EP3131459A1 - Method and system for muscle pain diagnosis - Google Patents
Method and system for muscle pain diagnosisInfo
- Publication number
- EP3131459A1 EP3131459A1 EP15780347.9A EP15780347A EP3131459A1 EP 3131459 A1 EP3131459 A1 EP 3131459A1 EP 15780347 A EP15780347 A EP 15780347A EP 3131459 A1 EP3131459 A1 EP 3131459A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- sensor
- stimulation
- pain
- muscle
- patient
- 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.)
- Withdrawn
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
- A61B5/4519—Muscles
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4824—Touch or pain perception evaluation
- A61B5/4827—Touch or pain perception evaluation assessing touch sensitivity, e.g. for evaluation of pain threshold
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4887—Locating particular structures in or on the body
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2562/00—Details of sensors; Constructional details of sensor housings or probes; Accessories for sensors
- A61B2562/02—Details of sensors specially adapted for in-vivo measurements
- A61B2562/028—Microscale sensors, e.g. electromechanical sensors [MEMS]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/1107—Measuring contraction of parts of the body, e.g. organ, muscle
Definitions
- the invention relates to systems and methods for identifying and evaluating muscle pain.
- TrP trigger point
- Palpation is often an unreliable means of identifying painful areas, and injections into painful spots within a muscle, identified through palpation without
- the system can comprise at least one stimulation source, at least one sensor, and processing circuitry.
- Each stimulation source can be configured to selectively apply a selected stimulation to the at least one selected muscle of the patient in accordance with a plurality of stimulation parameters.
- the plurality of stimulation parameters can comprise a magnitude, a phase, a waveform, and a frequency of the stimulation.
- Each stimulation parameter of the plurality of stimulation parameters can have a value that is selectively adjustable.
- the at least one sensor can be configured to detect at least one physiological signal within the at least one selected muscle of the patient.
- the processing circuitry can be in operative communication with the at least one stimulation source and the at least one sensor.
- the processing circuitry can be configured to determine a minimum stimulation magnitude for the selected stimulation of at least one stimulation source.
- the minimum stimulation magnitude can correspond to the lowest possible magnitude of the selected stimulation at which the at least one physiological signal detected by the at least one sensor is indicative of a contraction within the at least one selected muscle of the patient.
- Figure 1 is a schematic diagram illustrating various aspects of an exemplary pain evaluation system as disclosed herein;
- Figure 2 is a schematic diagram illustrating various aspects of an exemplary pain evaluation system as disclosed herein;
- Figure 3 is a circuit diagram illustrating an exemplary waveform generator and controller for use in a pain evaluation system as disclosed herein;
- Figure 4 is a circuit diagram illustrating an exemplary modulator circuit for the stimulus generator of a pain evaluation system as disclosed herein;
- Figure 5 is a circuit diagram illustrating an exemplary differential detecting component of a pain evaluation system as disclosed herein;
- Figure 6 is a schematic diagram illustrating an exemplary differential detecting component of a pain evaluation system as disclosed herein;
- Figure 7 is a circuit diagram illustrating an exemplary differential detecting component of a pain evaluation system as disclosed herein;
- Figure 8 illustrates an exemplary color-coded muscle pain status chart for use in the pain evaluation systems and methods as disclosed herein;
- Figure 9 is an exemplary evaluation chart for use in the pain evaluation systems and methods as disclosed herein;
- Figure 10 illustrates various aspects of an exemplary pain evaluation system as disclosed herein;
- Figure 11 illustrates various aspects of an exemplary pain evaluation system as disclosed herein;
- Figure 12 illustrates various aspects of an exemplary pain evaluation system as disclosed herein;
- Figure 13 illustrates various aspects of an exemplary pain evaluation system as disclosed herein;
- Figure 14 illustrates various aspects of an exemplary pain evaluation system as disclosed herein;
- Figure 15 illustrates various aspects of an exemplary pain evaluation system as disclosed herein;
- Figure 16 is a flowchart illustrating various aspects of an exemplary pain
- Figure 17 is a schematic diagram depicting an exemplary pain evaluation system as disclosed herein.
- Figure 18 is a perspective view of an exemplary self-contained pain evaluation device as disclosed herein.
- Figure 19 is a block diagram illustrating an exemplary operating environment for performing the disclosed pain detection methods.
- Figure 20 is a diagram showing the back muscles and thoracolumbar fascia of a subject.
- a system for evaluating pain within at least one selected muscle of a patient can comprise at least one stimulation source, at least one sensor, and processing circuitry.
- the at least one selected muscle can correspond to an area of pain complaint in the upper back, lower back, or thoracolumbar fascia of the patient; however, it is contemplated that the selected muscle can be positioned anywhere within the patient's body.
- each stimulation source of the at least one stimulation source can be configured to selectively apply a selected stimulation to the at least one selected muscle of the patient in accordance with a plurality of stimulation parameters.
- the plurality of stimulation parameters can comprise at least a magnitude, a phase, a waveform, and a frequency of the stimulation. It is contemplated that each stimulation parameter of the plurality of stimulation parameters can have a value that is selectively adjustable to produce a selected stimulation.
- the at least one stimulation source can comprise at least one of a stimulus pad and a stimulator head, such as, for example and without limitation, an aluminum stimulator head.
- the at least one sensor can be configured to detect at least one physiological signal within the at least one selected muscle of the patient.
- each sensor of the at least one sensor is selected from the group consisting of a miniature condenser, an omnidirectional microphone, a microelectromechanical system (MEMS) microphone, a MEMS accelerometer, and an adhesive contact electrical signal sensor pad, such as, for example and without limitation, an electrocardiogram (EKG) sensor pad.
- the at least one sensor can be configured to detect any physiological signal within the at least one selected muscle, such as, for example and without limitation, pressure waves, electrical signals, acoustic signals, acceleration, and the like associated with internal organic or inorganic processes.
- at least one stimulation source can be positioned anywhere along each selected muscle, from its origin to its insertion. In these aspects, it is contemplated that each selected muscle can be stimulated along its entire length from origin to insertion.
- the processing circuitry can be in operative communication with the at least one stimulation source and the at least one sensor.
- the processing circuitry can be configured to determine a minimum stimulation magnitude for the selected stimulation of at least one stimulation source. It is contemplated that the minimum stimulation magnitude can correspond to the lowest possible magnitude of the selected stimulation at which the at least one
- physiological signal detected by the at least one sensor is indicative of contraction within the at least one selected muscle of the patient. It is further contemplated that upon application of the selected stimulation at the minimum stimulation magnitude, the system and/or a clinician can determine whether the selected muscle is a source of pain.
- the at least one stimulation source can comprise at least one of an electrical signal generator and a mechanical force generator.
- the pain evaluation system can further comprise
- the at least one stimulation source and the at least one sensor can be positioned within the housing.
- the at least one stimulation source can comprise at least one external stimulation source provided separately from the at least one sensor.
- each sensor of the at least one sensor can be any sensor of the at least one sensor.
- the processing circuitry can be configured to receive the output from each sensor of the at least one sensor.
- the at least one stimulation source can comprise at least one electrical signal generator.
- the at least one electrical signal generator can be configured to apply an interferential electrical stimulus waveform to the at least one selected muscle of the patient.
- the interferential stimulus waveform can optionally comprise at least two electrical signals. It is contemplated that each electrical signal of the at least two electrical signals can have a frequency ranging from about 1 to about 3,000 Hz. In further exemplary aspects, each electrical signal of the at least two electrical signals can have corresponding waveform parameters.
- the waveform parameters can comprise at least amplitude, frequency, phase values, and amplitude modulation, and at least one of the waveform parameters of each electrical signal can be selectively adjustable.
- the waveform parameters can be selectively adjusted based on one or more of: the internal body process being targeted for identification; the specific muscle or muscle group of the patient being monitored; and the body type and composition of the patient, such as body fat percentage, residual muscle tension, and the like.
- the at least one electrical signal generator can comprise an electronic circuit.
- the electronic circuit can comprise at least two semiconductor transistors, and the at least two semiconductor transistors can be configured to multiply the at least two electrical signals into the interferential stimulus waveform.
- the at least one stimulation source can further comprise at least one electrode positioned in operative electrical communication with the at least one electrical signal generator.
- the at least one electrode can be configured to receive the interferential stimulus waveform from the electrical signal generator and apply the interferential stimulus waveform to the at least one selected muscle of the patient.
- the at least one stimulation source can comprise at least one electrical signal generator.
- the at least one electrical signal generator can comprise an electronic circuit that itself comprises at least two semiconductor transistors.
- the at least two semiconductor transistors can be configured to multiply at least two time-varying electrical signals into a composite interferential stimulus waveform, and the at least one electrical signal generator can be configured to apply the interferential stimulus waveform to the at least one selected muscle of the patient.
- the at least one stimulation source can further comprise at least one electrode positioned in operative electrical communication with the at least one electrical signal generator. In these aspects, the at least one electrode can be configured to receive the interferential stimulus waveform from the electrical signal generator and apply the interferential stimulus waveform to the at least one selected muscle of the patient.
- the electronic circuit of the at least one electronic signal generator can be configured to produce at least two pairs of interferential stimulus waveforms.
- the at least one stimulation source can be configured to deliver the interferential stimulus waveforms to the at least one selected muscle of the patient.
- at least one pair of interferential stimulus waveforms can be configured to be a reference channel that is compared to other stimulation sources of the at least one stimulation source.
- the at least one sensor can comprise a plurality of sensors.
- the plurality of sensors can cooperate with the processing circuitry to define a plurality of sensing channels and a plurality of processing channels, with each sensing channel being operatively connected to a corresponding processing channel.
- each sensing channel can comprise at least one sensor of the plurality of sensors.
- each respective processing channel of the plurality of processing channels can be configured to receive an output of each sensor of the at least one sensor of the corresponding sensing channel.
- the output of each sensor can be indicative of the at least one physiological signal detected by the at least one sensor of the corresponding sensing channel.
- the processing circuitry can comprise a high-common mode rejection ratio instrumentation amplifier positioned in operative communication with the at least one sensor.
- each sensor of the at least one sensor can be configured to produce an output indicative of the at least one physiological signal detected by the sensor, and wherein the instrumentation amplifier can be configured to receive the output from each sensor of the at least one sensor.
- the processing circuitry can further comprise at least one adaptive averaging circuit.
- the instrumentation amplifier can be configured to produce an output corresponding to the output received from each sensor of the at least one sensor.
- the at least one adaptive averaging circuit can be configured to receive each respective output of the instrumentation amplifier, and the at least one adaptive averaging circuit can be configured to isolate the at least one physiological signal from surrounding noise and thereby produce an isolated output signal.
- the at least one adaptive averaging circuit can be configured to compare the isolated output signal to a fixed voltage signal.
- the pain evaluation system can further comprise at least one display.
- the at least one adaptive averaging circuit can be positioned in operative communication with the processing circuitry, and the processing circuitry can be configured to produce a visual depiction of the comparison of the isolated output signal and the fixed voltage signal on the display.
- each adaptive averaging circuit can have corresponding signal processing parameters.
- the signal processing parameters can comprise at least a processing time period and an averaging time period. It is contemplated that at least one of the processing time period and the averaging time period can be selectively adjustable.
- the pain evaluation system can further comprise a database in operative communication with the processing circuitry.
- the database can comprise a plurality of signal processing parameter datasets, and the processing circuitry can be configured to adjust at least one of the processing time period and the averaging time period of each adaptive averaging circuit in accordance with a selected signal processing parameter dataset.
- the operator can selectively manually adjust at least one of the processing time period and the averaging time period of each adaptive averaging circuit.
- the pain evaluation system can further comprise a memory in operative communication with the processing circuitry.
- each sensor of the at least one sensor can be configured to produce an output indicative of the at least one physiological signal detected by the sensor, and the processing circuitry can be configured to receive the outputs of the at least one sensor and to produce a plurality of outputs.
- at least one output of the plurality of outputs can correspond to an output of the at least one sensor, and at least one output of the plurality of outputs can correspond to the minimum stimulation magnitude for a selected stimulation.
- the memory can be configured to receive the plurality of outputs from the processing circuitry for storage. In exemplary aspects, the memory can be configured to receive and store
- the system can further comprise a display positioned in operative communication with the processing circuitry.
- the at least one sensor and the display can be operatively secured to a housing.
- the display can be configured to visually depict at least one output of the plurality of outputs of the processing circuitry.
- the display can be integrated into or otherwise operatively coupled to a remote computing device that is in operative communication with the processing circuitry.
- the remote computing device can be selected from the group consisting of a smartphone, a tablet, and a computer, and the display can be operatively coupled to a host program and graphical user interface (GUI) stored within the remote computing device.
- GUI graphical user interface
- the display can be an LED display mounted within the same housing as the at least one sensor.
- the evaluation system can further comprise a system controller.
- the system controller can be operatively connected to the at least one stimulation source, the at least one sensor, and the processing circuitry.
- the system controller can be configured to effect selective adjustment of one or more parameters associated with at least one of the at least one stimulation source, the at least one sensor, and the processing circuitry.
- the system controller can be configured to maintain synchronization of the at least one stimulation source and the at least one sensor.
- the system can further comprise a remote computing device that is in operative communication with the at least one stimulation source and the system controller. In response to one or more inputs from a user, the remote computing device can be configured to effect selective adjustment of one or more control parameters associated with the operation of the at least one stimulation source.
- each sensor of the at least one sensor can be configured to produce an output indicative of the at least one physiological signal detected by the sensor.
- the processing circuitry can be configured to receive the outputs of the at least one sensor and to produce a plurality of outputs indicative of processing parameters of the processing circuitry.
- the system controller can be configured to evaluate the outputs produced by the at least one sensor and the processing circuitry to determine optimal parameters for at least one of the at least one stimulation source, the at least one sensor, and the processing circuitry.
- the system can further comprise a display in operative communication with the controller, and the controller can be configured to use the display to visually depict the optimal parameters.
- the controller can be configured to apply a selected stimulation to the at least one selected muscle using the optimal parameters. It is contemplated that the outputs of the at least one sensor upon application of the optimized signal can be monitored as previously described. It is further contemplated that the optimization and monitoring cycle can be continued as necessary to identify the desired parameters.
- the system controller can comprise software that is configured to permit retrieval of outputs produced by the at least one sensor as well as selective, remote adjustment of the parameters of the at least one sensor.
- the system controller can comprise software that is configured to permit retrieval of outputs produced by the at least one stimulation source as well as selective, remote adjustment of the parameters of the at least one stimulation source.
- the at least one stimulation source can comprise at least one electrode.
- the at least one electrode can comprise a first electrode spaced from a second electrode.
- the second electrode can optionally be configured to be positioned on the body of the patient at a location different than the location of the first electrode, and the second electrode can be configured to apply a reference stimulation signal to the at least one selected muscle of the patient.
- the optimization and monitoring procedure disclosed above with respect to the selected stimulation can be applied to a plurality of stimulations and sensor elements.
- the optimization and monitoring procedure can be applied to both a primary stimulation signal and a reference stimulation signal as disclosed herein.
- the pain evaluation system can further comprise a remote computing device and a medical records database.
- the medical records database can optionally contain historical pain data associated with the patient.
- the remote computing device can be positioned in operative communication with the medical records database, and the remote computing device can be configured to receive one or more inputs indicative of pain experienced by the patient upon application of a selected stimulation by the at least one stimulation source within the at least one selected muscle of the patient.
- the remote computing device can be configured to update the medical records database based upon the one or more inputs.
- each input of the one or more inputs received by the remote computing device can correspond to one of: no pain; persistent pain; and transient pain.
- the remote computing device can be configured to display the historical pain data associated with the patient prior to or during application of the selected stimulation by the at least one stimulation source.
- the remote computing device can be configured to display at least one of a muscle diagram of the body and diagrams for muscle evaluation and muscle treatment to guide a clinician, such as, for example, during and/or after stimulation of the patient.
- the remote computing device can be configured to selectively retrieve historical pain evaluation/treatment data associated with the patient from the medical records database.
- the medical records database can be accessible by a plurality of remote computing devices at a given time.
- the remote computing device can retrieve data from the medical records database in the form of printable reports, which can optionally be displayed by the remote computing device, stored in local memory, and/or delivered to a printer for printing.
- each muscle of the list of muscles and/or muscle depictions can be displayed in association with a selected color indicator.
- each selected color indicator can correspond to a respective muscle pain evaluation/treatment status, such as, for example and without limitation: no pain; persistent pain; transient pain; persistent pain less than three months after injection; and persistent pain more than three months after injection.
- the selected color indicator can be selectively adjustable by a clinician during stimulation of the patient.
- the at least one stimulation source, the at least one sensor, and the system controller can be provided as separate, individually-packaged units that are operatively connected using conventional wired or wireless connections.
- at least two of the at least one stimulation source, the at least one sensor, and the system controller can be provided together as an integral, and optionally portable, unit.
- the at least one stimulation source, the at least one sensor, and the system controller can be provided together as an integral, and optionally portable, unit.
- the processing circuitry disclosed herein can be configured to develop an algorithm for detecting stimulation of a selected muscle of a patient in accordance with pain stimulation data collected on a pool of patients.
- the processing circuitry can be configured to apply the algorithm to evaluate whether a selected muscle is likely a source of pain.
- aspects of the disclosed systems can be used in a variety of applications.
- aspects of the processing circuitry disclosed herein can be used in other medical applications, fiber optic communications, local area networking, wide area networking, wireless communications, and the like.
- the disclosed pain evaluation systems can be used to perform a method of evaluating pain within at least one selected muscle of a patient.
- the method can comprise using the disclosed system to determine the minimum stimulation magnitude for the selected stimulation of at least one stimulation source.
- the minimum stimulation magnitude can be zero when the stimulation occurs naturally within the body of the patient.
- the method can comprise selectively adjusting one or more of the stimulation parameters to produce the selected stimulation.
- the selective adjust can optionally be effected using a remote computing device.
- the method can comprise applying an interferential electrical stimulus waveform to the at least one selected muscle of the patient using at least one electrical signal generator as disclosed herein.
- the method can comprise applying a composite interferential stimulus waveform to the at least one selected muscle of the patient using at least one electrical signal generator as disclosed herein.
- the method can comprise applying at least two pairs of interferential stimulus waveforms to the at least one selected muscle of the patient using at least one electrical signal generator as disclosed herein.
- the method can comprise receiving the outputs of the at least one sensor using the processing circuitry.
- the method can comprise isolating the at least one physiological signal from surrounding noise to produce an isolated output signal using the processing circuitry as disclosed herein.
- the method can further comprise comparing the isolated output signal to a fixed voltage signal as disclosed herein.
- the method can further comprise producing a visual depiction of the comparison of the isolated output signal and the fixed voltage signal as disclosed herein.
- the method can further comprise using the processing circuitry to adjust at least one of the processing time period and the averaging time period of each adaptive averaging circuit of the processing circuitry in accordance with a selected signal processing parameter dataset from a database as disclosed herein.
- the method can further comprise storing the plurality of outputs from the processing circuitry in a memory.
- the method can further comprise visually depicting at least one output of the plurality of outputs of the processing circuitry on a display as disclosed herein.
- the method can comprise
- the method can comprise maintaining synchronization of the at least one stimulation source and the at least one sensor using the system controller as disclosed herein.
- the method can comprise using the system controller to evaluate the outputs produced by the at least one sensor and the processing circuitry to determine optimal parameters for at least one of the at least one stimulation source, the at least one sensor, and the processing circuitry.
- the method can further comprise visually depicting the optimal parameters using a display as disclosed herein.
- the method can further comprise applying the selected stimulation to the at least one selected muscle of the patient using the optimal parameters.
- the method can comprise applying a reference stimulation signal to the at least one selected muscle of the patient as disclosed herein.
- the method can comprise using the disclosed system to update the historical pain data associated with the patient within the medical records database based upon the presence of at least one of pain and discomfort experienced by the patient upon application of a selected stimulation by the at least one stimulation source.
- the method can comprise using a remote computing device to display at least one of a muscle diagram and a treatment diagram to guide a clinician before, during, or after stimulation of the patient.
- the method can comprise using the remote computing device to selectively adjust the evaluation/treatment status of pain within each muscle of the patient that is stimulated.
- the method can comprise using the remote computing device to selectively retrieve historical pain
- evaluation/treatment data associated with the patient from the medical records database.
- the disclosed pain evaluation system will be generally referred to below as a
- the PDMI device represents a multifaceted approach to the evaluation and treatment of functional muscle pain.
- the PMDI device is a departure from the prior art in that it automatically establishes the smallest strength of a stimulus needed to cause a muscle contraction; in contrast, prior art approaches estimate the proper strength of stimulus by observing a muscle twitch.
- the PMDI device also departs from the prior art in that it comprises embedded software that helps suggest to clinicians all of the muscles that could potentially be pain generators.
- the software is also configured to provide diagrams to direct the clinician on the proper placement of the instrument to stimulate a specific muscle(s) to determine if it is the source of pain rather than an adjacent muscle(s) that could mistakenly be considered.
- a point of tenderness on the skin may represent a number of muscles overlying each other. Unless tenderness is elicited along the course of a muscle, from beginning to end (origin to insertion), a clinician cannot accurately know if the suspected muscle is indeed a source of pain. As can be appreciated, this is important because muscle attachment sites as well as TrPs in a muscle, all function as pain generators.
- a specific muscle versus a trigger point is necessary to determine where a needle should be placed in the course of treatment. It is contemplated that moving a muscle replicates what occurs in vivo, in contrast to the community standard of identifying a muscle suspected of producing pain through palpation. It is further contemplated that tenderness to palpation in a resting muscle is not a good test for muscle pain because it does not replicate what occurs with most patients who have muscle -based pain (viz., pain with activity or prolonged positioning). It is still further contemplated that causing a minimal contraction is a more accurate replication of typical pain producing activity.
- a minimal contraction will provide a more valid indication of the muscle(s) causing pain versus pain caused by pressure, which could be a reflection of pain that is referred from another muscle or a confounded response based on palpation pressing on overlying muscles.
- the PMDI after the PMDI establishes the minimum stimulation magnitude, it can be configured to automatically shift to a diagnostic mode.
- the corresponding stimulus can be provided through a stimulation device (e.g., an aluminum stimulator head) along the course of a suspected muscle.
- a stimulation device e.g., an aluminum stimulator head
- One example is an area of pain complaint in the upper back (see FIG. 20, showing the Back Muscles and Thoracolumbar Fascia). Overlapping muscles and/or adjacent muscles can be the source of pain. Therefore, the PMDI is placed along the course of the muscle from the origin/insertion of each of the potentially suspect muscles and the muscle is stimulated along its entirety from origin to insertion.
- Non-limiting examples of muscles that can be tested using the disclosed systems and methods comprise:
- Rhomboids from the medial border of the scapula to the thoracic and lower cervical spines
- Levator scapula after palpating the origin on the superior medial angle of the scapula stimulating it up to the cervical spine
- Trapezius from the acromion to the upper thoracic and cervical spines and occiput.
- other muscles can be tested and evaluated using the disclosed systems and methods.
- the operator can record the results of the muscle testing in accordance with the methods disclosed herein, which can optionally comprise pressing appropriate buttons on the PMDI.
- the information can optionally be transmitted wirelessly to a remote computing device as disclosed herein.
- Results of the examination can be recorded on the medical records database, such as, for example and without limitation, an electronic medical records (EMR) database, and the results can be used for discussion with the patient or submitted for insurance billing. It is contemplated that, with knowledge of the specific muscle(s) causing pain with movement, a treatment plan can be provided.
- EMR electronic medical records
- the PMDI can shift to a treatment mode, either automatically (based on software) or manually (in response to an input from the operator).
- the PMDI can display a diagram and/or video of the selected muscle, along with directions showing the clinician how to insert the needle so as to thoroughly pierce the muscle attachments and tissue in accordance with the method disclosed in U.S. Patent No. 6,432,063, which is hereby incorporated herein by reference in its entirety.
- the muscle injected, the date of injection, and other paint/treatment data can be transmitted to the medical records database for future retrieval.
- the medical records database can be updated to provide a historical picture of the patient's pain/treatment progression. It is contemplated that when pain persists in the region where a specific muscle(s) were injected, it suggests that another un- injected muscle(s) is the source of the pain, in contrast to the conventional, community standard of trigger point injections, where injecting the same painful muscle (or areas) repeatedly is within the standard of care.
- the PMDI can automatically sense barely noticeable muscle contractions of the patient using the at least one sensor as disclosed herein.
- the PMDI can provide means for a clinician in practice, who may not have an excellent knowledge of muscle anatomy, to accurately identify and test muscles not ordinarily considered in the diagnosis and treatment of common pain syndromes.
- the patient when the muscle receives the selected stimulation at the automatically determined minimum stimulation magnitude to provide a contraction, the patient can have one of two responses: (1) No discomfort; or (2) Discomfort that is described as: (a) Bruise-like; (b) Black and Blue; (c) "It feels like you're pressing very hard”; or (d) Tender. If discomfort is produced, the application of the stimulus can continue. If the patient reports reduced and then absence of discomfort after about 30 seconds to about 1 minute, it can be recorded as
- the PMDI can provide the unique capability of identifying a muscle as a source of pain rather than possibly as a referred pain from another muscle producing the pain. It is further contemplated that palpation cannot make that distinction.
- the muscle can be wholly injected into muscle tissue, TrPs, and attachments. However, it is contemplated that partial injection can also be used.
- the PMDI can be selectively moved to a treatment mode.
- a muscle can be chosen from a list of stored identified muscles, and the selected muscle can be shown on a display. With the selected muscle shown on the display, suggested sites to pierce the muscle can be labeled and/or shown in a diagram or video.
- the muscle When the muscle is injected, it can be classified under the treatment module as "injected” for future reference.
- the pain/treatment status of the identified muscles can be dated and color coded to permit quick review of the patients' muscle status, with different colors corresponding to the following statuses: No pain; Transient Pain; Persistent pain; Persistent pain injected in past 3 months; or Persistent pain injected more than 3 months ago.
- Sensitized neurons will open up previously ineffective connections (nerve pathways) so that neurons receiving signals from other muscles in the body also become more sensitive normally a strong sensation in a muscle is necessary to cause the neuron representing that muscle in the spinal cord to depolarize (fire).
- CS a lesser stimulation will cause firing.
- muscle allodynia may occur in another muscle to which the stimulus is referred, producing referred muscle pain.
- the muscle with referred pain although tender to palpation, will often only be transiently tender to PMDI stimulation because the muscle fibers are not dysfunctional (only the neurons)
- DNIC presentation-diffuse noxious inhibitory control
- CPM conditioned pain modulation
- the methods and systems disclosed herein may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects.
- the methods and systems may take the form of a computer program product on a computer-readable storage medium having computer-readable program instructions (e.g., computer software) embodied in the storage medium. More particularly, the present methods and systems may take the form of web- implemented computer software. Any suitable computer-readable storage medium may be utilized including hard disks, CD-ROMs, optical storage devices, or magnetic storage devices.
- These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer- readable memory produce an article of manufacture including computer-readable instructions for implementing the function specified in the flowchart block or blocks.
- the computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions that execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks.
- blocks of the block diagrams and flowchart illustrations support combinations of means for performing the specified functions, combinations of steps for performing the specified functions and program instruction means for performing the specified functions. It will also be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, can be implemented by special purpose hardware-based computer systems that perform the specified functions or steps, or combinations of special purpose hardware and computer instructions.
- a unit can be software, hardware, or a combination of software and hardware.
- the units can comprise the pain diagnosis Software 106 as illustrated in FIG. 19 and described below.
- the units can comprise a computer 101 as illustrated in FIG. 19 and described below.
- the computer 101 can be a pain evaluation system as disclosed herein.
- the computer 101 can be a computing device connected to the pain evaluation system.
- FIG. 19 is a block diagram illustrating an exemplary operating environment for performing at least a portion of the disclosed methods.
- This exemplary operating environment is only an example of an operating environment and is not intended to suggest any limitation as to the scope of use or functionality of operating environment architecture. Neither should the operating environment be interpreted as having any dependency or requirement relating to any one or combination of components illustrated in the exemplary operating environment.
- Examples of well known computing systems, environments, and/or configurations that can be suitable for use with the systems and methods comprise, but are not limited to, personal computers, server computers, laptop devices, and multiprocessor systems. Additional examples comprise set top boxes,
- the processing of the disclosed methods and systems can be performed by software components.
- the disclosed systems and methods can be described in the general context of computer-executable instructions, such as program modules, being executed by one or more computers or other devices.
- program modules comprise computer code, routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types.
- the disclosed methods can also be practiced in grid-based and distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network.
- program modules can be located in both local and remote computer storage media including memory storage devices.
- the components of the computer 101 can comprise, but are not limited to, one or more processors or processing units 103, a system memory
- system bus 113 that couples various system components including the processor 103 to the system memory 112.
- the system can utilize parallel computing.
- the system bus 113 represents one or more of several possible types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures.
- bus architectures can comprise an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA) local bus, an Accelerated Graphics Port (AGP) bus, and a Peripheral Component Interconnects (PCI), a PCI-Express bus, a Personal Computer Memory Card Industry Association (PCMCIA), Universal Serial Bus (USB) and the like.
- ISA Industry Standard Architecture
- MCA Micro Channel Architecture
- EISA Enhanced ISA
- VESA Video Electronics Standards Association
- AGP Accelerated Graphics Port
- PCI Peripheral Component Interconnects
- PCI-Express PCI-Express
- PCMCIA Personal Computer Memory Card Industry Association
- USB Universal Serial Bus
- each of the subsystems including the processor 103, a mass storage device 104, an operating system 105, pain diagnosis/evaluation software 106, pain diagnosis/evaluation/treatment data 107, a network adapter 108, system memory 112, an Input/Output Interface 110, a display adapter 109, a display device 111, and a human machine interface 102, can be contained within one or more remote computing devices 114a,b,c at physically separate locations, connected through buses of this form, in effect implementing a fully distributed system.
- the computer 101 typically comprises a variety of computer readable media.
- Exemplary readable media can be any available media that is accessible by the computer 101 and comprises, for example and not meant to be limiting, both volatile and non-volatile media, removable and non-removable media.
- the system memory 112 comprises computer readable media in the form of volatile memory, such as random access memory (RAM), and/or non-volatile memory, such as read only memory (ROM).
- RAM random access memory
- ROM read only memory
- the system memory 112 typically contains data such as diagnosis and treatment data 107 and/or program modules such as operating system 105 and pain diagnosis software 106 that are immediately accessible to and/or are presently operated on by the processing unit 103.
- the computer 101 can also comprise other removable/non- removable, volatile/non-volatile computer storage media.
- FIG. 1 illustrates a mass storage device 104 which can provide non-volatile storage of computer code, computer readable instructions, data structures, program modules, and other data for the computer 101.
- a mass storage device 104 can be a hard disk, a removable magnetic disk, a removable optical disk, magnetic cassettes or other magnetic storage devices, flash memory cards, CD-ROM, digital versatile disks (DVD) or other optical storage, random access memories (RAM), read only memories (ROM), electrically erasable programmable read-only memory (EEPROM), and the like.
- any number of program modules can be stored on the mass storage device 104, including by way of example, an operating system 105 and pain diagnosis software 106.
- Each of the operating system 105 and pain diagnosis software 106 (or some combination thereof) can comprise elements of the programming and the pain diagnosis software 106.
- Diagnosis and treatment data 107 can also be stored on the mass storage device 104.
- Diagnosis and treatment data 107 can be stored in any of one or more databases known in the art. Examples of such databases comprise, DB2®, Microsoft® Access, Microsoft® SQL Server, Oracle®, mySQL, PostgreSQL, and the like. The databases can be centralized or distributed across multiple systems.
- the user can enter commands and information into the
- an input device comprises, but are not limited to, a keyboard, pointing device (e.g., a "mouse"), a microphone, a joystick, a scanner, tactile input devices such as gloves, and other body coverings, and the like
- a human machine interface 102 that is coupled to the system bus 113, but can be connected by other interface and bus structures, such as a parallel port, game port, an IEEE 1394 Port (also known as a Firewire port), a serial port, or a universal serial bus (USB).
- a display device 111 can also be connected to the system bus 113 via an interface, such as a display adapter 109. It is contemplated that the computer 101 can have more than one display adapter 109 and the computer 101 can have more than one display device 111.
- a display device can be a monitor, an LCD (Liquid Crystal Display), or a projector.
- other output peripheral devices can comprise components such as speakers (not shown) and a printer (not shown) which can be connected to the computer 101 via Input Output Interface 110. Any step and/or result of the methods can be output in any form to an output device. Such output can be any form of visual representation, including, but not limited to, textual, graphical, animation, audio, tactile, and the like.
- the computer 101 can operate in a networked environment using logical
- a remote computing device can be a personal computer, portable computer, a server, a router, a network computer, a peer device or other common network node, and so on.
- Logical connections between the computer 101 and a remote computing device 114a,b,c can be made via a local area network (LAN) and a general wide area network (WAN).
- LAN local area network
- WAN wide area network
- network adapter 108 can be implemented in both wired and wireless environments. Such networking environments are conventional and commonplace in offices, enterprise-wide computer networks, intranets, and the Internet 115.
- Computer readable media can comprise “computer storage media” and “communications media.”
- “Computer storage media” comprise volatile and non-volatile, removable and non-removable media implemented in any methods or technology for storage of information such as computer readable instructions, data structures, program modules, or other data.
- Exemplary computer storage media comprises, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer.
- the methods and systems can employ Artificial Intelligence techniques such as machine learning and iterative learning.
- Artificial Intelligence techniques such as machine learning and iterative learning.
- Such techniques include, but are not limited to, expert systems, case based reasoning, Bayesian networks, behavior based AI, neural networks, fuzzy systems, evolutionary computation (e.g. genetic algorithms), swarm intelligence (e.g. ant algorithms), and hybrid intelligent systems (e.g. Expert inference rules generated through a neural network or production rules from statistical learning).
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Abstract
Description
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US201461979728P | 2014-04-15 | 2014-04-15 | |
PCT/US2015/025987 WO2015160964A1 (en) | 2014-04-15 | 2015-04-15 | Method and system for muscle pain diagnosis |
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EP3131459A4 EP3131459A4 (en) | 2017-12-27 |
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GB2550854B (en) | 2016-05-25 | 2019-06-26 | Ge Aviat Systems Ltd | Aircraft time synchronization system |
KR102495358B1 (en) * | 2017-09-25 | 2023-02-02 | 삼성전자주식회사 | Neuromimetic stimulating apparatus and method thereof |
KR102003348B1 (en) * | 2017-12-21 | 2019-07-24 | (주)로임시스템 | Emg measuring band for optimizing electrode position |
CA3003155A1 (en) * | 2018-04-25 | 2019-10-25 | Dynamic Disc Designs Corp. | Sensitivity metering system for use in patient diagnosis |
EP4291083A1 (en) | 2021-02-12 | 2023-12-20 | Norman Marcus d/b/a Norman Marcus Pain Institute | Muscle and fascia pain identification by electrical stimulus |
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US5230344A (en) * | 1992-07-31 | 1993-07-27 | Intelligent Hearing Systems Corp. | Evoked potential processing system with spectral averaging, adaptive averaging, two dimensional filters, electrode configuration and method therefor |
US5324317A (en) * | 1992-09-30 | 1994-06-28 | Medserve Group, Inc. | Interferential stimulator for applying low frequency alternating current to the body |
US6529195B1 (en) * | 2000-09-08 | 2003-03-04 | James B. Eberlein | Pain migration tracking and display method |
US6538503B2 (en) * | 2001-02-22 | 2003-03-25 | Texas Instruments Incorporated | Instrumentation amplifier and method for obtaining high common mode rejection |
US7499746B2 (en) * | 2004-01-30 | 2009-03-03 | Encore Medical Asset Corporation | Automated adaptive muscle stimulation method and apparatus |
US20060129058A1 (en) * | 2004-12-13 | 2006-06-15 | Power Equine | Electromyogram for animals |
CA2601666A1 (en) * | 2005-03-18 | 2006-09-28 | The Trustees Of The Stevens Institute Of Technology | Apparatus for diagnosing muscular pain and method of using same |
US7894905B2 (en) * | 2006-03-13 | 2011-02-22 | Neuropace, Inc. | Implantable system enabling responsive therapy for pain |
CA2727498C (en) * | 2008-07-02 | 2020-04-21 | Niveus Medical, Inc. | Systems and methods for automated muscle stimulation |
CA2795045C (en) * | 2010-03-30 | 2022-07-05 | Julia Cole Finkel | Apparatus and method for human algometry |
FI125357B (en) * | 2010-10-11 | 2015-09-15 | Juno Medical Llc | Device for indication of physiological exertion level and recovery after exertion |
JP6243328B2 (en) * | 2011-05-13 | 2017-12-06 | サルーダ・メディカル・ピーティーワイ・リミテッド | Method and apparatus for controlling neural stimulation |
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- 2015-04-15 JP JP2017506622A patent/JP2017518845A/en active Pending
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