Determine the reliability of the monitored subject's vital signs

Abstract

Concepts for determining the reliability of a monitored subject's vital signs are presented. One such concept obtains activity data associated with a detected activity or posture of the monitored subject. Based on the activity data and physiological data associated with one or more physical or physiological attributes of the monitored subject, a measure of the reliability of the monitored subject's vital signs is determined.

Description

Technical Field

[0001] The present invention relates generally to monitoring subjects, such as humans or patients, and more particularly to determining the reliability of vital signs of a monitored subject. Background Art

[0002] Monitoring of a subject's health status or recovery following injury, hospitalization, and treatment is a major concern in most branches of medicine, including geriatrics, rehabilitation and physical therapy, neurology and orthopedics, nursing and elderly care.

[0003] US 2016 / 015308 A1 discloses an apparatus and method for monitoring vital signs of a subject.

[0004] US 2012 / 029300 A1 discloses systems and methods for reducing false alarms associated with vital signs monitoring.

[0005] Warning systems are typically used in low-emergency environments in hospitals or medical care facilities to provide alerts in the event of a subject's deterioration. Such warning systems are typically based on vital signs, like heart rate, respiratory rate, arterial oxygen saturation (SpO2), blood pressure, carbon dioxide, and temperature. Such vital signs are typically monitored by intermittent manual spot checks of the patient. These spot checks are performed at regular intervals, and their frequency depends on the severity of the patient and the number of staff.

[0006] A recent trend in patient monitoring systems is towards automatic and frequent (or even continuous) assessment of a subject's vital signs to improve the efficiency of early warning systems and to reduce caregiver workload.

[0007] A monitoring device comprising sensors that are continuously connected to the patient is able to perform unattended monitoring. Also, so that the subject is not restricted in his mobility (and can, for example, move around or walk around), wireless monitoring devices are generally preferred.

[0008] Such monitoring devices should deliver reliable and actionable information, thereby avoiding too many false and / or irrelevant alarms. However, physical activity, movement and / or posture changes of the monitored subject can cause metabolic and hemodynamic changes in the subject, which in turn can lead to changes in vital signs on the monitored subject. Measurements taken when the subject is in different states can therefore lead to inaccuracies in derived results (such as scores (e.g., early warning scores (EWS))) and automatically detected patient deterioration, as well as an increased number of irrelevant alarms. For example, because the subject has just climbed some stairs, the subject's heart rate may be elevated, and this may result in clinically meaningless alarms for high heart rates.

[0009] Therefore, changes in vital signs due to patient activity, movement and / or posture changes can result in false or incorrect alarms. It may therefore be desirable to develop concepts for reducing or preventing the generation of false alarms that might otherwise result from changes in vital signs due to physical activity, movement and / or posture changes of a monitored subject. Summary of the invention

[0010] The present invention is intended to at least partially meet the above needs. To this end, the present invention provides a system and a method as defined in the independent claims. The dependent claims provide advantageous embodiments.

[0011] A system for determining the reliability of vital signs of a monitored object is provided, wherein the measure of reliability is defined as the level of influence of current and / or recent activity on the vital signs, the system comprising: a signal interface, which is suitable for obtaining activity data related to the detected activity or posture of the monitored object; a data acquisition unit, which is suitable for obtaining physiological data related to one or more physical or physiological attributes of the monitored object; wherein the one or more physical or physiological attributes of the monitored object include at least one of the following: height; weight; age; gender; (one or more) existing diseases; relative size; aerobic profile; anaerobic power; strength; agility; body shape; recovery ability; and level of health; and a reliability unit, which is suitable for determining the measure of reliability of one or more vital signs of the monitored object based on the activity data and the physiological data.

[0012] Concepts for determining the reliability of a subject's vital signs based on the subject's physical activity or posture are presented. By using measurements of the subject's physical movement, activity, or posture and the subject's physiological characteristics, the impact of the movement, activity, or posture on one or more of the subject's vital signs can be evaluated or predicted. For example, by determining a measure (e.g., a reliability measure) of deviations in the subject's vital signs caused by physical exertion, embodiments can enable identification of when measurements of vital signs should be disregarded or adjusted. This provides an indication of how representative current vital signs are used for those vital signs when the subject has been at rest for a long time.

[0013] Embodiments may thus facilitate identification of changes in vital signs that are meaningful and represent potential changes in a person's physical or mental abilities that are distinct from changes caused by changes in the subject's physical activity and / or posture. This may help reduce the number of false alarms (i.e., inaccurate or incorrect monitoring decisions) and provide more accurate monitoring. Additionally, embodiments may be used for assessment purposes, such as to evaluate whether a subject shows significant changes in one or more vital signs.

[0014] For example, the proposed embodiments can be used to determine (or predict) when vital signs are not significantly disturbed by the subject's physical activity. It is therefore possible to identify when vital signs are considered reliable (e.g., when the monitored subject is at rest) and useful for monitoring the subject. In this way, a representative understanding of how current vital signs are with respect to the subject's resting state is provided by the embodiments.

[0015] The reliability of one or more vital signs can therefore be inferred using a single sensor (e.g., an accelerometer) worn or carried by the subject. This can help reduce the associated cost and / or complexity of the monitoring system. For example, embodiments can avoid the need for multiple sensors (and complex signal processing of their respective signals) and can simply employ a single-value (e.g., movement or posture) sensing arrangement.

[0016] An embodiment may be based on a proposal to determine the reliability or usefulness of a subject's vital sign measurements based on the subject's detected activity or posture. Additionally, a prediction may be made as to when the vital signs will cease to be significantly disturbed by previous physical activity (e.g., when the subject will be considered to be back in a resting state) and therefore identify when an alarm or warning system may be turned on again.

[0017] Embodiments may therefore be able to distinguish between changes in vital signs that represent actual changes in a person's physical health and other changes that may be the result of changes in a person's physical activity and / or posture.

[0018] Improved (e.g., more accurate) monitoring of a subject's health or well-being may thus be facilitated by using information related to the subject's physical activity or posture. Embodiments may also be used to infer trends based on changes in a subject's detected activity or posture, thereby enabling predictions of when measured vital signs will be reliable (e.g., when a subject will return to a resting state).

[0019] The proposed embodiment may therefore have particular relevance to patient monitoring, since, for example, it may aid in the interpretation of changes in a patient's vital signs over time. The proposed concept may also facilitate accurately signaling improvements or deteriorations in the health status of a monitored but moving subject.

[0020] The measure of reliability comprises the duration of the recovery time required for the monitored subject to return to a resting state. In some proposed embodiments, the measure of reliability may comprise a measure of the deviation of the monitored subject's vital signs from a resting value or range for the monitored subject in the resting state. The measure of deviation may, for example, represent the absolute difference between a current value of a vital sign and a resting state value of the vital sign. The measure of reliability may thus represent the level of impact of (current and / or recent) activity on a vital sign, and the measure may even be quantified at a unitless level.

[0021] Thus, the proposed concept can enable an assessment of whether a subject's vital signs (such as heart rate, respiratory rate, blood pressure, etc.) are reliable for use in an early warning system. In this way, embodiments can avoid false alarms that would otherwise be generated due to changes in vital signs caused by the physical activity of the monitored subject.

[0022] In the proposed embodiment, the reliability unit may be adapted to determine the resting state of the monitored subject based on the physiological data. This may provide the advantage that specific properties of the subject can be used to accurately determine the effect or influence that activity has on the subject's vital signs. It may also enable a more accurate determination of when the monitored subject may be in a resting state and therefore when vital signs may be reliable and useful for monitoring purposes.

[0023] In some embodiments, the signal interface may be further adapted to obtain vital sign data associated with detected values ​​of the vital signs of the monitored object. Additionally, the system may further comprise a prediction unit adapted to determine predicted values ​​of the vital signs of the monitored object at rest based on the vital sign data and the measure of reliability of the vital signs of the monitored object. For example, by considering the current values ​​of the vital signs and their reliability (e.g. deviations from normal / expected values ​​for the object caused by physical activity or posture), it may be possible to predict or infer when the object may be considered to have returned to a resting state. This in turn may facilitate prediction or identification of when measuring the vital signs of the object will be useful for monitoring purposes (and not excessively altered by changes in the subject's activity or posture).

[0024] The reliability unit may be adapted to: compare the value of the physiological data with one or more thresholds to obtain a comparison result; generate a characterization value based on the physiological data; and determine a measure of the reliability of the vital sign of the monitored object based on the comparison result and the characterization value. Simple mathematical functions may therefore be employed, resulting in a simple and reduced complexity implementation.

[0025] The proposed embodiment may further comprise a historical data interface adapted to obtain historical data relating to previous activities or postures of the monitored subject. The reliability unit may then be adapted to determine a measure of reliability of the monitored subject's vital signs also based on the historical data. Taking into account previously obtained information may improve the accuracy of the determination or evaluation, for example, via a comparison and / or improvement of the obtained measure of reliability based on the historical data.

[0026] The reliability unit may be adapted to obtain a historical measure of reliability of the monitored subject's vital signs, the historical measure of reliability having been previously determined for previously detected activities or postures of the monitored subject. The reliability unit may then be adapted to determine a trend in the reliability of the monitored subject's vital signs based on the determined measure of reliability and the historical measure of reliability. This may provide the advantage that a more accurate determination / assessment may be made. It may also cater for unique characteristics or properties associated with the monitored subject.

[0027] Embodiments may further include a sensor adapted to detect a value of the activity or posture of the monitored object and to generate a signal comprising activity data representative of the detected value. Preferably, the sensor may include at least one of: an accelerometer; a gyroscope; a movement sensor; a weight sensor; a pressure sensor; and a timing device. Additionally, the sensor may be adapted to be coupled to a person or an object.

[0028] For example, there are many sensors that can be employed by the system according to the embodiment. Typical sensors include PIR (passive infrared; measuring movement and presence), OC (open-closed; measuring the state of doors, especially front doors, windows and cabinets, including refrigerators), and pressure sensors or mats (measuring occupancy of users sitting on chairs, lying in bed, standing on doormats in front of the front door, in the bathroom, etc.). Many other sensors exist and can be imagined, such as sensors for indicating the switch state of indicators, etc. Another series of sensors are those based on physical quantities, such as accelerometers, magnetometers, gyroscopes and air pressure sensors. For example, accelerometers can also measure the rate or speed of movement of people or objects moved by people. Another series of sensors include microphones and cameras (including infrared, even UV and other parts of the spectrum), GPS and location sensitive IR also belong to these. Ultrasonic or RF-based sensors (including RFID tags) provide additional inputs. Appliances with their own IP addresses (called the Internet of Things) provide additional sensor input signals that can be used by smart home systems.

[0029] Although the sensor(s) may be mounted in a monitored environment (e.g., a person's home), they may also be attached to a user device (e.g., a key ring) or placed into clothing, a pocket, or a bag, or as an insole or underwear, etc. They may also be made to be worn explicitly like a wristwatch or pendant. By way of further example, some embodiments may employ sensors adapted to be coupled to a person or object.

[0030] The activity data relating to detected activity or posture of the monitored object may include a value of at least one of: the speed of movement of the object; a measure of the force applied by the object to an object; a distance traveled by a part of the object; the rate of acceleration of a part of the object; a measure of the posture of the object.

[0031] Additionally, the sensor may communicate its output signal to an interface of an embodiment via a wired or wireless connection or a combination thereof. Accordingly, in an embodiment, the sensor may be adapted to be coupled to a person or an object.

[0032] Embodiments may thus be implemented with pre-existing, pre-installed or otherwise separately provided presence or activity sensors, and output signals from such sensors may be received and processed according to the proposed concepts. Other embodiments may be provided with sensors (e.g. where appropriate sensors are not available).

[0033] The sensor may also be adapted to perform preliminary processing of the detected values, such as signal filtering, sampling, conditioning, etc., in order to, for example, reduce the required transmission bandwidth and / or transmission duration. Alternatively, the sensor may send raw data.

[0034] The sensor arrangement / system may be positioned in strategic locations so that it detects appropriate values ​​without the need for a person to intentionally or consciously activate / operate the sensor. In this way, the person may only need to carry out their own normal activities. Such strategic positioning may ensure that the value of the property of the person or object can be automatically and accurately obtained, and this may not require the person to remember to perform any special or additional activities in order for the value to be detected by the sensor. For example, this may remove the risk of a person forgetting to activate the sensor (e.g., by pressing a button).

[0035] Thus, non-invasive monitoring can be achieved using relatively simple sensors that provide data about specific properties / parameters of an object or a property of a person, such as movement, weight, speed, and / or distance traveled. Such sensors for measuring an object's activity or posture can be simple, small, and / or inexpensive.

[0036] Thus, the monitoring system of the present invention may employ conventional sensors and / or existing sensor arrangements. Moreover, embodiments may employ sensors that are considered non-invasive and more easily accepted by the person being monitored. Moreover, using the data provided by these sensors, the reliability or usefulness of changes in the subject's vital signs may be determined and provide information about the person being monitored.

[0037] Such sensors may be employed by or in conjunction with embodiments to increase the number and / or accuracy of activities and / or gestures monitored. They may also be used to confirm or qualify readings obtained by primary sensors so as to avoid false or unintentional measurements. For example, signals from position sensors worn by a monitored person may be used to confirm whether movement readings obtained by a movement sensing system are indeed attributed to the monitored object.

[0038] Embodiments may also be adapted to store the data in a database adapted to store historical data associated with one or more previously obtained activity data and / or determined measures of reliability. Previously obtained data and / or determined values ​​may thus, for example, be stored in a historical database and then used in subsequent calculations. Furthermore, currently determined values ​​may be used to recalculate or improve previously determined trends, forecasts or estimates.

[0039] It will be appreciated that all or part of the proposed system may comprise one or more data processing units. For example, the system may be implemented using a single processor suitable for performing data processing in order to determine the reliability of the vital signs of the monitored subject.

[0040] The system for determining the reliability of the vital signs of the monitored subject may be located remotely from the activity / posture sensor(s), and signals representing the detected values ​​may be communicated to the system unit via the communication link.

[0041] The system may include: a server device including a signal interface, a data acquisition unit and a reliability unit; and a client device including (one or more) sensors. Dedicated data processing devices may thus be used for the purpose of determining the reliability of the vital signs of the monitored subject, thereby reducing the processing requirements or capabilities of other components or devices of the system.

[0042] The system may also include a client device, wherein the client device includes a signal interface, a data acquisition unit, and a reliability unit and a display system. In other words, a user (such as a caregiver) may have a suitably arranged client device (such as a laptop, tablet computer, mobile phone, PDA, etc.) that processes the received activity data and physiological data in order to determine the reliability of the vital signs of the monitored subject.

[0043] Thus, processing may be hosted at a different location than where activity / gesture sensing occurs. For example, for power efficiency reasons (e.g., to improve battery life), it may be advantageous to perform only a portion of the processing at the sensor location, thereby reducing associated costs, processing power, transmission requirements, etc.

[0044] It will therefore be appreciated that processing capabilities may be distributed throughout the system in different manners depending upon predetermined constraints and / or availability of processing resources.

[0045] Embodiments may also enable some processing loads to be distributed throughout the system. For example, preprocessing may be performed at an active sensor system. Alternatively or additionally, processing may be performed at a communication gateway. In some embodiments, processing may be performed at a remote gateway or server, thereby relinquishing processing requirements from an end user or output device. Such distribution of processing and / or hardware may allow for improved maintenance capabilities (e.g., by centralizing complex or expensive hardware in preferred locations). It may also enable computational loads and / or traffic to be designed or located within a networked system based on available processing power. A preferred approach may be to process sensor signals locally and transmit the extracted data for full processing at a remote server.

[0046] The one or more physical or physiological attributes of the monitored subject may include at least one of: height; weight; age; gender; (one or more) existing diseases; anaerobic power; strength; body shape; relative size; aerobic profile; agility; recovery ability; and level of fitness. Any suitable physical or physiological properties, attributes, characteristics, or characteristics of the subject that may affect the amount that the subject's activity or posture affects his / her vital signs may therefore be considered. Embodiments may also consider factors that may affect such attributes, such as prescribed medications, diet, nutritional supplements, sleep patterns, or injuries.

[0047] The value of the object's physical or physiological attribute can be objective, and therefore simply measured or determined / detected using appropriate technology / methods, however, some physiological attributes (such as recovery capacity; and the level of health) can be estimated. Such physical or physiological attributes can be estimated by a user (such as an object, a caregiver, or a family member) and provided as user input, and / or they can be learned / inferred from activity data in combination with vital sign measurements. Combinations are also possible, for example, the level of recovery capacity / health can be first estimated by the user, provided via user input, and then the embodiment can subsequently adapt these in response to the vital signs of the object caused by the activity. If not provided as user input, default values ​​for physical or physiological attributes can be used, and these can be calculated based on the known physical or physiological attributes of the object (such as height, weight, age and / or gender). This can achieve a customized or personalized evaluation of the reliability of the vital signs of the monitored object. More accurate results can therefore be provided by the proposed embodiment.

[0048] It should be understood that references to vital signs are considered different from references to physical or physiological attributes, and also different from detected activities or postures. Such a distinction can be explained on the premise that vital signs (often abbreviated as just signs) are generally known to be a set of the most important signs indicating the status of the body's important (life-sustaining) functions. Measurements of vital signs are obtained to assess a person's overall physical health, give clues to possible diseases, and show progress towards recovery. The normal or expected range of a subject's vital signs varies with physical or physiological attributes, such as age; gender; (one or more) existing diseases; anaerobic power; strength; body shape; relative size; aerobic profile; agility; recovery ability; and level of health. There are four main vital signs: body temperature, blood pressure, pulse (heart rate) and respiratory rate (respiratory rate), often expressed as BT, BP, HR and RR. However, depending on the clinical environment, vital signs may include other measurements referred to as the "fifth vital sign" or "sixth vital sign".

[0049] The detected activity may include any of: speed (e.g., translation and / or rotation) or rate of movement of a part of the subject; a measure of a force (or its derivative) applied by the subject to an object (such as magnitude, rate of change / rate of change, average, etc.); a distance traveled by a body part of the subject; a rate of acceleration of a body part of the subject; and a measure of the subject's posture. By detecting values ​​of the subject's activity or posture, changes in the detected values ​​over time can be identified, and based on such changes, a measure of the reliability of the subject's vital signs can be inferred and monitored.

[0050] The reliability unit may be further adapted to generate an output signal based on a measure of the determined reliability of the vital sign of the monitored subject. Embodiments may be adapted to provide the output signal to at least one of: the subject; a medical practitioner; and a caregiver. The output signal may thus be provided to a user or a monitoring system, for example for the purpose of indicating whether the measured vital sign should be disregarded or ignored.

[0051] Embodiments may further comprise a user input interface adapted to receive user input for defining or modifying activity data and / or physiological data.

[0052] The reliability unit may also be adapted to generate a control signal for modifying a graphical element based on a measure of the determined reliability of the object's vital signs. In addition, the system may further include a display system adapted to display the graphical element according to the control signal generated by the reliability unit. In this way, a user (such as a caregiver) may have a suitably arranged display system that is capable of receiving and displaying information about the reliability of the monitored object's vital signs, and the user may be positioned away from the object. Embodiments may therefore enable a user to remotely monitor an object (e.g., a patient) using a portable display device (such as a laptop computer, a tablet computer, a mobile phone, a PDA, etc.).

[0053] According to another aspect of the present invention, a system for monitoring the vital signs of an object is provided, the system comprising: an input interface suitable for obtaining vital sign data related to one or more detected vital signs of the object; a sensor arrangement suitable for detecting values ​​of activities or postures of the monitored object and generating activity data representing the detected values; a system for determining the reliability of the vital signs of the monitored object according to the proposed embodiment; and a processing unit suitable for processing the vital sign data based on the determined reliability of the vital signs of the monitored object.

[0054] The processing performed by the processing unit may include at least one of: preventing an alarm from being activated; postponing the collection of additional vital sign data associated with the detected vital signs of the subject; preventing the vital sign data associated with one or more detected vital signs of the subject from being provided to a warning system; and determining a value of a physical or physiological attribute of the subject based on the vital sign data and the determined reliability of one or more vital signs of the monitored subject. For the latter, vital sign measurements are continued even during periods of low reliability. In this way, the obtained vital signs can be used to determine physical or physiological attributes (e.g., level of health, recovery ability, etc.), or, in other words, to learn the response of the subject's vital signs to activity. Even when it is determined that the vital signs do not represent the resting state of the subject (and should therefore be ignored for purposes of, for example, providing an early warning), embodiments can therefore still utilize the measured vital signs (e.g., learn from the measured vital signs).

[0055] According to another aspect of the present invention, a method for determining the reliability of vital signs of a monitored object is provided, the method comprising: obtaining activity data related to a detected activity or posture of the monitored object; obtaining physiological data related to one or more physical or physiological attributes of the monitored object; and determining a measure of the reliability of the vital signs of the monitored object based on the activity data and the physiological data.

[0056] According to another aspect of the present invention, a method for monitoring the vital signs of an object is provided, the method comprising: obtaining vital sign data related to one or more detected vital signs of the object; detecting values ​​of activities or postures of the monitored object and generating activity data representing the detected values; determining the reliability of the vital signs of the monitored object according to a proposed embodiment; and processing the vital sign data based on the determined reliability of the vital signs of the monitored object.

[0057] According to yet another aspect of the present invention, a computer program product for determining the reliability of vital signs of a monitored object is provided, wherein the computer program product comprises a computer-readable storage medium having a computer-readable program code embodied therein, and the computer-readable program code is configured to execute all the steps of the embodiment.

[0058] A computer system may be provided, comprising: a computer program product according to an embodiment; and one or more processors adapted to perform a method according to an embodiment by executing the computer readable program code of the computer program product.

[0059] In a further aspect, the present invention relates to a computer-readable non-transitory storage medium comprising instructions which, when executed by a processing device, perform the steps of the method of controlling a monitoring system display unit according to an embodiment.

[0060] These and other aspects of the invention will be apparent from and elucidated with reference to the embodiment(s) described hereinafter. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Examples of aspects of the present invention will now be described in detail with reference to the accompanying drawings, in which:

[0062] Figure 1 is a simplified block diagram of a system for monitoring an object according to an embodiment;

[0063] Figure 2 is a flow chart of an activity history calculation method that may be employed by an embodiment;

[0064] Figure 3A-3B a graph illustrating the effect of different values ​​of the time constant of the exponential decay, wherein the change in the intensity of the subject's activity over time is plotted as a solid line and the subject's activity history index (Mh) is plotted as a dashed line;

[0065] Figure 4A-4B is a graph illustrating the effect of such a simple algorithm on subject data assuming different personal trends of vital signs as described by the coefficient gamma of the model, wherein the subject's activity intensity over time is plotted as a solid line and the subject's activity history index (Mh) is plotted as a dashed line;

[0066] Figure 5 is a simplified block diagram of a system for monitoring an object according to another embodiment; and

[0067] Figure 6 is a simplified block diagram of a computer within which one or more portions of the embodiments may be employed. DETAILED DESCRIPTION

[0068] Concepts for determining the reliability of vital signs in outpatient subjects are proposed, which can, for example, help improve health deterioration assessment and monitoring. For example, such subjects can include disabled people, elderly people, injured people, medical patients, etc. For example, elderly people can mean people over 50 years old, over 65 years old, over 70 years old, over 80 years old.

[0069] The illustrative embodiments can be utilized in many different types of monitoring environments, such as hospitals, wards, nursing homes, people's homes, etc. In order to provide a context for describing the elements and functions of the illustrative embodiments, the following figures are provided as examples of how aspects of the illustrative embodiments can be implemented. Therefore, it should be appreciated that the figures are merely examples and are not intended to state or imply any limitations on the environments, systems, or methods in which aspects or embodiments of the present invention can be implemented.

[0070] Embodiments of the present invention are directed to enabling unreliable vital signs of a subject to be identified and potentially discarded / ignored.Such information may therefore contribute to improved monitoring accuracy or efficiency, for example by avoiding or reducing the number of false alarms.

[0071] Embodiments employ the concept of determining the reliability of vital signs based on the subject's physical activity or posture. Such activity or posture can be sensed, for example, using a wearable mobile. In addition, by taking into account one or more physical or physiological attributes of the subject, the impact of the subject's physical activity or posture on his / her vital signs can be evaluated. Only when the vital signs are deemed reliable (e.g., indicating that the subject is at rest) can the warning system then be activated / triggered.

[0072] By determining a measure of the reliability of vital signs, embodiments can enable identification of meaningful changes in a subject's vital signs that are significant and / or represent potential changes in a person's physical health. This can help reduce the number of false positives (i.e., inaccurate or incorrect instances) and provide more accurate monitoring. Thus, embodiments can be helpful for assessment or monitoring purposes, such as to evaluate whether a subject shows significant improvements in physical health.

[0073] Physical activity or posture can be detected or inferred based on sensor output signals, and systems and methods for such detection or inference already exist. Therefore, the proposed concept can be used in combination with existing activity / posture detection or monitoring systems / methods. For example, Dries Vermeiren et al. described a system based on 2 three-axis accelerometers for detecting patients' daily living activities (ADL) in an article entitled "Detecting Human Motion: Introducing Step, Fall and ADL algorithms". Moreover, H Pirsiavas et al. described an algorithm for detecting ADL in first-person camera views in an article entitled "Detecting activities of daily living in first-person camera views" (CVPR, 2012). In addition, in Bonomi, Alberto G. et al., "Detection of type, duration, and intensity of physical activity using an accelerometer" (Medicine & Science in Sports & Exercise 41.9 (2009): 1770-1777), a system is described that is capable of classifying activity types such as walking, active standing or sitting based on a single three-axis accelerometer positioned on the trunk of the body, and defining its duration and intensity according to metabolic consumption. Because many such ADL detection or monitoring methods / systems are known and any one or more of these may be employed, a detailed description of such methods / systems is omitted from this description.

[0074] Figure 1 An embodiment of a system 1 according to the invention is shown comprising a motion sensor 10 adapted to detect object movements of an object.

[0075] Here, the motion sensor 10 is integrated into a portable device coupled to the monitored object, carried or worn by the monitored object, so that it moves with the movement of the object. For example, the motion sensor 10 may include an accelerometer, a magnetometer and / or a gyroscope.

[0076] In this way, the person only needs to carry out his / her normal activities while being monitored, and may not even be aware that he / she is operating the motion sensor 10 and being monitored. This configuration of the motion sensor 10 can enable the movement of an object to be detected without requiring the person to remember to perform any special or additional activities in order for the movement or activity of the object to be detected. For example, it can remove the need for the subject to perform a specific additional action (e.g., pressing a button) in order to activate the motion sensor 10.

[0077] The motion sensor 10 comprises a motion sensing arrangement adapted to determine (when the object is moving) the speed of movement of the object, the distance travelled by the object and the rate of acceleration of the object.

[0078] The motion sensor 10 is adapted to output a sensor output signal 100 of (one or more) detected values ​​representing the movement of the object. Of course, many more sensors may be employed to provide signals of detected values ​​indicative of the nature of the activity and / or posture of the object. For example, one or more pressure sensors may be used to detect the amplitude of a pull or thrust applied by an object to an object. Such additional signals may be useful for identifying which of the properties of the object indicated in the sensor output signal 100. They may also be used to confirm or qualify the values ​​detected by the motion sensor 10 so that false or unintentional measurements are avoided. For example, a signal from a position sensor worn by a monitored object may be used to confirm whether the value detected by the motion sensor 10 is indeed attributable to, for example, the monitored object walking.

[0079] The motion sensor 10 communicates its output signal 100 via a wired or wireless connection. As an example, the wireless connection may include a short- to medium-range communication link. For the avoidance of doubt, a short- to medium-range communication link may be considered to refer to a short-range or medium-range communication link having a range of up to about one hundred (100) meters. In a short-range communication link designed for a very short communication distance, the signal typically travels from a few centimeters to a few meters, while in a medium-range communication link designed for a short- to medium-range communication distance, the signal typically travels up to one hundred (100) meters. Examples of short-range wireless communication links are ANT+, Bluetooth, Bluetooth Low Energy, IEEE802.15.4, ISA100a, infrared (IrDA), near field communication (NFC), RFID, 6LoWPAN, UWB, wireless HART, wireless HD, wireless USB, ZigBee. Examples of medium-range communication links include Wi-Fi, ISM band, Z-wave. Here, the output signal is not encrypted for communication via a wired or wireless connection in a protected manner. However, it will be appreciated that in other embodiments, one or more encryption techniques and / or one or more secure communication links may be employed for communication of signals in the system.

[0080] The system also includes a system 110 for determining the reliability of the vital signs of the monitored subject. The system 110 has a signal interface 115 adapted to receive the sensor output signal 100. In this way, the signal interface 115 is adapted to receive activity data related to the detected activity or posture of the monitored subject. The activity data includes information representing the detected value of the nature of the activity or posture of the subject.

[0081] The system 110 also includes a data acquisition unit 120 adapted to obtain physiological data related to one or more physical or physiological attributes of the monitored subject. Here, the data acquisition unit 120 retrieves the physiological data from a database 121, which is adapted to store values ​​of the physical or physiological attributes of the monitored subject, such as height, weight, age, gender, recovery ability and health level.

[0082] The obtained activity data and physiological data are provided to a reliability unit 122 of the system 110. The reliability unit 122 is adapted to process the activity data and physiological data to determine a measure of reliability of the vital signs of the monitored subject. To this end, the reliability unit 122 of the system 110 may communicate with one or more data processing resources available in the Internet or "cloud" 50. Such data processing resources may perform some or all of the processing required to determine the measure of reliability.

[0083] In this embodiment, the reliability unit 122 compares the value of the physiological data with one or more threshold values ​​to obtain a comparison result and generates a characterization value based on the physiological data. Based on the comparison result and the characterization value, the reliability unit 122 determines a measure of the reliability of the vital signs of the monitored object. The measure of reliability includes: a value of the recovery time required for the monitored object to return to a resting state, and / or a measure of the deviation of the vital signs of the monitored object from a resting value or range in which the monitored object is in a resting state. Therefore, for this purpose, the reliability unit 122 of this embodiment is also suitable for determining the resting state of the monitored object based on the physiological data. For example, the resting heart rate of the object can be calculated using physiological data related to the object (such as height, weight, age, health level, etc.).

[0084] The signal interface 115 of this embodiment is further adapted to obtain vital sign data relating to detected values ​​of vital signs of the monitored subject. Here, such vital sign data is provided from a vital sign sensor 125, which in this embodiment is a heart rate monitor.

[0085] The obtained vital sign data are provided to a prediction unit 124 of the system 110. The prediction unit 124 is adapted to determine, based on the vital sign data and the measure of reliability determined by the reliability unit 122, a predicted value of a vital sign (eg heart rate) of the monitored subject at rest.

[0086] For example, if the determined measure of reliability includes a value for the deviation of the monitored subject's heart rate from a resting value or range for the monitored subject, this can be combined with the currently detected subject's heart rate to predict a value for the heart rate without the changes caused by activity or posture. In other words, the determined measure of reliability can be used to adjust the currently detected subject's heart rate to accommodate the subject's activity or posture.

[0087] Again, for this purpose, prediction unit 124 may communicate with one or more data processing resources available in the Internet or "cloud" 50. Such data processing resources may perform some or all of the processing required to determine a predicted value for a vital sign.

[0088] Thus, it will be appreciated that embodiments may employ distributed processing principles.

[0089] The data processing system 110 is further adapted to generate an output signal 130 representing a measure of the determined reliability of the vital signs of the monitored subject. In other words, after determining a measure of the reliability of the vital signs of the monitored subject based on the activity data and physiological data obtained (with or without communication with the data processing resource via the Internet or the "cloud"), the output signal 130 representing the determined measure of reliability is generated.

[0090] The system also includes a graphical user interface (GUI) 160 for providing information to one or more users. The output signal 130 is provided to the GUI 160 via a wired or wireless connection. By way of example, the wireless connection may include a short to medium range communication link. Figure 1 As indicated, the output signal 130 is provided from the data processing unit 110 to the GUI 160. However, where the system already uses data processing resources via the Internet or the cloud 50, the output signal may be made available to the GUI 160 via the Internet or the cloud 50.

[0091] Based on the output signal 130, the GUI 160 is adapted to communicate information by displaying one or more graphical elements in a display area of ​​the GUI 160. In this manner, the system can communicate information about a measure of the reliability of a vital sign, which can help indicate whether a change in a vital sign is meaningful and represents a potential change in a person's physical or mental abilities. For example, the GUI 160 can be used to display graphical elements to a medical practitioner, a care provider, a family member, or a close relative. Alternatively or additionally, the GUI 160 can be adapted to display graphical elements to the person being monitored.

[0092] according to Figure 1From the above description of the embodiments, it will be appreciated that a system for identifying whether a change in a vital sign is meaningful and represents a potential change in a person's physical capabilities (or otherwise simply caused by activity or posture) is proposed. The system can be considered to include three main subsystems / functions: (i) the first is a source of activity data, which can, for example, include a wearable sensor capable of detecting one or more properties of an event (such as a walk occurring or a chair being raised); (ii) a second implementation is used to collect physiological data related to one or more physical or physiological attributes of the monitored subject; and (iii) a third implementation is an algorithm for determining a measure of the reliability of the vital signs of the monitored subject by analyzing the activity data and the physiological data.

[0093] Although not addressed above Figure 1 In the embodiment described in detail, however, in other embodiments, the reliability unit may be adapted to obtain a historical measure of the reliability of the vital signs of the monitored object (e.g. from a database adapted to store previously determined measures of reliability for previously detected activities or postures of the monitored object). The reliability unit may then determine a trend in the reliability of the vital signs of the monitored object further based on the determined measure of reliability and the historical measure of reliability.

[0094] From the above description, it will be appreciated that a concept for assessing whether a monitored subject's vital signs (such as heart rate, respiratory rate, blood pressure, etc.) are reliable for use in monitoring a subject (e.g., for an early warning system) is proposed. This can address the problem of false alarms generated in response to changes in vital signs caused by the subject's physical activity. The proposed embodiments can therefore enable hospitals to more accurately and / or reliably assess patient deterioration.

[0095] The method according to the embodiment can be summarized as follows:

[0096] (i) determining a measure of physical activity exerted by the monitored subject, such as determining the intensity, duration and / or type of activity being performed by the subject;

[0097] (ii) determining an activity history, e.g., calculating an index representing the cumulative effect of physical activity over time on the subject's vital signs. Such an activity history index is updated based on the subject's current activity type and / or intensity and based on the elapsed time since a previous activity (or set of activities);

[0098] (iii) personalizing model parameters, e.g., personalizing a model of how activity affects vital signs by changing or updating the values ​​of model parameters based on the subject's physiological characteristics. This makes the model customized to the subject;

[0099] (iv) determining the reliability of vital signs, such as determining whether measurements collected for a subject during a period of time represent a resting condition by assessing whether a motion history index is below a certain threshold indicating that previous activity or posture changes no longer affect the subject patient's vital signs;

[0100] (v) Inferring the values ​​of vital signs at rest: An additional feature of the proposed embodiment can estimate the expected values ​​of vital signs at rest by interpolation of the trends of the vital signs. This can make information about the condition of the subject available more quickly (e.g. even before the motion history has reached the required level of reliability and the vital signs return to a resting state).

[0101] Reference now Figure 2 , depicts a flow diagram of an activity history computation model that may be employed by an embodiment. The method employs accelerometer data and estimates of activity intensity and type.

[0102] First, in step 200, raw acceleration data is obtained from an accelerometer system attached to (or carried by) a monitored object.

[0103] The acceleration data is then processed in step 210. The processing in step 210 includes calculating characteristics of the acceleration data, such as amplitude, variance, and frequency content.

[0104] The acceleration signature is then compared to a predetermined threshold in step 220. The comparison to the threshold is used to determine whether the acceleration signature indicates activity.

[0105] If it is determined in step 220 that the acceleration characteristic does not exceed the threshold(s), the method proceeds to step 230 where a result is output indicating that no activity was detected (eg, “activity_reject”).

[0106] If it is determined in step 220 that the acceleration feature does exceed the threshold(s), the method proceeds to steps 240 and 250. In step 240, a result is output identifying that activity has been detected (e.g., "activity_detected"). In step 250, the intensity of the activity is determined, and in step 260 the determined intensity is provided as a result representing the intensity of the activity (e.g., "motion_level"). As an example, the intensity of the activity can be represented by a value ranging from 1 to 5 based on the acceleration signal variance.

[0107] The outputs of steps 240 and 260 are provided to step 270. The determination of the subject's personal recovery time from step 280 is also provided to step 270 along with the measure of activity history obtained from step 290.

[0108] The activity history is configured to be an index of the representativeness of the measured vital signs for the patient's resting condition. The index is determined using information about body load, such as the duration and intensity of detected movements within a certain time interval (e.g., 5 minutes). The activity history index is continuously updated over time based on: (i) the activity history value at the previous period, (ii) the subject's current body load, and (iii) a mean life time constant that defines how quickly the vital signs will converge to a representative resting state.

[0109] The individual recovery time (hereinafter referred to as mean life time constant) can be personalized for the subject in the calibration phase. The mean life time constant (τ-tau) is needed to update the activity history index when the subject is at rest and is recovering after physical activity or posture change.

[0110] In step 270, an activity history index is calculated using the provided inputs (i.e., the indication of detected activity from step 240, the activity intensity from step 260, the subject's personal recovery time from step 280, and the measure of activity history obtained from step 290). The calculated activity history index is provided as output 300 and is also used in step 290 to update the measure of activity history.

[0111] By way of example, the activity history index can be calculated mathematically according to the following formula:

[0112] Mh(t)=Mh(t-1)e -dt / τ ,

[0113] Wherein, Mh indicates the activity history (eg, motion history) at time t, dt is the time elapsed between time t-1 and t, and τ (tau) represents the time constant of exponential decay and depends on the physical or physiological properties of the subject.

[0114] The activity history can be expressed in units comparable to the units used to define the activity intensity. An example of how the activity history index (Mh) can be calculated starting from the definition of the activity level (AL) of the activity performed by the subject is shown below (Python TM ) code (where explanations are identified by the # (pound sign) symbol).

[0115]

[0116]

[0117] exist Figure 3A and 3BThe resulting calculations are illustrated in FIG for different values ​​of the time constant of the exponential decay. More specifically, the change in the subject's activity intensity over time is plotted as a solid line, and the subject's activity history index (Mh) is plotted as a dashed line. Here, the subject changes posture twice within 5 minutes each time and then walks at two different rates each time.

[0118] Figure 3A Shows the activity history than in Figure 3B The decay is slower (hence, tau is larger). Figure 3A The associated vital signs will not be suitable for assessment by the hospital's early warning score over a longer period of time.

[0119] Additionally, the algorithm designed to determine changes in the activity history index can be customized for a particular subject's situation.

[0120] Embodiments can be adapted to measure a subject's vital signs during a calibration phase. During such calibration, time trends of vital signs (e.g., heart rate or breathing rate) in response to physical activity or posture changes can be registered and used to determine an exponentially modeled mean life time decay that relates the activity history index to the time after which the vital sign has returned to a resting condition.

[0121] An alternative way to calculate the motion history is presented by the following algorithm based on an IRR filter of motion intensity to determine the motion history.

[0122]

[0123] The above approach will result in an activity history index that more closely resembles the temporal trends of the vital signs. The main difference from the previous implementation is that the time to reach the reliability threshold depends on the intensity and duration of the activity. The longer the activity (of a certain intensity), the longer it takes for the activity history index to reach a sufficiently low level as required to consider the vital signs to indicate that the subject is at rest.

[0124] Figure 4A and 4B The effect of this simple algorithm on subject data assuming different individual trends in vital signs as described by the coefficient gamma of the model is shown. Figure 4A and 4B In FIG. 5 , the change of the subject's activity intensity over time is plotted as a solid line, and the subject's activity history index (Mh) is plotted as a dotted line.

[0125] Figure 4A Shows the activity history than in Figure 4B The condition in decays more slowly (hence, tau is larger). Figure 4AThe associated vital signs will not be suitable for assessment by the hospital's early warning score over a longer period of time.

[0126] In an alternative embodiment, personalized parameters of the activity history model (e.g., tau or gamma) can also be used to evaluate the subject's ability to recover from physical stress. This can help detect a deteriorating condition of the subject and can be used to issue an alarm for results that exceed the early warning score. For example, if tau becomes significantly larger than it was before, an alarm can be issued to warn of deterioration. On the other hand, a significant decrease in tau can suggest that the subject has reached a better condition and can therefore be used to give a caregiver notification that the subject may be ready for discharge from the hospital or nursing home.

[0127] Furthermore, any large deviation between the expected and observed decrease in vital signs following physical activity can also be used as a sign of the subject's deterioration or readiness for discharge.

[0128] Tau and gamma may depend on the vital sign under study. For example, after activity, the respiratory rate typically returns to its resting value earlier than the heart rate. Tau is therefore typically smaller for the respiratory rate than it is for the heart rate. If the system of the invention is used for more than one type of vital sign, it may therefore work with different values ​​of tau and gamma for each vital sign.

[0129] Reference now Figure 5 , depicts another embodiment of a system according to the invention comprising an accelerometer arrangement 410 adapted to detect movement of a person. Here, the accelerometer arrangement 410 comprises a high-resolution three-axis accelerometer arrangement 410 adapted to be integrated into a necklace or pendant worn by a monitored subject. The accelerometer arrangement 410 is adapted to output one or more signals representing the detected value(s) of the movement of the subject.

[0130] Although this embodiment has been described as employing a portable and wearable sensor arrangement, it will be appreciated that in alternative embodiments, the movement of an object may be detected using one or more sensors strategically positioned within the monitoring environment. For example, a motion detection system may be positioned at the entrance or doorway of a room to measure the velocity of an object as it enters and leaves the room. Additionally, where multiple locations may be provided (e.g., on the first and second floors, etc.), multiple motion sensing systems may be employed and the measurements combined.

[0131] The sensor 10 that measures activity / posture may or may not be included in the same device as the vital signs sensor 125. The activity / posture sensor 10 may even be the same sensor as the vital signs sensor 125. For example, an accelerometer placed on the chest may be used to measure both activity / posture and respiration rate. Another example is a camera that measures both activity and heart rate and / or respiration rate. On the other hand, the activity / posture sensor 10 may be completely separate from the vital signs sensor 125, such as when activity is measured using a device in the subject's pocket and the vital signs come from an SpO2 sensor on the subject's finger.

[0132] The accelerometer arrangement 410 communicates the output signal via the Internet 420 (eg, using a wired or wireless connection) to a remotely located data processing system 430 (such as a server) for determining the reliability of the vital sign.

[0133] The data processing system 430 is adapted to receive one or more output signals (e.g. as activity data) from the accelerometer arrangement 410. The system is also adapted to obtain physiological data related to one or more physical or physiological attributes of the monitored subject (e.g. from a local or remote database and / or via a user input interface).

[0134] The data processing system 430 processes the activity data and the physiological data according to the method according to the proposed embodiment to determine a measure of reliability of the vital signs of the monitored object. More specifically, the method compares the value of the physiological data with one or more thresholds to obtain a comparison result, generates a characterization value based on the physiological data, and then determines a measure of reliability of the vital signs of the monitored object based on the comparison result and the characterization value.

[0135] The data processing system 430 is further adapted to generate an output signal representing a measure of the determined reliability of the vital signs of the monitored subject. Thus, the data processing 430 provides a centrally accessible processing resource that can receive information from the accelerometer arrangement 410 and run one or more algorithms to transform the received information into a description of the measure of the reliability of the vital signs of the monitored subject. Information related to the determined measure of reliability can be stored by the data processing system (e.g., in a database) and provided to other components of the system. Such provision of information regarding the detected or inferred measure of reliability of the vital signs of the monitored subject can be made in response to receiving a request (e.g., via the Internet 420) and / or can be made without a request (i.e., "pushed").

[0136] For the purpose of receiving information from the data processing system regarding measures of reliability of detected or inferred vital signs of a monitored subject and thereby enabling the subject's vital signs to be accurately and / or contextually monitored, the system also includes a first mobile computing device 440 and a second mobile computing device 450.

[0137] Here, the first mobile computing device 440 is a mobile phone device (such as a smartphone) having a display for displaying graphical elements representing a person's physical or mental health. The second mobile computing device 450 is a mobile computer such as a laptop or tablet computer having a display for displaying graphical elements representing a person's mobility.

[0138] The data processing system 430 is adapted to communicate output signals to the first mobile computing device 440 and the second mobile computing device 450 via the Internet 420 (e.g., using a wired or wireless connection). As described above, this may be done in response to receiving requests from the first mobile computing device 440 and the second mobile computing device 450.

[0139] Based on the received output signal, the first mobile computing device 440 and the second mobile computing device 450 are adapted to display one or more graphical elements in a display area provided by their respective displays. To this end, the first mobile computing device 440 and the second mobile computing device 450 each include a software application for processing, decrypting and / or interpreting the received output signal in order to determine how to display the graphical elements. Therefore, the first mobile computing device 440 and the second mobile computing device 450 each include a processing arrangement adapted to represent one or more values ​​of a measure of reliability of a vital sign of a subject, and based on the one or more values ​​of the measure of reliability of a vital sign, generate a display control signal for modifying at least one of a size, shape, position, orientation, pulsation or color of the graphical element.

[0140] Thus, the system can communicate information about the measure of reliability of the inferred or detected vital signs of the monitored subject to the users of the first mobile computing device 440 and the second mobile computing device 450. For example, each of the first mobile computing device 440 and the second mobile computing device 450 can be used to display graphical elements to a medical practitioner, a care provider, a family member, or a next of kin.

[0141] Implementations of the system of FIG. 4 may vary between: (i) where the data processing system 430 communicates data ready for display, which may, for example, include display data containing graphical elements (e.g., JPEG or other image formats), which are simply displayed to a user of a mobile computing device using a conventional image or web page display (which may be a web-based browser, etc.); (ii) where the data processing system 430 communicates raw data set information, which the receiving mobile computing device then processes to determine a measure of the reliability of the vital signs, and then displays the graphical elements based on the determined changes (e.g., using local software running on the mobile computing device). Of course, in other implementations, processing may be shared between the data processing system 430 and the receiving mobile computing device, such that portions of the data generated at the data processing system 430 are sent to the mobile computing device for further processing by local dedicated software of the mobile computing device. Embodiments may therefore employ server-side processing, client-side processing, or any combination thereof.

[0142] Additionally, where data processing system 430 does not "push" information (e.g., output a signal) but instead communicates information in response to receiving a request, a user of a device making such a request may be required to confirm or authenticate their identity and / or security credentials in order to communicate the information.

[0143] It should also be noted that although embodiments have been described above without requiring the use of additional / supplemental sensors, some embodiments may also include sensors suitable for detecting values ​​of properties of at least one of: the environment, the control / operation of an object, and the monitored object. Such a supplemental sensor arrangement may, for example, help improve the accuracy of activity determination. The supplemental sensor readings may, for example, quantify or improve the data analysis performed. For example, an object may wear or carry an identification tag or location tracker that enables an embodiment to distinguish and ignore the presence of other people or animals detected by a presence sensor or a motion sensor. By way of another example, a signal from a location sensor worn by a monitored object may be used to confirm whether a presence detection is indeed attributable to the monitored object or some other person.

[0144] There are many sensors that can be employed by embodiments. Typical sensors include PIR (pyroelectric infrared sensor; detects movement and presence) or pressure sensors. Many other sensors exist and are contemplated, such as sensors including microphones and cameras (including infrared (IR), or even UV and beyond, part of the spectrum).

[0145] The sensor may also be adapted to perform preliminary processing of the detected values ​​(such as signal filtering, sampling, conditioning, etc.) in order to reduce, for example, the required transmission bandwidth and / or transmission duration.

[0146] Non-intrusive monitoring can therefore be achieved using relatively simple sensors that provide data about specific properties of people (e.g., movement). Moreover, the movement of objects can be detected using inexpensive and widely used sensors. For example, motion sensors can be used to turn on lighting, and people are therefore generally familiar with their use. Therefore, embodiments can use sensors that are considered non-intrusive and more easily accepted by the person being monitored. However, using the data provided by these sensors, the activity of the object can be accurately determined and provide more information about the object being monitored. Therefore, some embodiments of the present invention can use traditional sensors and / or existing sensor arrangements. Moreover, embodiments can use sensors that are considered non-intrusive and more easily accepted by the person being monitored.

[0147] Figure 6 An example of a computer 500 in which one or more portions of an embodiment may be employed is illustrated. Various operations discussed above may utilize the capabilities of the computer 500. For example, one or more portions of a monitoring system suitable for monitoring a person may be incorporated into any element, module, application, and / or component discussed herein.

[0148] Computer 500 includes but is not limited to PC, workstation, laptop, PDA, handheld device, server, storage device, etc. Generally, in terms of hardware architecture, computer 500 may include one or more processors 510, memory 520 and one or more I / O devices 570 communicatively coupled via a local interface (not shown). As known in the art, the local interface may be, for example, but not limited to, one or more buses or other wired or wireless connections. The local interface may have other elements, such as a controller, a buffer (cache), a driver, a repeater and a receiver, to enable communication. In addition, the local interface may include address, control and / or data connections to enable appropriate communication between the above components.

[0149] Processor 510 is a hardware device for executing software that may be stored in memory 520. Processor 510 may be virtually any custom or commercially available processor, central processing unit (CPU), digital signal processor (DSP), or auxiliary processor among several processors associated with computer 500, and processor 510 may be a semiconductor-based microprocessor (in the form of a microchip) or a microprocessor.

[0150] The memory 520 can include any one or a combination of volatile memory elements (e.g., random access memory (RAM), such as dynamic random access memory (DRAM), static random access memory (SRAM), etc.) and non-volatile memory elements (e.g., ROM, erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic tape, compact disk read-only memory (CD-ROM), magnetic disk, diskette, cassette, cartridge, etc.). In addition, the memory 520 can incorporate electrical, magnetic, optical and / or other types of storage media. Note that the memory 520 can have a distributed architecture in which various components are located remotely from each other but can be accessed by the processor 510.

[0151] The software in the memory 520 may include one or more separate programs, each of which includes an ordered list of executable instructions for implementing logical functions. According to an exemplary embodiment, the software in the memory 520 includes a suitable operating system (O / S) 550, a compiler 540, a source code 530, and one or more applications 560. As shown, the application 560 includes many functional components for implementing the features and operations of the exemplary embodiments. The application 560 of the computer 500 can represent various applications, computing units, logic, functional units, processes, operations, virtual entities and / or modules according to the exemplary embodiments, but the application 560 does not mean limitation.

[0152] The operating system 550 controls the execution of other computer programs and provides scheduling, input-output control, file and data management, memory management, and communication control and related services. The inventors foresee that the application 560 used to implement the exemplary embodiment can be applied to all commercial operating systems.

[0153] Application 560 may be a source program, an executable program (object code), a script, or any other entity that includes a set of instructions to be executed. When it is a source program, then the program is typically translated via a compiler (e.g., compiler 540), an assembler, an interpreter, etc., which may or may not be included in memory 520 to operate properly in conjunction with O / S 550. In addition, application 560 can be written in an object-oriented programming language with classes of data and methods or a procedural programming language with routines, subroutines, and / or functions, such as, but not limited to, C, C++, C#, Pascal, BASIC, API calls, HTML, XHTML, XML, php.Python, ASP scripts, FORTRAN, COBOL, Perl, Java, ADA, .NET, etc.

[0154] I / O devices 570 may include input devices such as, for example, but not limited to: a mouse, keyboard, scanner, microphone, camera, etc. In addition, I / O devices 570 may also include output devices such as, but not limited to: a printer, display, etc. Finally, I / O devices 570 may also include devices that transmit both input and output, such as, but not limited to: a NIC or modulator / demodulator (for accessing remote devices, other files, devices, systems, or networks), a radio frequency (RF) or other transceiver, a telephone interface, a bridge, a router, etc. I / O devices 570 also include components for communicating over various networks such as the Internet or an intranet.

[0155] If the computer 500 is a PC, workstation, smart device, etc., the software in the memory 520 may also include a basic input output system (BIOS) (omitted for simplicity). The BIOS is a set of necessary software routines that initialize and test the hardware at startup, start the O / S 550, and support the transfer of data between hardware devices. The BIOS is stored in some type of read-only memory (such as ROM, PROM, EPROM, EEPROM, etc.) so that the BIOS can be executed when the computer 500 is activated.

[0156] When the computer 500 is in operation, the processor 510 is configured to execute software stored within the memory 520, to transfer data to and from the memory 520, and generally control the operation of the computer 500 according to the software. The applications 560 and the O / S 550 are read in whole or in part by the processor 510, possibly buffered in the processor 510, and then executed.

[0157] When application 560 is implemented in software, it should be noted that application 560 can be stored on substantially any computer-readable medium for use by or in conjunction with any computer-related system or method. In the context of this document, a computer-readable medium may be an electronic, magnetic, optical, or other physical device or means that can contain or store a computer program for use by or in conjunction with a computer-related system or method.

[0158] Application 560 can be embodied in any computer-readable medium for use by or in conjunction with an instruction execution system, apparatus, or device (such as a computer-based system, a system containing a processor), or other system capable of extracting instructions from an instruction execution system, apparatus, or device and executing the instructions. In the context of this document, a "computer-readable medium" can be any device that can store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium.

[0159] The present invention may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium (or media) having computer-readable program instructions thereon for causing a processor to execute various aspects of the present invention.

[0160] Computer readable storage medium can be a tangible device that can hold and store the instructions used by the instruction execution device. Computer readable storage medium can be, for example, but not limited to: electronic storage device, magnetic storage device, optical storage device, electromagnetic storage device, semiconductor storage device or any suitable combination of the above. The non-exhaustive list of more specific examples of computer readable storage medium includes the following items: portable computer disk, hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanical encoding device (such as a punch card or a convex structure in a groove on which instructions are recorded) and any suitable combination of the above. Computer readable storage medium as used in this article should not be interpreted as instantaneous signal itself, such as radio waves or other free propagating electromagnetic waves, electromagnetic waves propagated by waveguides or other transmission media (for example, light pulses by optical fiber cables) or electrical signals transmitted by wires.

[0161] The computer-readable program instructions described in this article can be downloaded from a computer-readable storage medium to a corresponding computing / processing device, or downloaded to an external computer or external storage device via a network (e.g., the Internet, a local area network, a wide area network, and / or a wireless network). The network may include copper transmission cables, optical transmission fibers, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the corresponding computing / processing device.

[0162] The computer-readable program instructions for performing the operation of the present invention can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Java, Smalltalk, C++, etc., and conventional procedural programming languages ​​optimized for embedded implementation, such as "C" language or similar programming languages. The computer-readable program instructions can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or completely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any type of network (including local area network (LAN) or wide area network (WAN)), or can be connected to an external computer (for example, by using the Internet of an Internet service provider). In some embodiments, by utilizing the state information of the computer-readable program instructions to personalize the electronic circuit, including for example programmable logic circuit, field programmable gate array (FPGA) or programmable logic array (PLA), the electronic circuit can execute the computer-readable program instructions to perform various aspects of the present invention.

[0163] Various aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It will be understood that each box of the flowchart illustration and / or block diagram and the combination of each box in the flowchart illustration and / or block diagram can be implemented by computer-readable program instructions.

[0164] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine, so that these instructions, when executed by the processor of the computer or other programmable data processing device, create a device for implementing the functions / actions specified in one or more boxes in the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium, which can direct the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable storage medium having the instructions stored therein includes an article of manufacture, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0165] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus, or other device to produce a computer-implemented process, so that the instructions executed on the computer, other programmable apparatus, or other device implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0166] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention.In this regard, each square box in the flow chart or block diagram can represent a module, segment or a part of an instruction, which includes one or more executable instructions for implementing (one or more) specified logical functions.In some alternative implementations, the function marked in the square box can occur in a sequence different from that marked in the accompanying drawings.For example, the two square boxes shown in succession can actually be performed substantially simultaneously, or the square boxes can sometimes be performed in reverse order, depending on the function involved.It will also be noted that each square box in the block diagram and / or the flow chart diagram, and the combination of the square boxes in the block diagram and / or the flow chart diagram can be implemented by a dedicated hardware-based system that performs a specified function or action or performs a combination of special hardware and computer instructions.

[0167] From the above description, it will be appreciated that embodiments can therefore facilitate monitoring of elderly, disabled or ill individuals to support independent living. Detected changes can be used for real-time monitoring and alerts, as well as to detect when vital signs are / are not reliable and / or when vital signs deviate from common or expected patterns or trends.

[0168] The description has been presented for the purpose of illustration and description, but the description is not intended to be exhaustive or to limit the invention in the form disclosed. Many modifications and variations will be apparent to those skilled in the art. The embodiments have been chosen and described in order to best explain the principles of the proposed embodiments, the practical application(s), and to enable others skilled in the art to understand the various embodiments with various modifications foreseen.

Claims

1. A system for determining the reliability of a vital sign of a monitored subject, wherein: The measure of reliability represents the level of influence of current and / or recent activities on the vital signs, the system comprising: a signal interface adapted to obtain activity data associated with a detected activity or gesture of the monitored subject; a data collection unit adapted to obtain physiological data related to one or more physical or physiological attributes of the monitored subject; wherein the one or more physical or physiological attributes of the monitored subject include at least one of the following: height; weight; age; gender; one or more existing diseases; aerobic profile; anaerobic power; strength; agility; body shape; recovery ability; and level of fitness; and a reliability unit adapted to determine a measure of reliability of one or more vital signs of the monitored subject based on the activity data and the physiological data, the measure comprising a duration of a recovery time required for the monitored subject to return to a resting state, The reliability unit is adapted to measure an absolute difference between a current value of a vital sign and a resting state value of the vital sign.

2. The system according to claim 1, wherein: The reliability unit is adapted to determine a resting state of the monitored subject based on the physiological data.

3. The system according to any one of claims 1 to 2, wherein: The signal interface is further adapted to obtain vital sign data associated with detected values ​​of vital signs of the monitored subject, And wherein the system further comprises a prediction unit adapted to determine a predicted value of the vital sign of the monitored subject at rest based on the vital sign data and the measure of reliability of one or more vital signs of the monitored subject.

4. The system according to any one of claims 1 to 2, wherein: The reliability unit is suitable for: comparing the value of the physiological data with one or more thresholds to obtain a comparison result; generating a characterization value based on the physiological data; and A measure of reliability of one or more vital signs of the monitored subject is determined based on the comparison result and the characterization value.

5. The system according to any one of claims 1 to 2, further comprising: a historical data interface adapted to obtain historical data related to previous activities or postures of the monitored subject, And wherein the reliability unit is adapted to determine a measure of reliability of one or more vital signs of the monitored subject also based on the historical data.

6. The system according to any one of claims 1 to 2, wherein: The reliability unit is adapted to obtain a historical measure of reliability of one or more vital signs of the monitored subject, the historical measure of reliability having been previously determined for previously detected activities or gestures of the monitored subject, and Therein, the reliability unit is adapted to determine a trend of the reliability of one or more vital signs of the monitored subject based on the determined measure of reliability and the historical measure of reliability.

7. The system according to any one of claims 1 to 2, further comprising: A sensor is adapted to detect a value of the activity or gesture of the monitored object and to generate a signal comprising activity data representative of the detected value.

8. The system according to claim 7, wherein: The sensor includes at least one of: an accelerometer; a gyroscope; a movement sensor; a weight sensor; a pressure sensor; and a timing device.

9. The system according to claim 7, wherein: The sensor is adapted to be coupled to a person or an object.

10. The system according to any one of claims 1 to 2, wherein: The activity data relating to the detected activity or gesture of the monitored subject comprises a value of at least one of: a speed of movement of the subject; The measure of the force exerted on an object by said object; The distance traveled by a portion of the object; the rate of acceleration of a portion of the object; a measure of the posture of the object.

11. A system for monitoring a subject's vital signs, the system comprising: an input interface adapted to obtain vital sign data associated with one or more detected vital signs of the subject; a sensor arrangement adapted to detect values ​​of an activity or gesture of a monitored subject and to generate activity data representative of the detected values; A system for determining the reliability of one or more vital signs of the monitored subject according to any one of claims 1 to 10; as well as A processing unit is adapted to process the vital sign data based on the determined reliability of one or more vital signs of the monitored subject.

12. A method for determining the reliability of one or more vital signs of a monitored subject implemented by a signal interface, a data acquisition unit and a processing system, wherein: The measure of reliability represents the level of influence of current and / or recent activities on the vital signs, the method comprising: obtaining activity data associated with a detected activity or gesture of the monitored subject; Obtaining physiological data related to one or more physical or physiological attributes of the monitored subject; wherein the one or more physical or physiological attributes of the monitored subject include at least one of the following: height; weight; age; gender; one or more existing diseases; aerobic profile; anaerobic power; strength; agility; body shape; recovery ability; and level of fitness; and determining a measure of reliability of one or more vital signs of the monitored subject based on the activity data and the physiological data, wherein the measure of reliability includes a duration of recovery time required for the monitored subject to return to a resting state; and An absolute difference between a current value of a vital sign and a resting state value of the vital sign is determined.

13. A method for monitoring a subject's vital signs, implemented by a processing system, the method comprising: obtaining vital sign data associated with one or more detected vital signs of the subject; detecting a value of an activity or posture of a monitored subject and generating activity data representing the detected value; Determining the reliability of one or more vital signs of the monitored subject according to claim 12; as well as The vital sign data is processed based on the determined reliability of one or more vital signs of the monitored subject.

14. The method according to claim 13, wherein: Processing the vital sign data includes at least one of: Prevent alarms from being activated; deferring collection of additional vital sign data related to the detected vital signs of the subject; preventing the vital sign data associated with one or more detected vital signs of the subject from being provided to a warning system; as well as A value of a physical or physiological attribute of the subject is determined based on the vital signs data and the determined reliabilities of one or more vital signs of the monitored subject.

15. A computer program product comprising computer readable code capable of being stored or stored on or downloaded from a communications network, said code when run on a computer implementing the method according to any one of claims 12 to 14.

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