movement disorder
US20050076908A1 (en) * 2003-09-18 2005-04-14 Kent Lee Autonomic arousal detection system and method
US6881192B1 (en) * 2002-06-12 2005-04-19 Pacesetter, Inc. Measurement of sleep apnea duration and evaluation of response therapies using duration metrics
US20050085738A1 (en) * 2003-09-18 2005-04-21 Stahmann Jeffrey E. Sleep logbook
US6890306B2 (en) * 2001-12-14 2005-05-10 Ela Medical S.A. Active medical device for the diagnosis of the sleep apnea syndrome
US20050115561A1 (en) * 2003-08-18 2005-06-02 Stahmann Jeffrey E. Patient monitoring, diagnosis, and/or therapy systems and methods
US20050119703A1 (en) * 1998-08-05 2005-06-02 Dilorenzo Daniel J. Apparatus and method for closed-loop intracranial stimulation for optimal control of neurological disease
US20050143617A1 (en) * 2003-12-31 2005-06-30 Raphael Auphan Sleep and environment control method and system
US20050177192A1 (en) * 2002-02-01 2005-08-11 Ali Rezai Neurostimulation for affecting sleep disorders
US20050222626A1 (en) * 1998-08-05 2005-10-06 Dilorenzo Daniel J Cloosed-loop feedback-driven neuromodulation
US20050240242A1 (en) * 1998-08-05 2005-10-27 Dilorenzo Daniel J Closed-loop feedback-driven neuromodulation
US20050240086A1 (en) * 2004-03-12 2005-10-27 Metin Akay Intelligent wearable monitor systems and methods
US20050245790A1 (en) * 2002-10-04 2005-11-03 Henrik Bergfalk Detection of psychological disorder activity patterns
US20060224191A1 (en) * 1998-08-05 2006-10-05 Dilorenzo Daniel J Systems and methods for monitoring a patient's neurological disease state
US20060293720A1 (en) * 1998-08-05 2006-12-28 Dilorenzo Daniel J Closed-loop feedback-driven neuromodulation
US7162304B1 (en) * 2003-05-08 2007-01-09 Advanced Bionics Corporation System for measuring cardiac rhythm parameters for assessment of spinal cord stimulation
US20070142862A1 (en) * 1998-08-05 2007-06-21 Dilorenzo Daniel J Systems and methods for monitoring a patient's neurological disease state
US7309314B2 (en) * 2003-09-23 2007-12-18 U.S. Department Of Veterans Affairs Method for predicting apnea-hypopnea index from overnight pulse oximetry readings
US7366572B2 (en) * 2004-03-16 2008-04-29 Medtronic, Inc. Controlling therapy based on sleep quality
US20080154111A1 (en) * 2006-12-22 2008-06-26 Jianping Wu Method, system and device for sleep stage determination using frontal electrodes
US7468040B2 (en) * 2003-09-18 2008-12-23 Cardiac Pacemakers, Inc. Methods and systems for implantably monitoring external breathing therapy

Family Cites Families (105)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US39745A (en) * 1863-09-01 Improvement in hoisting apparatus
US61320A (en) * 1867-01-22 of lewiston
US76908A (en) * 1868-04-21 William wallace goodwin
US65560A (en) * 1867-06-11 Dennis goodyear
US143617A (en) * 1873-10-14 Improvement in peat-machines
US85738A (en) * 1869-01-12 Improvement in picture-hook
CA1213330A (en) 1983-10-14 1986-10-28 Roger Broughton Movement artifact detector for sleep analysis
US4771780A (en) * 1987-01-15 1988-09-20 Siemens-Pacesetter, Inc. Rate-responsive pacemaker having digital motion sensor
DE3709073C2 (en) * 1987-03-19 1990-09-06 Eckhard Dr. 8000 Muenchen De Alt
US4776345A (en) * 1987-09-04 1988-10-11 Cns, Inc. Interactive determination of sleep stages
US5278190A (en) 1989-11-30 1994-01-11 Clintec Nutrition Co. Method for improving the quality of sleep and treating sleep disorders
FR2657443B1 (en) * 1990-01-24 1992-05-15 Blanchet Gerard Method and processing apparatus of electroencephalographic signal.
US5040536A (en) * 1990-01-31 1991-08-20 Medtronic, Inc. Intravascular pressure posture detector
US5031618A (en) * 1990-03-07 1991-07-16 Medtronic, Inc. Position-responsive neuro stimulator
US5050536A (en) * 1990-04-18 1991-09-24 Baker Reginald D Playhouse for cats
US5058584A (en) * 1990-08-30 1991-10-22 Medtronic, Inc. Method and apparatus for epidural burst stimulation for angina pectoris
US5233984A (en) * 1991-03-29 1993-08-10 Medtronic, Inc. Implantable multi-axis position and activity sensor
US5421830A (en) 1993-08-27 1995-06-06 Pacesetter, Inc. Programming system having means for recording and analyzing a patient's cardiac signal
US5476483A (en) 1994-06-10 1995-12-19 Pacesetter, Inc. System and method for modulating the base rate during sleep for a rate-responsive cardiac pacemaker
FI100851B (en) 1994-08-15 1998-03-13 Polar Electro Oy Method and apparatus for the individual's body part at eröimiseen and ambulatory recording regist Simultaneously, as well as movements of the different body parts for monitoring the superposed
FR2728798B1 (en) * 1994-12-30 1997-06-20 Ela Medical Sa A method of determining an activity criterion of a sensor for measuring a control parameter in an active implantable medical device
US5725562A (en) 1995-03-30 1998-03-10 Medtronic Inc Rate responsive cardiac pacemaker and method for discriminating stair climbing from other activities
US5591216A (en) 1995-05-19 1997-01-07 Medtronic, Inc. Method for treatment of sleep apnea by electrical stimulation
US5643332A (en) 1995-09-20 1997-07-01 Neuromotion Inc. Assembly for functional electrical stimulation during movement
US5683432A (en) 1996-01-11 1997-11-04 Medtronic, Inc. Adaptive, performance-optimizing communication system for communicating with an implanted medical device
US6094598A (en) 1996-04-25 2000-07-25 Medtronics, Inc. Method of treating movement disorders by brain stimulation and drug infusion
US5938690A (en) 1996-06-07 1999-08-17 Advanced Neuromodulation Systems, Inc. Pain management system and method
US5944680A (en) * 1996-06-26 1999-08-31 Medtronic, Inc. Respiratory effort detection method and apparatus
US5782884A (en) * 1996-11-05 1998-07-21 Sulzer Intermedics Inc. Rate responsive cardiac pacemaker with peak impedance detection for rate control
DE19653773C1 (en) 1996-12-21 1998-07-02 Ggt Ges Fuer Gerontotechnik Mb Method and device for detection of fall situations of persons with a risk to health
US6249700B1 (en) 1997-06-12 2001-06-19 Eckhard Alt Defibrillator with improved hemodynamic response and enhanced myocardial stability
GB9719497D0 (en) 1997-09-12 1997-11-19 Home Diagnostics Uk Limited Remote monitoring
US5941906A (en) * 1997-10-15 1999-08-24 Medtronic, Inc. Implantable, modular tissue stimulator
DE29719250U1 (en) 1997-10-30 1998-05-07 Hauptverband Der Gewerblichen Körperbelastungsmeß- and analysis system
US6128534A (en) * 1998-06-16 2000-10-03 Pacesetter, Inc. Implantable cardiac stimulation device and method for varying pacing parameters to mimic circadian cycles
FR2780654B1 (en) * 1998-07-06 2000-12-01 Ela Medical Sa Device for active implantable medical treatment by electrostimulation of the sleep apnea syndrome
US6735474B1 (en) 1998-07-06 2004-05-11 Advanced Bionics Corporation Implantable stimulator system and method for treatment of incontinence and pain
DE19831109A1 (en) 1998-07-11 2000-01-13 Univ Schiller Jena Monitoring and evaluation of infants and new born breathing cycle
US6157857A (en) 1998-07-24 2000-12-05 Dimpfel; Wilfried Apparatus for determining sleep staging
DE19842107A1 (en) * 1998-09-08 2000-03-09 Biotronik Mess & Therapieg Method for detecting the body position of a person
US6044297A (en) * 1998-09-25 2000-03-28 Medtronic, Inc. Posture and device orientation and calibration for implantable medical devices
US6160478A (en) 1998-10-27 2000-12-12 Sarcos Lc Wireless health monitoring system
US6259948B1 (en) * 1998-11-13 2001-07-10 Pacesetter, Inc. Medical device
US6161095A (en) 1998-12-16 2000-12-12 Health Hero Network, Inc. Treatment regimen compliance and efficacy with feedback
US6466234B1 (en) 1999-02-03 2002-10-15 Microsoft Corporation Method and system for controlling environmental conditions
US6315740B1 (en) 1999-05-17 2001-11-13 Balbir Singh Seizure and movement monitoring apparatus
US7141034B2 (en) 2000-06-08 2006-11-28 Altea Therapeutics Corporation Transdermal drug delivery device, method of making same and method of using same
US6351672B1 (en) * 1999-07-22 2002-02-26 Pacesetter, Inc. System and method for modulating the pacing rate based on patient activity and position
US6449508B1 (en) * 1999-10-21 2002-09-10 Medtronic, Inc. Accelerometer count calculation for activity signal for an implantable medical device
US6466821B1 (en) 1999-12-08 2002-10-15 Pacesetter, Inc. AC/DC multi-axis accelerometer for determining patient activity and body position
US8002700B2 (en) 1999-12-30 2011-08-23 Medtronic, Inc. Communications system for an implantable medical device and a delivery device
US6611783B2 (en) * 2000-01-07 2003-08-26 Nocwatch, Inc. Attitude indicator and activity monitoring device
US6873268B2 (en) 2000-01-21 2005-03-29 Medtronic Minimed, Inc. Microprocessor controlled ambulatory medical apparatus with hand held communication device
US6626902B1 (en) 2000-04-12 2003-09-30 University Of Virginia Patent Foundation Multi-probe system
US6884596B2 (en) * 2000-04-28 2005-04-26 The Regents Of The University Of California Screening and therapeutic methods for promoting wakefulness and sleep
US6572557B2 (en) 2000-05-09 2003-06-03 Pacesetter, Inc. System and method for monitoring progression of cardiac disease state using physiologic sensors
DE10024103A1 (en) 2000-05-18 2001-11-29 Baumgart Schmitt Rudolf Arrangement for improving sleep quality by thermal stimulation has several thermoelectric units driven if sleep-related breathing problem automatically detected in real time
JP2001344352A (en) * 2000-05-31 2001-12-14 Toshiba Corp Life assisting device, life assisting method and advertisement information providing method
US6605038B1 (en) * 2000-06-16 2003-08-12 Bodymedia, Inc. System for monitoring health, wellness and fitness
US6687538B1 (en) * 2000-06-19 2004-02-03 Medtronic, Inc. Trial neuro stimulator with lead diagnostics
US6468234B1 (en) 2000-07-14 2002-10-22 The Board Of Trustees Of The Leland Stanford Junior University SleepSmart
WO2002041771A1 (en) 2000-11-27 2002-05-30 Modco Inc. Apparatus and method for monitoring blood pressure and another physiological parameter
US7167751B1 (en) 2001-03-01 2007-01-23 Advanced Bionics Corporation Method of using a fully implantable miniature neurostimulator for vagus nerve stimulation
EP1395335A1 (en) 2001-05-29 2004-03-10 Medtronic, Inc. Closed-loop neuromodulation for prevention and treatment of cardiac conditions
CA2448806C (en) 2001-06-13 2011-10-18 Compumedics Limited Methods and apparatus for monitoring consciousness
US6662047B2 (en) 2001-09-05 2003-12-09 Pacesetter, Inc. Pacing mode to reduce effects of orthostatic hypotension and syncope
WO2003024325A3 (en) 2001-09-21 2003-12-18 Clark Hinton Vital sign detector
US6751503B1 (en) 2001-11-01 2004-06-15 Pacesetter, Inc. Methods and systems for treating patients with congestive heart failure (CHF)
WO2003051356A1 (en) 2001-12-17 2003-06-26 Merck & Co., Inc. Method for treating circadian rhythm disruptions
EP1511418B1 (en) 2002-02-07 2009-04-08 Ecole Polytechnique Fédérale de Lausanne (EPFL) Body movement monitoring device
US6999817B2 (en) * 2002-02-14 2006-02-14 Packsetter, Inc. Cardiac stimulation device including sleep apnea prevention and treatment
US7043305B2 (en) * 2002-03-06 2006-05-09 Cardiac Pacemakers, Inc. Method and apparatus for establishing context among events and optimizing implanted medical device performance
US6937891B2 (en) 2002-04-26 2005-08-30 Medtronic, Inc. Independent therapy programs in an implantable medical device
US7151961B1 (en) 2002-05-24 2006-12-19 Advanced Bionics Corporation Treatment of movement disorders by brain stimulation
US6922587B2 (en) * 2002-06-26 2005-07-26 Pacesetter, Inc. System and method for tracking progression of left ventricular dysfunction using implantable cardiac stimulation device
US7369896B2 (en) 2002-10-24 2008-05-06 Lockheed Martin Corporation Systems and methods for treating movement disorders
US7189204B2 (en) * 2002-12-04 2007-03-13 Cardiac Pacemakers, Inc. Sleep detection using an adjustable threshold
US7025730B2 (en) * 2003-01-10 2006-04-11 Medtronic, Inc. System and method for automatically monitoring and delivering therapy for sleep-related disordered breathing
US7207947B2 (en) 2003-01-10 2007-04-24 Pacesetter, Inc. System and method for detecting circadian states using an implantable medical device
US7155279B2 (en) 2003-03-28 2006-12-26 Advanced Bionics Corporation Treatment of movement disorders with drug therapy
US7221979B2 (en) 2003-04-30 2007-05-22 Medtronic, Inc. Methods and apparatus for the regulation of hormone release
US7680537B2 (en) * 2003-08-18 2010-03-16 Cardiac Pacemakers, Inc. Therapy triggered by prediction of disordered breathing
US8396565B2 (en) 2003-09-15 2013-03-12 Medtronic, Inc. Automatic therapy adjustments
US7887493B2 (en) * 2003-09-18 2011-02-15 Cardiac Pacemakers, Inc. Implantable device employing movement sensing for detecting sleep-related disorders
US20050087538A1 (en) * 2003-10-23 2005-04-28 Wolfe Darrell R. Iceless multiple can cooler
US6964641B2 (en) 2003-12-24 2005-11-15 Medtronic, Inc. Implantable medical device with sleep disordered breathing monitoring
US7130689B1 (en) 2004-02-24 2006-10-31 Pacesetter, Inc. Methods and systems for optimizing cardiac pacing intervals for various physiologic factors
US8308661B2 (en) 2004-03-16 2012-11-13 Medtronic, Inc. Collecting activity and sleep quality information via a medical device
US7881798B2 (en) 2004-03-16 2011-02-01 Medtronic Inc. Controlling therapy based on sleep quality
US7805196B2 (en) 2004-03-16 2010-09-28 Medtronic, Inc. Collecting activity information to evaluate therapy
US8725244B2 (en) 2004-03-16 2014-05-13 Medtronic, Inc. Determination of sleep quality for neurological disorders
US7792583B2 (en) 2004-03-16 2010-09-07 Medtronic, Inc. Collecting posture information to evaluate therapy
US7542803B2 (en) 2004-03-16 2009-06-02 Medtronic, Inc. Sensitivity analysis for selecting therapy parameter sets
US7717848B2 (en) * 2004-03-16 2010-05-18 Medtronic, Inc. Collecting sleep quality information via a medical device
US7395113B2 (en) 2004-03-16 2008-07-01 Medtronic, Inc. Collecting activity information to evaluate therapy
US7330760B2 (en) 2004-03-16 2008-02-12 Medtronic, Inc. Collecting posture information to evaluate therapy
US20050209512A1 (en) 2004-03-16 2005-09-22 Heruth Kenneth T Detecting sleep
US7491181B2 (en) 2004-03-16 2009-02-17 Medtronic, Inc. Collecting activity and sleep quality information via a medical device
US8135473B2 (en) 2004-04-14 2012-03-13 Medtronic, Inc. Collecting posture and activity information to evaluate therapy
US7313440B2 (en) 2004-04-14 2007-12-25 Medtronic, Inc. Collecting posture and activity information to evaluate therapy
US7819909B2 (en) 2004-07-20 2010-10-26 Medtronic, Inc. Therapy programming guidance based on stored programming history
US7415308B2 (en) 2005-02-23 2008-08-19 Medtronic, Inc. Implantable medical device providing adaptive neurostimulation therapy for incontinence
US20070046408A1 (en) 2005-08-30 2007-03-01 Youngtack Shim Magnet-shunted systems and methods
US7853322B2 (en) 2005-12-02 2010-12-14 Medtronic, Inc. Closed-loop therapy adjustment
US8744587B2 (en) 2006-03-24 2014-06-03 Medtronic, Inc. Collecting gait information for evaluation and control of therapy

Patent Citations (93)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4297685A (en) * 1979-05-31 1981-10-27 Environmental Devices Corporation Apparatus and method for sleep detection
US5125412A (en) * 1990-07-23 1992-06-30 Thornton William E Musculoskeletal activity monitor
US5337758A (en) * 1991-01-11 1994-08-16 Orthopedic Systems, Inc. Spine motion analyzer and method
US5275159A (en) * 1991-03-22 1994-01-04 Madaus Schwarzer Medizintechnik Gmbh & Co. Kg Method and apparatus for diagnosis of sleep disorders
US5335657A (en) * 1991-05-03 1994-08-09 Cyberonics, Inc. Therapeutic treatment of sleep disorder by nerve stimulation
US5645053A (en) * 1991-11-14 1997-07-08 University Technologies International, Inc. Auto CPAP system and method for preventing patient disturbance using airflow profile information
US5732696A (en) * 1992-03-17 1998-03-31 New York University Polysomnograph scoring
US5469861A (en) * 1992-04-17 1995-11-28 Mark F. Piscopo Posture monitor
US6296606B1 (en) * 1993-12-17 2001-10-02 Charles Goldberg Patient thermal support device
US5514162A (en) * 1994-06-07 1996-05-07 Pacesetter, Inc. System and method for automatically determining the slope of a transfer function for a rate-responsive cardiac pacemaker
US5593431A (en) * 1995-03-30 1997-01-14 Medtronic, Inc. Medical service employing multiple DC accelerometers for patient activity and posture sensing and method
US6091973A (en) * 1995-04-11 2000-07-18 Resmed Limited Monitoring the occurrence of apneic and hypopneic arousals
US20020169485A1 (en) * 1995-10-16 2002-11-14 Neuropace, Inc. Differential neurostimulation therapy driven by physiological context
US5999846A (en) * 1995-11-08 1999-12-07 Oxford Medical Limited Physiological monitoring
US5919149A (en) * 1996-03-19 1999-07-06 Allum; John H. Method and apparatus for angular position and velocity based determination of body sway for the diagnosis and rehabilitation of balance and gait disorders
US5833709A (en) * 1996-04-25 1998-11-10 Medtronic, Inc. Method of treating movement disorders by brain stimulation
US5713923A (en) * 1996-05-13 1998-02-03 Medtronic, Inc. Techniques for treating epilepsy by brain stimulation and drug infusion
US5895371A (en) * 1996-08-27 1999-04-20 Sabratek Corporation Medical treatment apparatus and method
US6597954B1 (en) * 1997-10-27 2003-07-22 Neuropace, Inc. System and method for controlling epileptic seizures with spatially separated detection and stimulation electrodes
US6059576A (en) * 1997-11-21 2000-05-09 Brann; Theodore L. Training and safety device, system and method to aid in proper movement during physical activity
US6227203B1 (en) * 1998-02-12 2001-05-08 Medtronic, Inc. Techniques for controlling abnormal involuntary movements by brain stimulation and drug infusion
US6165143A (en) * 1998-03-17 2000-12-26 Van Lummel; R. C. Method for measuring and indicating the extent to which an individual is limited in daily life activities
US5904708A (en) * 1998-03-19 1999-05-18 Medtronic, Inc. System and method for deriving relative physiologic signals
US6120467A (en) * 1998-04-30 2000-09-19 Medtronic Inc. Spinal cord simulation systems with patient activity monitoring and therapy adjustments
US6539249B1 (en) * 1998-05-11 2003-03-25 Cardiac Pacemakers, Inc. Method and apparatus for assessing patient well-being
US6045513A (en) * 1998-05-13 2000-04-04 Medtronic, Inc. Implantable medical device for tracking patient functional status
US6095991A (en) * 1998-07-23 2000-08-01 Individual Monitoring Systems, Inc. Ambulatory body position monitor
US20050021104A1 (en) * 1998-08-05 2005-01-27 Dilorenzo Daniel John Apparatus and method for closed-loop intracranial stimulation for optimal control of neurological disease
US6819956B2 (en) * 1998-08-05 2004-11-16 Dilorenzo Daniel J. Optimal method and apparatus for neural modulation for the treatment of neurological disease, particularly movement disorders
US20050240242A1 (en) * 1998-08-05 2005-10-27 Dilorenzo Daniel J Closed-loop feedback-driven neuromodulation
US20060224191A1 (en) * 1998-08-05 2006-10-05 Dilorenzo Daniel J Systems and methods for monitoring a patient's neurological disease state
US20060293720A1 (en) * 1998-08-05 2006-12-28 Dilorenzo Daniel J Closed-loop feedback-driven neuromodulation
US20050021103A1 (en) * 1998-08-05 2005-01-27 Dilorenzo Daniel John Apparatus and method for closed-loop intracranial stimulation for optimal control of neurological disease
US6366813B1 (en) * 1998-08-05 2002-04-02 Dilorenzo Daniel J. Apparatus and method for closed-loop intracranical stimulation for optimal control of neurological disease
US20070073355A1 (en) * 1998-08-05 2007-03-29 Bioneuronics Corporation Apparatus and method for closed-loop intracranial stimulation for optimal control of neurological disease
US7209787B2 (en) * 1998-08-05 2007-04-24 Bioneuronics Corporation Apparatus and method for closed-loop intracranial stimulation for optimal control of neurological disease
US20070142862A1 (en) * 1998-08-05 2007-06-21 Dilorenzo Daniel J Systems and methods for monitoring a patient's neurological disease state
US20050222626A1 (en) * 1998-08-05 2005-10-06 Dilorenzo Daniel J Cloosed-loop feedback-driven neuromodulation
US20020177882A1 (en) * 1998-08-05 2002-11-28 Dilorenzo Daniel J. Optimal method and apparatus for neural modulation for the treatment of neurological disease, particularly movement disorders
US20050119703A1 (en) * 1998-08-05 2005-06-02 Dilorenzo Daniel J. Apparatus and method for closed-loop intracranial stimulation for optimal control of neurological disease
US6416471B1 (en) * 1999-04-15 2002-07-09 Nexan Limited Portable remote patient telemonitoring system
US6273856B1 (en) * 1999-10-19 2001-08-14 Cardiac Pacemakers, Inc. Apparatus and methods for METS measurement by accelerometer and minute ventilation sensors
US20010031930A1 (en) * 1999-12-19 2001-10-18 Roizen Michael F. Alarm upon detection of impending sleep state
US6514218B2 (en) * 2000-01-07 2003-02-04 Minolta Co., Ltd. Posture detecting device and breathing function measuring device
US20030139692A1 (en) * 2000-02-04 2003-07-24 Eric Barrey Method for analysing irregularities in human locomotion
US20030004423A1 (en) * 2000-03-02 2003-01-02 Itamar Medical Ltd. Method and apparatus for the non-invasive detection of particular sleep-state conditions by monitoring the peripheral vascular system
US6659968B1 (en) * 2000-06-01 2003-12-09 Advanced Bionics Corporation Activity monitor for pain management efficacy measurement
US20040049132A1 (en) * 2000-06-15 2004-03-11 The Procter & Gamble Company Device for body activity detection and processing
US6459934B1 (en) * 2000-07-21 2002-10-01 Cardiac Pacemakers, Inc. Estimate of efficiency using acceleration-heart rate ratio
US20040015103A1 (en) * 2000-10-05 2004-01-22 Kamiar Aminian Body movement monitoring system and method
US6665558B2 (en) * 2000-12-15 2003-12-16 Cardiac Pacemakers, Inc. System and method for correlation of patient health information and implant device data
US20020077562A1 (en) * 2000-12-15 2002-06-20 James Kalgren System and method for correlation of patient health information and implant device data
US20020091308A1 (en) * 2001-01-09 2002-07-11 Kipshidze Nicholas N. Method and apparatus for the synchronized therapeutic treatment of a life form
US6752766B2 (en) * 2001-01-30 2004-06-22 Peter Kowallik Method and device for sleep monitoring
US20020161412A1 (en) * 2001-04-25 2002-10-31 Cardiac Pacemakers, Inc. Determination of long-term condition of cardiac patients
US20020193697A1 (en) * 2001-04-30 2002-12-19 Cho Yong Kyun Method and apparatus to detect and treat sleep respiratory events
US20020193839A1 (en) * 2001-06-07 2002-12-19 Cho Yong Kyun Method for providing a therapy to a patient involving modifying the therapy after detecting an onset of sleep in the patient, and implantable medical device embodying same
US6773404B2 (en) * 2001-12-07 2004-08-10 Ela Medical S.A. Discriminating between an awake phase and a sleep phase of a patient in an active implantable medical device
US20030163059A1 (en) * 2001-12-07 2003-08-28 Yann Poezevera Discriminating between an awake phase and a sleep phase of a patient in an active implantable medical device
US6890306B2 (en) * 2001-12-14 2005-05-10 Ela Medical S.A. Active medical device for the diagnosis of the sleep apnea syndrome
US20030135917A1 (en) * 2002-01-24 2003-07-24 Ruane Joseph J. Reconfigurable orthopedic sleep aids
US20050177192A1 (en) * 2002-02-01 2005-08-11 Ali Rezai Neurostimulation for affecting sleep disorders
US20030149457A1 (en) * 2002-02-05 2003-08-07 Neuropace, Inc. Responsive electrical stimulation for movement disorders
US20030153953A1 (en) * 2002-02-14 2003-08-14 Euljoon Park Stimulation device for sleep apnea prevention, detection and treatment
US6928324B2 (en) * 2002-02-14 2005-08-09 Pacesetter, Inc. Stimulation device for sleep apnea prevention, detection and treatment
US20030195588A1 (en) * 2002-04-16 2003-10-16 Neuropace, Inc. External ear canal interface for the treatment of neurological disorders
US20030204219A1 (en) * 2002-04-29 2003-10-30 Frans Gielen Stimulation control for brain stimulation
US20030212445A1 (en) * 2002-05-13 2003-11-13 Weinberg Lisa P. Implantable neural stimulation device providing activity, rest, and long term closed-loop peripheral vascular disease therapy and method
US6881192B1 (en) * 2002-06-12 2005-04-19 Pacesetter, Inc. Measurement of sleep apnea duration and evaluation of response therapies using duration metrics
US20040002742A1 (en) * 2002-06-27 2004-01-01 Florio Joseph J. Using activity-based rest disturbance as a metric of sleep apnea
US20050245790A1 (en) * 2002-10-04 2005-11-03 Henrik Bergfalk Detection of psychological disorder activity patterns
US6878121B2 (en) * 2002-11-01 2005-04-12 David T. Krausman Sleep scoring apparatus and method
US20040102814A1 (en) * 2002-11-22 2004-05-27 Chris Sorensen Physician programmer system with telemetered sensor waveform
US20040111040A1 (en) * 2002-12-04 2004-06-10 Quan Ni Detection of disordered breathing
US20040199217A1 (en) * 2003-04-02 2004-10-07 Lee Michael T. Management of neurostimulation therapy using parameter sets
US20040215269A1 (en) * 2003-04-25 2004-10-28 Medtronic, Inc. System and method for supplying a patient reminder alert from an implantable medical device
US7162304B1 (en) * 2003-05-08 2007-01-09 Advanced Bionics Corporation System for measuring cardiac rhythm parameters for assessment of spinal cord stimulation
US7787946B2 (en) * 2003-08-18 2010-08-31 Cardiac Pacemakers, Inc. Patient monitoring, diagnosis, and/or therapy systems and methods
US20050115561A1 (en) * 2003-08-18 2005-06-02 Stahmann Jeffrey E. Patient monitoring, diagnosis, and/or therapy systems and methods
US20050039745A1 (en) * 2003-08-18 2005-02-24 Stahmann Jeffrey E. Adaptive therapy for disordered breathing
US20050042589A1 (en) * 2003-08-18 2005-02-24 Hatlestad John D. Sleep quality data collection and evaluation
US7468040B2 (en) * 2003-09-18 2008-12-23 Cardiac Pacemakers, Inc. Methods and systems for implantably monitoring external breathing therapy
US20050061320A1 (en) * 2003-09-18 2005-03-24 Cardiac Pacemakers, Inc. Coordinated use of respiratory and cardiac therapies for sleep disordered breathing
US20050076908A1 (en) * 2003-09-18 2005-04-14 Kent Lee Autonomic arousal detection system and method
US20050065560A1 (en) * 2003-09-18 2005-03-24 Cardiac Pacemakers, Inc. Snoring detection system and method
US20050080463A1 (en) * 2003-09-18 2005-04-14 Stahmann Jeffrey E. System and method for detecting an involuntary muscle movement disorder
US20050085738A1 (en) * 2003-09-18 2005-04-21 Stahmann Jeffrey E. Sleep logbook
US7309314B2 (en) * 2003-09-23 2007-12-18 U.S. Department Of Veterans Affairs Method for predicting apnea-hypopnea index from overnight pulse oximetry readings
US20050143617A1 (en) * 2003-12-31 2005-06-30 Raphael Auphan Sleep and environment control method and system
US20050240086A1 (en) * 2004-03-12 2005-10-27 Metin Akay Intelligent wearable monitor systems and methods
US7366572B2 (en) * 2004-03-16 2008-04-29 Medtronic, Inc. Controlling therapy based on sleep quality
US20080154111A1 (en) * 2006-12-22 2008-06-26 Jianping Wu Method, system and device for sleep stage determination using frontal electrodes
US8244340B2 (en) * 2006-12-22 2012-08-14 Natus Medical Incorporated Method, system and device for sleep stage determination using frontal electrodes

Cited By (138)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7899509B2 (en) 2002-10-01 2011-03-01 Nellcor Puritan Bennett Llc Forehead sensor placement
US8452367B2 (en) 2002-10-01 2013-05-28 Covidien Lp Forehead sensor placement
US7822453B2 (en) 2002-10-01 2010-10-26 Nellcor Puritan Bennett Llc Forehead sensor placement
US7813779B2 (en) 2003-06-25 2010-10-12 Nellcor Puritan Bennett Llc Hat-based oximeter sensor
US7979102B2 (en) 2003-06-25 2011-07-12 Nellcor Puritan Bennett Llc Hat-based oximeter sensor
US7877127B2 (en) 2003-06-25 2011-01-25 Nellcor Puritan Bennett Llc Hat-based oximeter sensor
US7809420B2 (en) 2003-06-25 2010-10-05 Nellcor Puritan Bennett Llc Hat-based oximeter sensor
US7877126B2 (en) 2003-06-25 2011-01-25 Nellcor Puritan Bennett Llc Hat-based oximeter sensor
US8396565B2 (en) 2003-09-15 2013-03-12 Medtronic, Inc. Automatic therapy adjustments
US8412297B2 (en) 2003-10-01 2013-04-02 Covidien Lp Forehead sensor placement
US8792982B2 (en) 2004-03-16 2014-07-29 Medtronic, Inc. Collecting posture information to evaluate therapy
US8337431B2 (en) 2004-03-16 2012-12-25 Medtronic, Inc. Collecting activity and sleep quality information via a medical device
US8335568B2 (en) 2004-03-16 2012-12-18 Medtronic, Inc. Controlling therapy based on sleep quality
US20070123758A1 (en) * 2004-03-16 2007-05-31 Medtronic, Inc. Determination of sleep quality for neurological disorders
US8332038B2 (en) 2004-03-16 2012-12-11 Medtronic, Inc. Detecting sleep to evaluate therapy
US20050234514A1 (en) * 2004-03-16 2005-10-20 Heruth Kenneth T Collecting posture information to evaluate therapy
US20050234518A1 (en) * 2004-03-16 2005-10-20 Heruth Kenneth T Collecting activity and sleep quality information via a medical device
US20070276439A1 (en) * 2004-03-16 2007-11-29 Medtronic, Inc. Collecting sleep quality information via a medical device
US7330760B2 (en) 2004-03-16 2008-02-12 Medtronic, Inc. Collecting posture information to evaluate therapy
US20080071324A1 (en) * 2004-03-16 2008-03-20 Medtronic, Inc. Sensitivity analysis for selecting therapy parameter sets
US20080071326A1 (en) * 2004-03-16 2008-03-20 Medtronic, Inc. Detecting sleep to evaluate therapy
US20080071150A1 (en) * 2004-03-16 2008-03-20 Medtronic, Inc. Collecting activity and sleep quality information via a medical device
US7366572B2 (en) 2004-03-16 2008-04-29 Medtronic, Inc. Controlling therapy based on sleep quality
US7395113B2 (en) 2004-03-16 2008-07-01 Medtronic, Inc. Collecting activity information to evaluate therapy
US20080177355A1 (en) * 2004-03-16 2008-07-24 Medtronic, Inc. Collecting activity information to evaluate therapy
US20050209643A1 (en) * 2004-03-16 2005-09-22 Heruth Kenneth T Controlling therapy based on sleep quality
US8447401B2 (en) 2004-03-16 2013-05-21 Medtronic, Inc. Collecting posture information to evaluate therapy
US20090118599A1 (en) * 2004-03-16 2009-05-07 Medtronic, Inc. Collecting activity and sleep quality information via a medical device
US8308661B2 (en) 2004-03-16 2012-11-13 Medtronic, Inc. Collecting activity and sleep quality information via a medical device
US20090306740A1 (en) * 2004-03-16 2009-12-10 Medtronic, Inc. Controlling therapy based on sleep quality
US20050222522A1 (en) * 2004-03-16 2005-10-06 Heruth Kenneth T Detecting sleep
US20100174155A1 (en) * 2004-03-16 2010-07-08 Medtronic, Inc. Collecting sleep quality information via a medical device
US7775993B2 (en) 2004-03-16 2010-08-17 Medtronic, Inc. Detecting sleep
US7792583B2 (en) 2004-03-16 2010-09-07 Medtronic, Inc. Collecting posture information to evaluate therapy
US7805196B2 (en) 2004-03-16 2010-09-28 Medtronic, Inc. Collecting activity information to evaluate therapy
US20050216064A1 (en) * 2004-03-16 2005-09-29 Heruth Kenneth T Sensitivity analysis for selecting therapy parameter sets
US20050215947A1 (en) * 2004-03-16 2005-09-29 Heruth Kenneth T Controlling therapy based on sleep quality
US20050209511A1 (en) * 2004-03-16 2005-09-22 Heruth Kenneth T Collecting activity and sleep quality information via a medical device
US20100305665A1 (en) * 2004-03-16 2010-12-02 Medtronic, Inc. Collecting posture information to evaluate therapy
US7717848B2 (en) 2004-03-16 2010-05-18 Medtronic, Inc. Collecting sleep quality information via a medical device
US20050209513A1 (en) * 2004-03-16 2005-09-22 Heruth Kenneth T Collecting sleep quality information via a medical device
US7881798B2 (en) 2004-03-16 2011-02-01 Medtronic Inc. Controlling therapy based on sleep quality
US20050209645A1 (en) * 2004-03-16 2005-09-22 Heruth Kenneth T Collecting posture information to evaluate therapy
US20050209644A1 (en) * 2004-03-16 2005-09-22 Heruth Kenneth T Collecting activity information to evaluate therapy
US7908013B2 (en) 2004-03-16 2011-03-15 Medtronic, Inc. Collecting activity information to evaluate therapy
US8725244B2 (en) 2004-03-16 2014-05-13 Medtronic, Inc. Determination of sleep quality for neurological disorders
US20050209512A1 (en) * 2004-03-16 2005-09-22 Heruth Kenneth T Detecting sleep
US9623248B2 (en) 2004-03-16 2017-04-18 Medtronic, Inc. Collecting sleep quality information via a medical device
US8758242B2 (en) 2004-03-16 2014-06-24 Medtronic, Inc. Collecting sleep quality information via a medical device
US8032224B2 (en) 2004-03-16 2011-10-04 Medtronic, Inc. Sensitivity analysis for selecting therapy parameter sets
US8190253B2 (en) 2004-03-16 2012-05-29 Medtronic, Inc. Collecting activity information to evaluate incontinence therapy
US8055348B2 (en) 2004-03-16 2011-11-08 Medtronic, Inc. Detecting sleep to evaluate therapy
US8396554B2 (en) 2004-03-16 2013-03-12 Medtronic, Inc. Collecting posture information to evaluate therapy
US8135473B2 (en) 2004-04-14 2012-03-13 Medtronic, Inc. Collecting posture and activity information to evaluate therapy
US20050245988A1 (en) * 2004-04-14 2005-11-03 Medtronic, Inc. Collecting posture and activity information to evaluate therapy
US8688221B2 (en) 2004-04-14 2014-04-01 Medtronic, Inc. Collecting posture and activity information to evaluate therapy
US8021299B2 (en) 2005-06-01 2011-09-20 Medtronic, Inc. Correlating a non-polysomnographic physiological parameter set with sleep states
US20070015976A1 (en) * 2005-06-01 2007-01-18 Medtronic, Inc. Correlating a non-polysomnographic physiological parameter set with sleep states
US8444578B2 (en) 2005-12-02 2013-05-21 Medtronic, Inc. Wearable ambulatory data recorder
US20070129769A1 (en) * 2005-12-02 2007-06-07 Medtronic, Inc. Wearable ambulatory data recorder
US20070129622A1 (en) * 2005-12-02 2007-06-07 Medtronic, Inc. Wearable ambulatory data recorder
US8016776B2 (en) 2005-12-02 2011-09-13 Medtronic, Inc. Wearable ambulatory data recorder
US8744587B2 (en) 2006-03-24 2014-06-03 Medtronic, Inc. Collecting gait information for evaluation and control of therapy
US9592379B2 (en) 2006-03-24 2017-03-14 Medtronic, Inc. Collecting gait information for evaluation and control of therapy
US20070250134A1 (en) * 2006-03-24 2007-10-25 Medtronic, Inc. Collecting gait information for evaluation and control of therapy
US9597032B2 (en) 2007-02-09 2017-03-21 Neuropace, Inc. Devices and methods for monitoring physiological information relating to sleep with an implantable device
US7894890B2 (en) 2007-02-09 2011-02-22 Neuropace, Inc. Devices and methods for monitoring physiological information relating to sleep with an implantable device
US9326724B2 (en) 2007-02-09 2016-05-03 Neuropace, Inc. Devices and methods for monitoring physiological information relating to sleep with an implantable device
US8068904B2 (en) 2007-02-09 2011-11-29 Neuropace, Inc. Devices and methods for monitoring physiological information relating to sleep with an implantable device
US20080195166A1 (en) * 2007-02-09 2008-08-14 Felice Sun Devices and methods for monitoring physiological information relating to sleep with an implantable device
US8903483B2 (en) 2007-02-09 2014-12-02 Neuropace, Inc. Devices and methods for monitoring physiological information relating to sleep with an implantable device
US20110112381A1 (en) * 2007-02-09 2011-05-12 Neuropace, Inc. Devices and methods for monitoring physiological information relating to sleep with an implantable device
US8538514B2 (en) 2007-02-09 2013-09-17 Neuropace, Inc. Devices and methods for monitoring physiological information relating to sleep with an implantable device
US8369940B2 (en) 2007-02-09 2013-02-05 Neuropace, Inc. Devices and methods for monitoring physiological information relating to sleep with an implantable device
US9743841B2 (en) * 2007-09-25 2017-08-29 Ric Investments, Llc Automated sleep phenotyping
US20090082639A1 (en) * 2007-09-25 2009-03-26 Pittman Stephen D Automated Sleep Phenotyping
US20090156908A1 (en) * 2007-12-14 2009-06-18 Transoma Medical, Inc. Deriving Patient Activity Information from Sensed Body Electrical Information
US8180442B2 (en) 2007-12-14 2012-05-15 Greatbatch Ltd. Deriving patient activity information from sensed body electrical information
US8447411B2 (en) 2008-07-11 2013-05-21 Medtronic, Inc. Patient interaction with posture-responsive therapy
US9560990B2 (en) 2008-07-11 2017-02-07 Medtronic, Inc. Obtaining baseline patient information
US8332041B2 (en) 2008-07-11 2012-12-11 Medtronic, Inc. Patient interaction with posture-responsive therapy
US8401666B2 (en) 2008-07-11 2013-03-19 Medtronic, Inc. Modification profiles for posture-responsive therapy
US8323218B2 (en) 2008-07-11 2012-12-04 Medtronic, Inc. Generation of proportional posture information over multiple time intervals
US8437861B2 (en) 2008-07-11 2013-05-07 Medtronic, Inc. Posture state redefinition based on posture data and therapy adjustments
US8326420B2 (en) 2008-07-11 2012-12-04 Medtronic, Inc. Associating therapy adjustments with posture states using stability timers
US8315710B2 (en) 2008-07-11 2012-11-20 Medtronic, Inc. Associating therapy adjustments with patient posture states
US9545518B2 (en) 2008-07-11 2017-01-17 Medtronic, Inc. Posture state classification for a medical device
US8282580B2 (en) 2008-07-11 2012-10-09 Medtronic, Inc. Data rejection for posture state analysis
US8504150B2 (en) 2008-07-11 2013-08-06 Medtronic, Inc. Associating therapy adjustments with posture states using a stability timer
US9440084B2 (en) 2008-07-11 2016-09-13 Medtronic, Inc. Programming posture responsive therapy
US8515550B2 (en) 2008-07-11 2013-08-20 Medtronic, Inc. Assignment of therapy parameter to multiple posture states
US8515549B2 (en) 2008-07-11 2013-08-20 Medtronic, Inc. Associating therapy adjustments with intended patient posture states
US9592387B2 (en) 2008-07-11 2017-03-14 Medtronic, Inc. Patient-defined posture states for posture responsive therapy
US8583252B2 (en) 2008-07-11 2013-11-12 Medtronic, Inc. Patient interaction with posture-responsive therapy
US9327129B2 (en) 2008-07-11 2016-05-03 Medtronic, Inc. Blended posture state classification and therapy delivery
US8644945B2 (en) 2008-07-11 2014-02-04 Medtronic, Inc. Patient interaction with posture-responsive therapy
US8249718B2 (en) 2008-07-11 2012-08-21 Medtronic, Inc. Programming posture state-responsive therapy with nominal therapy parameters
US8688225B2 (en) 2008-07-11 2014-04-01 Medtronic, Inc. Posture state detection using selectable system control parameters
US8708934B2 (en) 2008-07-11 2014-04-29 Medtronic, Inc. Reorientation of patient posture states for posture-responsive therapy
US8231556B2 (en) 2008-07-11 2012-07-31 Medtronic, Inc. Obtaining baseline patient information
US8219206B2 (en) 2008-07-11 2012-07-10 Medtronic, Inc. Dwell time adjustments for posture state-responsive therapy
US8751011B2 (en) 2008-07-11 2014-06-10 Medtronic, Inc. Defining therapy parameter values for posture states
US8755901B2 (en) 2008-07-11 2014-06-17 Medtronic, Inc. Patient assignment of therapy parameter to posture state
US8209028B2 (en) 2008-07-11 2012-06-26 Medtronic, Inc. Objectification of posture state-responsive therapy based on patient therapy adjustments
US8200340B2 (en) 2008-07-11 2012-06-12 Medtronic, Inc. Guided programming for posture-state responsive therapy
US9272091B2 (en) 2008-07-11 2016-03-01 Medtronic, Inc. Posture state display on medical device user interface
US9662045B2 (en) 2008-07-11 2017-05-30 Medtronic, Inc. Generation of sleep quality information based on posture state data
US8886302B2 (en) 2008-07-11 2014-11-11 Medtronic, Inc. Adjustment of posture-responsive therapy
US8150531B2 (en) 2008-07-11 2012-04-03 Medtronic, Inc. Associating therapy adjustments with patient posture states
US8905948B2 (en) 2008-07-11 2014-12-09 Medtronic, Inc. Generation of proportional posture information over multiple time intervals
US9050471B2 (en) 2008-07-11 2015-06-09 Medtronic, Inc. Posture state display on medical device user interface
US8958885B2 (en) 2008-07-11 2015-02-17 Medtronic, Inc. Posture state classification for a medical device
US9776008B2 (en) 2008-07-11 2017-10-03 Medtronic, Inc. Posture state responsive therapy delivery using dwell times
US8280517B2 (en) 2008-09-19 2012-10-02 Medtronic, Inc. Automatic validation techniques for validating operation of medical devices
US8364220B2 (en) 2008-09-25 2013-01-29 Covidien Lp Medical sensor and technique for using the same
US8257274B2 (en) 2008-09-25 2012-09-04 Nellcor Puritan Bennett Llc Medical sensor and technique for using the same
US20110257466A1 (en) * 2008-12-19 2011-10-20 Koninklijke Philips Electronics N.V. System and method for increasing the of relaxation of a person
US8515515B2 (en) 2009-03-25 2013-08-20 Covidien Lp Medical sensor with compressible light barrier and technique for using the same
US8781548B2 (en) 2009-03-31 2014-07-15 Covidien Lp Medical sensor with flexible components and technique for using the same
US9327070B2 (en) 2009-04-30 2016-05-03 Medtronic, Inc. Medical device therapy based on posture and timing
US8231555B2 (en) 2009-04-30 2012-07-31 Medtronic, Inc. Therapy system including multiple posture sensors
US20120296236A1 (en) * 2009-04-30 2012-11-22 Medtronic, Inc. Therapy system including multiple posture sensors
US9026223B2 (en) 2009-04-30 2015-05-05 Medtronic, Inc. Therapy system including multiple posture sensors
US9717846B2 (en) * 2009-04-30 2017-08-01 Medtronic, Inc. Therapy system including multiple posture sensors
US8175720B2 (en) 2009-04-30 2012-05-08 Medtronic, Inc. Posture-responsive therapy control based on patient input
US9149210B2 (en) 2010-01-08 2015-10-06 Medtronic, Inc. Automated calibration of posture state classification for a medical device
US8579834B2 (en) 2010-01-08 2013-11-12 Medtronic, Inc. Display of detected patient posture state
US8388555B2 (en) 2010-01-08 2013-03-05 Medtronic, Inc. Posture state classification for a medical device
US8758274B2 (en) 2010-01-08 2014-06-24 Medtronic, Inc. Automated adjustment of posture state definitions for a medical device
US9174055B2 (en) 2010-01-08 2015-11-03 Medtronic, Inc. Display of detected patient posture state
US9357949B2 (en) 2010-01-08 2016-06-07 Medtronic, Inc. User interface that displays medical therapy and posture data
US9566441B2 (en) 2010-04-30 2017-02-14 Medtronic, Inc. Detecting posture sensor signal shift or drift in medical devices
US9737719B2 (en) 2012-04-26 2017-08-22 Medtronic, Inc. Adjustment of therapy based on acceleration
US20150038804A1 (en) * 2013-07-30 2015-02-05 Magdy Younes Method, non-transitory computer readable medium and apparatus for arousal intensity scoring
US20150112155A1 (en) * 2013-10-23 2015-04-23 Quanttus, Inc. Sleep parameters
US9333351B2 (en) 2013-12-16 2016-05-10 Pacesetter, Inc. Neurostimulation method and system to treat apnea
US20150196766A1 (en) * 2014-01-15 2015-07-16 Pacesetter, Inc. Wireless closed-loop and system to detect and treat sleep apnea
US9498627B2 (en) * 2014-01-15 2016-11-22 Pacesetter, Inc. Wireless closed-loop and system to detect and treat sleep apnea

Also Published As

Publication number Publication date Type
US7717848B2 (en) 2010-05-18 grant
US9205264B2 (en) 2015-12-08 grant
US20100174155A1 (en) 2010-07-08 application
WO2005089649A1 (en) 2005-09-29 application
US20160158552A1 (en) 2016-06-09 application
US20050209513A1 (en) 2005-09-22 application
US9623248B2 (en) 2017-04-18 grant
US20140249605A1 (en) 2014-09-04 application
US20160263382A1 (en) 2016-09-15 application
US8758242B2 (en) 2014-06-24 grant

Similar Documents

Publication Publication Date Title
US6463328B1 (en) Adaptive brain stimulation method and system
US7591265B2 (en) Coordinated use of respiratory and cardiac therapies for sleep disordered breathing
US7155281B1 (en) Complimentary activity sensor network for disease monitoring and therapy modulation in an implantable device
US20100010432A1 (en) Associating therapy adjustments with patient posture states
US20050107838A1 (en) Subcutaneous cardiac rhythm management with disordered breathing detection and treatment
US20080114219A1 (en) Monitoring of chronobiological rhythms for disease and drug management using one or more implantable device
US20080195166A1 (en) Devices and methods for monitoring physiological information relating to sleep with an implantable device
US6066163A (en) Adaptive brain stimulation method and system
US7319899B2 (en) Sensing techniques for implantable medical devices
US20050080461A1 (en) System and method for moderating a therapy delivered during sleep using physiologic data acquired during non-sleep
US8209028B2 (en) Objectification of posture state-responsive therapy based on patient therapy adjustments
US20050113710A1 (en) Implantable device employing movement sensing for detecting sleep-related disorders
US7160252B2 (en) Method and apparatus for detecting respiratory disturbances
US7957809B2 (en) Closed-loop therapy adjustment
US20060195144A1 (en) System and method for regulating cardiopulmanary triggered therapy to the brain
US20110282416A1 (en) Systems for patient control of implantable medical device therapy
US7572225B2 (en) Sleep logbook
US7469697B2 (en) Feedback system and method for sleep disordered breathing therapy
US6641542B2 (en) Method and apparatus to detect and treat sleep respiratory events
US20080281376A1 (en) Therapy control using relative motion between sensors
US20100010572A1 (en) Adjustment of posture-responsive therapy
US20100010390A1 (en) Dwell time adjustments for posture state-responsive therapy
US20070260286A1 (en) System and method for utilizing brain state information to modulate cardiac therapy
US20060036294A1 (en) Patient compliance management device and method
US20070150026A1 (en) Closed-loop therapy adjustment

Legal Events

Date Code Title Description
AS Assignment

Owner name: MEDTRONIC, INC., MINNESOTA

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:HERUTH, KENNETH T.;MIESEL, KEITH A.;REEL/FRAME:018248/0362

Effective date: 20050512