JPWO2020120425A5 - - Google Patents

Description

The present invention relates to systems and methods for sensing physiological parameters of a subject, particularly systems and methods suitable for continuous monitoring.

Human physiological parameters such as heart rate (HR), respiratory rate (RR) or arterial oxygen saturation ( _SpO2 ) serve as indicators of a person's current status and as strong predictors of serious medical events. . For this reason, physiological parameters are extensively monitored in inpatient and outpatient care settings, at home or in further health, leisure and fitness settings.

One method of measuring physiological parameters is plethysmography. Plethysmography generally refers to the measurement of volume changes in an organ or body part, and specifically refers to the detection of volume changes by cardiovascular pulse waves that travel through a subject's body with each heartbeat.

Photoplethysmography (PPG) is an optical measurement technique that evaluates temporal changes in light reflectance or transmittance of a region or space of interest. PPG is based on the principle that blood absorbs more light than surrounding tissue, so variations in blood volume from heartbeat to heartbeat affect transmission or reflectance accordingly.

Therefore, the PPG signal conveys heart rate information. In addition to information regarding heart rate, the PPG waveform can include information due to other physiological phenomena such as breathing. Blood oxygen saturation can be determined by evaluating transmittance and/or reflectance at various wavelengths (typically red and infrared). PPG signals may also be used to provide indicators of arrhythmias and other cardiac conditions.

However, electrocardiogram (ECG) measurements are the standard technique for diagnosing cardiac arrhythmias. However, continuous ECG monitoring over a long period of time until an arrhythmia is diagnosed is not always possible.

As an alternative, it is known that a combination of continuous PPG monitoring and spot measurements of the ECG can be used. In this solution, the PPG sensor can be embedded in a wearable device worn on the wrist, for example. An algorithm detects possible arrhythmia episodes based on the PPG signal and then alerts the patient to take ECG measurements that can be used for diagnosis. This warning can be given by the wearer, for example using vibrations, sound or light signals, or a combination thereof.

For the device to be effective, the user's response speed to alerts must be as high as possible. For example, to capture short-term arrhythmia episodes, it is important that the user responds, preferably quickly.

Known devices allow users to manually personalize alerts and operating modes depending on the environment and situation. For example, vibration signals are preferred for providing alerts when watching a movie. Warnings are likely to be missed, especially during sleep.

If the warning is set to be strong, the warning may be perceived as noticeable not only to the user but also perhaps to those around the user. For example, it may disrupt meetings or wake the user's spouse during the night.

US Patent Application Publication US2017/0258349 discloses a clock-based ECG monitoring system. Output notifications are provided when pulse wave monitoring is performed and the need for ECG measurements is determined. In particular, if an arrhythmia is detected based on pulse wave monitoring, a notification is provided to the user to perform an ECG measurement.

US Patent Application Publication US2017/0014037 discloses a system for detecting heart rate variability using a PPG sensor and then initiating instructions to a user to perform ECG measurements. The accelerometer is used to correct motion artifacts in the PPG signal.

US patent application publication US2010/0076331 discloses another clock-based ECG monitoring system. The user is reminded to take ECG measurements based on activity level and temperature changes.

Therefore, there is a need for a more reliable alert system, especially for alerts related to physiological measurements.

The invention is defined by the claims.

According to one aspect of the invention, a physiological parameter sensing system having a controller, the controller comprising:
receiving an activity signal from at least one activity monitor and a physiological signal from at least one first physiological parameter sensor;
analyzing the activity signal to determine a type and/or level of activity;
analyzing the physiological signal and determining when additional physiological parameter sensing is recommended ;
A system is provided that is configured to generate an alert signal in response to said determination for generating an alert with characteristics determined by said type and/or level of activity.

The system uses the signal from the first sensor to determine when further investigation is required . Although the first sensor is suitable for long-term continuous monitoring, including for example during sleep and exercise, further investigations may use sensing modalities that are more accurate but not suitable for continuous monitoring. may require sensing to be used. Further investigations aim to provide information of diagnostic relevance, for example.

The alert notifies the user that further investigation should be performed. However, the alert can be selected to take into account the user's current activities and be suitable to get the user's attention, but also not to disturb the user unduly.

The system may further include an input device for receiving user input in response to the generated alert, and the controller may provide a response between the generation of the alert and the user's received response to the generated alert. further configured to measure the time elapsed.

The timing information may be used to represent the effectiveness of the alert for that particular user. In this manner, the characteristics of the alert may be personalized to a particular user based on response to the alert. The controller has or controls a timer, for example, so that timing begins when an alert is generated and timing ends when a user response is received.

The input device has, for example, an element that allows a command to stop the warning. Therefore, response time is the time it takes for a user to perceive an alert and then provide a command to stop the alert. If the user knows to stop the alert as soon as it is perceived, this is a good measure of how effective the alert was.

The system includes, for example, a memory for storing a mapping between the type (i.e. category) and/or intensity of activity of a given type and the characteristics of the alert, such that the characteristics of the alert are determined. automatically selected based on the type and/or level of activity performed. The controller may then be adapted to update this mapping based on the response over time.

However, the system may include additional methods of changing the characteristics of the alert other than based on the timing of the user's response. For example, a user may otherwise personalize his or her alert settings by providing user input. A user may, for example, adjust the characteristics of different types of alerts differently. This user adjustability may be an alternative to allowing the user to manually configure the characteristics of the alert (depending on the activity type), which may be an alternative to automatic adjustment of the characteristics of the alert based on response over time. You can also combine them.

To this end, machine learning algorithms may be used to optimize the characteristics of the alert. This is based on a statistical analysis of user response times to various alert characteristics. Warnings should be as minimally intrusive as possible while still achieving the desired response speed.

The command to stop the alert may also be used to initiate further physiological parameter sensing if the additional sensing is part of the same overall system. Therefore, the user may be requested to perform further measurements as soon as the alert is perceived.

The characteristics of the warning are, for example:
the type of warning selected from at least vibration, sound and lighting; and/or the intensity and/or duration of the generated warning signal.

The intensity of an audio warning is the volume, the intensity of a vibration warning is the amount of vibration, and the intensity of an illumination warning is the intensity of light. Warnings can combine different types (eg vibration and sound) and different intensities. The frequency of the vibrations may be adjusted, the warning pulsed, and the timing controlled (eg, regularly or irregularly) to achieve the desired response. Different combinations of alert types and alert strengths can be combined based on activity information.

The first physiological parameter signal includes, for example, a photoplethysmography (PPG) signal. This may be used to at least obtain heart rate information, but may also allow arrhythmias to be detected. PPG sensing can be performed continuously during sleep and during activity. However, other wearable sensors such as accelerometers may be used for continuous cardiac information monitoring.

The controller is configured, for example, to analyze the physiological sensor signals to identify abnormal vital signs and thereby determine when additional physiological parameter sensing is recommended. Abnormal vital signs may be an arrhythmia such as atrial fibrillation.

The controller may e.g. configured to receive and analyze the signal. It is well known that acceleration information can be used to classify user activity.

The activity signal includes at least two different activity types selected from, for example, active, sitting, sleeping, running, walking, cycling, and sleeping in a particular sleep stage. Thus, at a general level, activity can be classified as active, sedentary (but awake), or sleeping. However, more detailed activities (running, walking, cycling, etc.) may be identified, and specific sleep stages (REM and non-REM, or specific sleep stages such as REM, N1, N2, N3) may be identified. May be identified.

The system may include various sensors. Therefore, the system further includes:
a first physiological parameter sensor, such as a PPG sensor, configured to provide a physiological signal when interacting with a patient;
The patient may have at least one of: an activity monitor that provides an activity signal when interacting with a patient; and an alert generation unit that generates an alert based on the alert signal.

The system may further include an ECG sensor, with additional physiological parameter sensing comprising ECG sensing. Therefore, the ECG sensor is ready for use by the user as soon as a warning is provided. It should be noted that since the problem to be investigated may be of short duration, it is considered important to perform ECG measurements as soon as the warning is provided. ECG sensors, for example, include electrodes for application to the skin to detect the electrical signals generated by a subject's heart each time it beats.

The invention also provides a method for generating an alert in response to sensing a physiological parameter, the method comprising:
monitoring a physiological parameter using a first physiological parameter sensor;
analyzing the physiological parameters to determine when additional physiological parameter sensing is recommended;
monitoring the user's activity to determine the type and/or level of the activity and, in response to the determination, generating an alert having characteristics determined by the type and/or level of the activity;
A method is provided.

The method may include receiving user input in response to the generated alert, and timing the user's response to the generated alert, the method including the steps of: , and the type and/or level of activity based on the timed response.

The first physiological parameter sensor is, for example, a PPG sensor, the analysis comprises identifying an arrhythmia (such as atrial fibrillation), and the additional physiological parameter sensing comprises ECG sensing.

The invention also provides a computer program product comprising a computer program code configured, when executed on a computer, to cause the computer to perform the method defined above.

Preferred embodiments of the invention will now be described in detail, by way of example only, with reference to the accompanying drawings, in which: FIG.

3 illustrates a physiological parameter sensing system. 3 illustrates a physiological parameter sensing method. 2 shows a general computer architecture for implementing the controller of the system of FIG. 1;

The detailed description and specific examples, while indicating illustrative embodiments of apparatus, systems, and methods, are for illustrative purposes only and are not intended to limit the scope of the invention. I hope you understand that there is no such thing. These and other features, aspects, and advantages of the devices, systems, and methods of the present invention will be better understood from the following description, appended claims, and accompanying drawings. It is to be understood that the drawings are only schematic and are not drawn to scale. It should also be understood that the same reference numbers are used throughout the drawings to indicate the same or similar parts.

The present invention provides a physiological parameter sensing system that receives (or includes) signals from a first physiological parameter sensor and an activity monitor. The first physiological parameter sensor signal is used to determine when additional physiological parameter sensing is recommended and then an alert is generated. Alerts have characteristics determined by the type and/or level of activity currently performed by the user. In this way, the warning can be selected to be perceived by the user but not annoying.

FIG. 1 shows an example of a physiological parameter sensing system 10. As shown in FIG. In this example, all relevant sensors are shown as part of the system. However, the invention can also be implemented solely by a controller that receives and processes signals from external sensors.

The first physiological parameter sensor 12 is for detecting abnormal vital signs of the user 14. Sensor 12 is typically a wearable sensor for continuous monitoring of physiological parameters, during the day and at night, and when the user is engaged in physical activity such as running or cycling or sports. It can also be used while The sensor is used to determine when additional physiological parameter sensing is recommended. This may be desirable because more accurate diagnosis is possible from different sensing modalities, but typically not suitable for continuous monitoring.

In a preferred example, the first physiological parameter sensor is a photoplethysmography (PPG) sensor. The sensor can be used to at least obtain heart rate information, but can further enable the detection of arrhythmias such as atrial fibrillation. The PPG sensor is, for example, a device worn on the wrist.

The invention can also be applied to other sensor examples. In all cases, the vital sign information obtained by the first physiological parameter sensor may not be the best possible sensing modality for making a diagnosis, and therefore when a more appropriate sensing modality should be used. used only to provide indicators (especially warnings) of For example, the first physiological parameter sensor can analyze cardiac performance based on motion detection rather than optical detection as used by PPG sensors. The PPG sensor may be a contact sensor or a remote sensor, for example using a camera.

A second physiological sensor 16 is used to perform additional physiological sensing.

In a preferred example, the second physiological parameter sensor is an ECG sensor. Therefore, the ECG sensor 16 is ready for use by the user as soon as a warning is provided. Since the problem to be investigated may be of short duration, it is considered important to perform electrocardiogram measurements as soon as a warning is provided.

ECG sensor 16 comprises, for example, electrodes applied to the skin to detect electrical signals generated by the subject's heart each time it beats. The ECG sensor may be part of a patch or chest strap.

The second physiological parameter sensor may instead be a non-worn sensor and may be an external device that is not integrated into the overall system. Alternatively, the user may need to apply a second physiological parameter sensor before taking further measurements. This may depend on the speed at which further measurements need to be taken. A fully integrated system as shown in Figure 1 provides a fully integrated method, allowing the second physiological parameter sensor to be activated as soon as an alert is received. .

In another example, the second physiological parameter sensor is a blood pressure monitor. Blood pressure (particularly blood pressure difference) can be obtained from the PPG signal, but not with very high accuracy. PPG-based measurements using a first physiological parameter sensor provide a warning to take more accurate blood pressure measurements using a blood pressure monitor such as a cuff (e.g., in patients on blood pressure medication or infants). May be used for pregnant women at risk of pre-symptoms).

The invention can also be applied to core body temperature measurements. For example, the first physiological parameter sensor may be a wrist-worn temperature sensor, which may provide some indication of core body temperature. This may be relevant for measuring fever and infection. After the warning has been issued, a thermometer could be used for more accurate measurements.

Alert generation unit 18 is used to alert the user of the need to perform additional physiological parameter sensing.

Alert generating unit 18 may use vibration, sound or lighting, or any combination thereof, to provide a signal that is perceived by the user. The generated alert has the characteristics of the alert, which means the type of alert (vibration, sound and lighting) and/or the intensity of the generated alert signal and/or the duration of the generated alert signal. The warning generating unit may have one type, such as vibration only, in which case the characteristics of the warning relate only to the nature of the generated vibrations.

In the illustrated example, the alert generation unit is shown as a wrist-worn device that provides vibrations and, optionally, also outputs a sound (although the sound may be generated by other parts of the system). . The alert may additionally or alternatively be generated by an external device under the command/control of the alert generating unit, such as the user's television, mobile phone or tablet.

The intensity of a sound warning is the volume, the intensity of a vibration warning is the magnitude of vibration, and the intensity of a lighting warning is the intensity of light. Warnings can combine different types (eg vibration and sound) and different intensities.

Although the alert generating unit 18 is shown separate from the sensors 12, 16, it will be appreciated that it may be integrated with one (or both) of the sensors.

The invention is based on controlling the alert generation unit 18 to generate alerts with characteristics determined by the type and/or level of activity currently performed by the user. For this purpose, the system has an activity monitor 20.

The activity monitor 20 comprises, for example, an accelerometer arrangement (of one or more accelerometers) for detecting movement of a subject. It is well known that acceleration information can be used to classify user activity.

Activity monitor 20 is, for example, for detecting at least two different activity types, so that different alerts can be generated from different activity types.

There may be a few different activity types, such as active, sitting (but awake), or sleeping.

However, activity types can also be classified more precisely, such as running, walking, cycling, dancing, etc.

There is only one activity type and the activities may be classified based on the intensity of the activity.

Sleep detection can also be divided into sleep stages. In particular, sleep can generally be classified into rapid eye movement (REM) sleep and non-rapid eye movement (non-REM) sleep. Non-REM sleep is further classified into N1 stage, N2 stage, and N3 stage sleep. N1 corresponds to a light sleep state and N3 corresponds to a deep sleep state. Non-REM stage N3 or stage N2 sleep can be slow wave (eg, deep) sleep. Determination of sleep stages is performed as reported in "Validation of Photoplethysmography-Based Sleep Staging Compared With Polysomnography in Healthy Middle-Agred Adults" by Fonseca P. et al. (Sleep, July 1, 2017, 40(7)). , which is based on PPG measurements.

Various control functions are realized by controller 22. Controller 22 has a processing unit 24 and memory 26.

Controller 22 analyzes signals from activity monitor 20 to determine the type and/or level of activity. The controller may further determine an activity intensity level for a particular activity.

The signal from the first physiological parameter sensor 12 is analyzed to determine when additional physiological parameter sensing is recommended, ie , when abnormal vital signs are detected .

A warning generator is then utilized to generate the most appropriate warning signal. In particular, the memory 26 stores a mapping between the type and/or level of activity and the characteristics of the alert such that the characteristics of the alert are automatically selected based on the determined activity type and/or level. Remember. The mapping may be an algorithm or a lookup table.

The overall system thus uses the first sensor 12 to determine when further investigation is required . Although the first sensor performs continuous monitoring over long periods of time, further investigations may require sensing using sensing modalities that are more accurate but may not be suitable for continuous monitoring.

The system of FIG. 1 further includes an input device 28 for receiving user input in response to the generated alert. As shown, it may be part of the alert generating unit 18, such as a push button.

Controller 22 times the user's response to the generated alert, ie, the time between the output of the alert and the user operating input device 28 . This timing information may be used to represent the effectiveness of the alert for that particular user and while they are involved in the particular type and/or level of detected activity. In this way, the characteristics of the alert may be personalized to a particular user based on their response to the alert.

This characterization may include updating the mapping stored in memory and, if not, learning by the algorithm used to implement the mapping based on activity type and response time. Optimal alert characteristics are determined, for example, based on training of the algorithm and/or subsequent learning during use of the system.

Machine learning can implement deep learning, where the available raw data is processed to determine when to trigger an alert .

The user may, for example, use input device 18 to stop the alert. Therefore, response time is the time it takes for a user to perceive an alert and then provide a command to stop the alert.

The command to stop the alert may also be used to initiate further physiological parameter sensing using the second physiological parameter sensor 16 (if the sensor is integrated into the entire system as in FIG. ). The user may therefore be required to perform further measurements as soon as the alert is perceived.

The user's response speed must be as high as possible to ensure that the second physiological parameter sensing is performed immediately if necessary. This makes it possible to detect short-term arrhythmia episodes.

The invention provides alert settings, e.g. different vibration characteristics of the vibration alert, which are configured to at least the current activity status of the user and optionally also to the user's characteristics. Typically, the intensity of the vibration alert is adjusted such that the alert is weaker when the person is seated and stronger when the person is active. Furthermore, to enable appropriate arousal during sleep, the alert may be adapted based on the detected sleep stage, as described above. Depending on the subject's health status, the warning can be ignored during sleep, which can be beneficial for the subject's overall health.

Deep sleep requires stronger alerts than light sleep. Additionally or alternatively, the rhythmic pattern of the alert may be adjusted, for example, to make it less regular when the person is active. The length of the warning may also be adjusted, e.g. longer bursts, or the non-response time may be adjusted e.g. to keep it on longer when the person is active. .

The response statistics needed to determine appropriate alert settings typically consist of average response time, optionally depending on the activity type, or number of non-responses, again optionally depending on the activity type.

If the subject reacts relatively slowly (on average) to the warning, the warning may become stronger, less regular, or longer. If a person responds quickly (on average) to warnings, the warnings may be reduced, made more regular, or made shorter.

Algorithms for detecting arrhythmia from PPG signals are well known, such as "Reliable PPG-based algorithm in atrial fibrillation detection" by Shan, SM et al. (2016. Biomedical Circuits & Systems), and "Atrial Fibrillation detection" by Bonomi, AG et al. Detection using Photo-plethysmography and Acceleration Data at the Wrist” (Computing in Cardiology 2016, vol. 43).

The above example is based on controlling alerts based on activity information. Other measured values can be taken into account as well. For example, an ambient light sensor can be used to detect darkness, which can indicate coverage of the warning device by clothing, for example. Therefore, vibration and/or sound may be preferred over light output. Similarly, if there is a lot of ambient noise detected by the microphone, vibration and/or light may be preferred over sound output.

For some activities, warning adaptation may be adjustable. For example, in some cases (e.g. set by the user) it may be possible that sleep is not disturbed (as described above) and as a result it may be determined that no warning is given; In other cases, it may be desired to wake the subject from sleep, and the characteristics of the alert are selected accordingly. In this way, there may be adjustment settings that may be enabled by the user and/or the physician.

In the above example, the activity monitor and the first physiological parameter sensor are different units. However, in some examples they may be the same unit. For example, a PPG sensor may be used to obtain activity information based on heart rate and breathing rate.

FIG. 2 illustrates a method for generating an alert in response to sensing a physiological parameter.

The method begins at step 30.

In parallel, the first physiological parameter sensor is used to continuously monitor the physiological parameter in step 32 and the user's activity is monitored in step 34.

At step 36, the user's activity is analyzed and the type and/or level of activity is determined. At step 38, the physiological parameters are analyzed to determine when additional physiological parameter sensing is recommended. If not, the method can return to the beginning, resulting in continuous PPG monitoring until abnormal vital signs are detected.

At step 40, the characteristics of the alert are determined by the controller, and these are determined by the type of activity and/or the intensity of the activity.

At step 42, a warning is generated.

This provides a way to take into account at least the user's activity type and/or level.

Optionally, there is further personalization, according to which user input is received at step 44 in response to the generated alert. This response triggers sensing using a second physiological parameter sensor (ie, an ECG sensor) in step 45, and the user's response to the generated alert is also timed by the controller. The method can automatically return to the start after the ECG measurement, or the user can restart the device (using the first physiological parameter sensor) into its monitoring mode.

The timing information is used by the controller to update the mapping between the characteristics of the alert and the type and/or level of activity, as indicated by the feedback step 46.

The invention is implemented at least in part in software by software operating a controller.

FIG. 3 shows an example of a computer 50 for implementing the controller described above. Computer 50 may include one or more processors 51, memory 52, and one or more I/O devices 53 communicatively coupled via a local interface (not shown). A local interface may be, for example, but not limited to, one or more buses or other wired or wireless connections, as is known in the art. Local interfaces may have additional elements such as controllers, buffers (caches), drivers, repeaters and receivers to enable communication. Furthermore, the local interface may include address, control, and/or data connections to enable appropriate communication between the aforementioned components.

Processor 51 is a hardware device for executing software that can be stored in memory 52 . Processor 51 may be virtually any custom-made or commercially available processor, central processing unit (CPU), digital signal processor (DSP), or auxiliary processor among several processors associated with computer 50. The processor 51 can be a semiconductor-based microprocessor (in the form of a microchip) or a microprocessor.

Memory 52 includes volatile memory devices (e.g., random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), etc.) and non-volatile memory devices (e.g., ROM, erasable programmable read-only memory, etc.). memory (EPROM), electronically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), tape, compact disk read-only memory (CD-ROM), disk, diskette, cartridge, cassette, etc.) It may include one or a combination. Additionally, memory 52 may incorporate electronic, magnetic, optical and/or other types of storage media. Note that memory 52 may have a distributed architecture, with various components located remotely from each other but accessible by processor 51.

The software within memory 52 may include one or more separate programs, each program containing an ordered list of executable instructions to implement a logical function. Software within memory 52 includes a suitable operating system (O/S) 54, compiler 55, source code 56, and one or more applications 57, according to an embodiment.

Application 57 comprises a number of functional components such as computational units, logic circuits, functional units, processes, operations, virtual entities and/or modules.

Operating system 54 controls the execution of computer program instructions and provides scheduling, input/output control, file and data management, memory management, and communication control and related services.

Application 57 may be a source program, executable program (object code), script, or any other entity that constitutes a set of instructions to be executed. In the case of source programs, the program is typically translated via a compiler (such as compiler 55), assembler, interpreter, etc., which are included in memory 52 for proper operation in conjunction with operating system 54. does not need to be included. Furthermore, the application 57 can be written as an object-oriented programming language with classes of data and methods, or a procedural programming language with routines, subroutines and/or functions, such as C, C++, C#, It includes Pascal, BASIC, API call, HTML, XHTML, XML, ASP script, JavaScript (registered trademark), FORTRAN, COBOL, Perl, Java (registered trademark), ADA, .NET, etc.

I/O devices 53 can include, but are not limited to, input devices such as a mouse, keyboard, scanner, microphone, camera, and the like. Further, the I/O device 53 may include, for example, but not limited to, an output device such as a printer or a display. Finally, I/O devices 53 include devices that communicate both input and output, such as network interface controllers (NICs) or modulators/demodulators (accessing remote devices, other files, devices, systems, or networks). may further include, but are not limited to, radio frequency (RF) or other transceivers, telephone interfaces, bridges, routers, etc. I/O device 53 also includes components for communicating over various networks, such as the Internet or an intranet.

When computer 50 is in operation, processor 51 is configured to execute software stored in memory 52, communicate data to and from memory 52, and generally control the operation of computer 50 in accordance with the software. . Applications 57 and operating system 54 are read in whole or in part by processor 51, perhaps buffered within processor 51, and then executed.

Note that when application 57 is implemented in software, application 57 can be stored on virtually any computer-readable medium for use by or in connection with any computer-related system or method. In the context of this specification, a computer-readable medium is an electronic, magnetic, optical or other physical device or device capable of containing or storing a computer program for use by or in connection with a computer-related system or method. It can be used as a means.

From reading the drawings, description, and appended claims, modifications to the disclosed embodiments can be understood and effected by those skilled in the art who practice the claimed invention. In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. Note that the term "adapted to" is intended to be equivalent to the term "configured to." Any reference signs in the claims shall not be construed as limiting the claim.

Claims (15)

A physiological parameter sensing system having a controller, the controller comprising:
receiving a physiological signal from at least one first physiological parameter sensor;
determining when additional physiological parameter sensing is recommended by analyzing the physiological signals and identifying abnormal vital signs;
receiving an activity signal from at least one activity monitor;
analyzing the activity signal to determine a type and/or level of activity;
in response to said determination, generating an alert signal for generating an alert with characteristics determined by said type and/or level of activity ; and
measuring the time elapsed between generation of the alert and receiving user input in response to the generated alert, used to represent the effectiveness of the alert to the user;
The system is configured as follows. The system of claim 1, further comprising an input device for receiving the user input . 3. A system according to claim 1 or 2, wherein the system stores a mapping between characteristics of alerts and types and/or levels of activity. 3. The system according to claim 2, wherein the system stores a mapping between characteristics of alerts and types and/or levels of activity, and the controller is configured to update the mapping based on the measured time. System described. The characteristics of said warning are:
5. A system according to any one of claims 1 to 4, having a type of warning selected from at least vibration, audio and/or lighting, and/or an intensity and/or duration of the generated warning. 6. A system according to any preceding claim, wherein the controller is configured to receive and analyze physiological signals comprising photoplethysmographic signals. 7. The system according to any one of claims 1 to 6 , wherein the abnormal vital sign is an arrhythmia . 8. A system according to any preceding claim, wherein the controller is configured to receive and analyze an activity signal comprising an accelerometer signal. 9. The activity signal has at least two different activity types selected from active, sitting, sleeping, running, walking, cycling and sleeping in a particular sleep stage. A system according to any one of the clauses. a first physiological parameter sensor configured to provide a physiological signal ;
The system according to any one of claims 1 to 9, further comprising at least one of: an activity monitor configured to provide an activity signal ; and an alert generation unit configured to generate an alert based on the alert signal. . 11. The system of claim 10, further comprising an electrocardiogram sensor, and wherein the additional physiological parameter sensing comprises electrocardiogram sensing. A method of operating a physiological parameter sensing system that generates an alert in response to sensing a physiological parameter, the physiological parameter sensing system having a controller;
the controller monitors a physiological parameter using a first physiological parameter sensor;
the controller determining when additional physiological parameter sensing is recommended by analyzing the physiological signals and identifying abnormal vital signs;
the controller monitoring the user's activity using an activity monitor to determine the type and/or level of activity;
the controller, in response to the determination , generating an alert with characteristics determined by the type and/or level of the activity;
the controller receiving user input responsive to the generated alert;
the controller measuring the time elapsed between generation of the alert and receiving user input in response to the generated alert, which is used to represent the effectiveness of the alert to a user;
How to have. 13. The method of claim 12, further comprising the step of the controller updating a mapping between characteristics of the alert and type and/or level of activity based on the measured time. the first physiological parameter sensor is a photoplethysmographic sensor, the analyzing comprises the controller identifying an arrhythmia, and the additional physiological parameter sensing comprises electrocardiogram sensing. , the method according to claim 12 or 13. 15. A computer program product comprising computer program code configured to cause said computer to perform a method according to any one of claims 12 to 14 when executed by said controller of a system according to claim 1. .