(19)
(11)EP 2 350 898 B1

(12)EUROPEAN PATENT SPECIFICATION

(45)Mention of the grant of the patent:
20.05.2020 Bulletin 2020/21

(21)Application number: 09792896.4

(22)Date of filing:  23.09.2009
(51)Int. Cl.: 
G16H 40/63  (2018.01)
(86)International application number:
PCT/US2009/058020
(87)International publication number:
WO 2010/036700 (01.04.2010 Gazette  2010/13)

(54)

CONTACTLESS AND MINIMAL-CONTACT MONITORING OF QUALITY OF LIFE PARAMETERS FOR ASSESSMENT AND INTERVENTION

KONTAKTLOSE UND KONTAKTMINIMALE ÜBERWACHUNG VON LEBENSQUALITÄTSPARAMETERN ZUR BEWERTUNG UND INTERVENTION

SURVEILLANCE SANS CONTACT ET À CONTACT MINIMAL DES PARAMÈTRES DE QUALITÉ DE VIE POUR ÉVALUATION ET INTERVENTION


(84)Designated Contracting States:
AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO SE SI SK SM TR

(30)Priority: 24.09.2008 US 99792 P

(43)Date of publication of application:
03.08.2011 Bulletin 2011/31

(73)Proprietor: ResMed Sensor Technologies Limited
Dublin 4 (IE)

(72)Inventors:
  • HENEGHAN, Conor
    Campbell, CA 95008 (US)
  • HANLEY, Conor
    Dun Laoghaire (IE)
  • FOX, Niall
    Tullamore Co. Offaly (IE)
  • ZAFFARONI, Alberto
    Saronno (IT)
  • DE CHAZAL, Philip
    Dublin 2 (IE)

(74)Representative: Vossius & Partner Patentanwälte Rechtsanwälte mbB 
Siebertstrasse 3
81675 München
81675 München (DE)


(56)References cited: : 
WO-A-2006/054306
WO-A-2008/057883
WO-A-2007/143535
WO-A1-2008/037020
  
      
    Note: Within nine months from the publication of the mention of the grant of the European patent, any person may give notice to the European Patent Office of opposition to the European patent granted. Notice of opposition shall be filed in a written reasoned statement. It shall not be deemed to have been filed until the opposition fee has been paid. (Art. 99(1) European Patent Convention).


    Description

    BACKGROUND



    [0001] This disclosure relates to the measurement, aggregation and analysis of data collected using non-contact or minimal-contact sensors together with a means for capturing subjective responses to provide quality of life parameters for individual subjects, particularly in the context of a controlled trial of interventions on human subjects (e.g., a clinical trial of a drug, or an evaluation of a consumer item such as a fragrance).

    [0002] Monitoring of quality-of-life (QOL) parameters can be of importance when developing interventions aimed at improving a person's QOL. Quality-of-life parameters are measurements of general well-being which are generally accepted as being meaningful to an individual's perception of their life. In general QOL markers have a combination of an underlying objectively measurable elements, and a subjectively related element. Specific non-limiting examples include:
    • Sleep quality - an individual can subjectively report whether they are sleeping well or badly, and this has an impact on their perceived QOL. For a sleep quality QOL parameter, an objective measurement could be sleep duration, and a subjective input could be "how restful" the sleep was.
    • Stress - an individual can report on whether they find their current life circumstances to be stressful. For a stress QOL parameter, an objective measurement could be heart rate or cortisol levels; a subjective element could be a stress level questionnaire
    • Relaxation - an individual can report the subjective sensation of being relaxed, which can also be objectively related to autonomic nervous system activity.
    • Pain - an individual can subjectively record levels of pain using a Pain Index [such as the Visual Analog Scale]. More objective measurements of pain can be obtained using a dolorimeter
    • Body temperature - subjects can often report feelings of overheating or coolness which are not directly related to objective measurement of body core temperature.
    • Vigilance/drowsiness - vigilance, or attentiveness can also be measured objectively (e.g., using the psychomotor vigilance test) or through subjective questionnaires.


    [0003] For clarification, a non-contact (or contactless) sensor is one which senses a parameter of a subject's physiology or behavior without any direct physical contact with a subject. Non-limiting examples include a movement detector based on radio-wave reflections, a microphone placed remotely from a subject, an infrared camera recording the surface temperature, or a faucet-monitor which records turning on of a faucet to wash hands. A minimal contact sensor may be considered to be one in which there is some physical contact with a sensor, but this is limited to short durations. Examples include a weight scale, a blood pressure monitor, a breath analyzer, or a hand-held surface ECG monitor. These minimal contact sensors can be distinguished from contact sensors typically used in clinical trials such as ECG patches, oximeters, EEG electrodes, etc, where there typically is adhesion to the body, and typically the sensor is intended for use over prolonged periods of time (e.g. > 1 hour).

    [0004] A key unifying factor in defining QOL parameters is the need to combine objective data from sensors, and subjective data from the monitored subject to assess the overall QOL. A particular challenge then arises when one wishes to measure the impact of an intervention on changes in QOL. For example, a company who has developed a drug to counteract sleep disruption will be interested to see if its drug has had any direct impact on a person's sleep which has resulted in either objectively or subjectively improved QOL. Similarly if a company has developed a product such as a skin emollient to reduce itchiness due to dry skin, they may wish to see if there has been an improved QOL (i.e., reduced scratching, lower level of discomfort) etc.

    [0005] One commonly accepted means for answering such questions is to conduct a clinical or consumer trial which poses a statistical hypothesis which can be verified or rejected with a certain level of confidence. For example, in drug trials a double-blinded random controlled trial is a well accepted methodology for ascertaining the effect of drugs. However, measurement of QOL is difficult to conduct for a number of reasons, which various aspects of this disclosure can overcome: (a) it can be difficult to define a suitable measure for a QOL outcome, (b) by wearing a measurement device to measure QOL, one may directly impact on the exact quality-of-life parameter you wish to study, (c) there are logistical and financial challenges of measuring parameters in a natural "home" setting rather than in a formal laboratory setting. There are a variety of conventional techniques to measure some aspects of QOL which will now be discussed, together with their limitations.

    [0006] Monitoring of a quality-of-life parameter can be motivated by a desire to integrate it into an intervention program. As an example, a person may undertake cognitive behavioral therapy (CBT) to reduce their stress-related quality of life. An important component of a CBT program is the ongoing assessment of the stress quality of life index, whose measurement will itself form part of the behavioral intervention. As a second example of an embodiment of the disclosure, we will describe a system for improving sleep quality through use of objective and subjective measurements of sleep quality-of-life indices.

    [0007] As specific examples of the limitations of the current state of the art, consider the problem of measuring sleep quality in response to an anti-insomnia drug. Firstly, defining "sleep quality" as it relates to quality of life can be difficult, as this will often be a combination of objective and subjective measurements. Secondly, the current method favored for measuring sleep is to use a so-called polysomnogram which measures multiple physiological parameters (EEG, ECG, EOG, respiratory effort, oxygen level etc.). While the resulting physiological measurements are very rich, their measurement fundamentally alters the sleeping state of the subject (e.g., it is harder for them to turn over in bed), and cannot represent a true QOL sleep measurement. Finally, the current cost of the polysomnogram test (approximately $1500 in 2008) makes it an impractical tool for measurement of sleep quality in large numbers of subjects over long periods of time. Accordingly, there is a need for a system which can provide robust measurements of sleep quality-of-life in a highly non-invasive fashion. In an embodiment of our system, we describe one method for objectively measuring sleep quality using a totally non-invasive biomotion sensor. This can be combined with a number of subjective tools for measuring sleep quality, such as the Pittsburgh Sleep Quality Index and the Insomnia Severity Index (these consist of questionnaires on sleep habits such as time-to-bed, estimated time-to-fall-asleep etc.

    [0008] Another QOL parameter of interest is stress level or, conversely, relaxation. Current techniques for objective measurement of stress include measurement of heart rate variability or cortisol levels. However, measurement of heart rate variability typically requires the subject to wear electrodes on the chest, which is often impractical for situations of daily living. Likewise, collection of cortisol samples to assess stress requires frequent collection of saliva samples, and is difficult to integrate into a daily living routine. There are also a number of widely used subjective measurements of stress or anxiety (e.g., Spiclberger's State-Trait Anxiety Inventory). Accordingly, a method, system or apparatus which can reliably gather information about stress-related QOL parameters would have utility in a variety of settings.

    [0009] Finally, measurement of the quality-of-life implications of chronic pain (such as chronic lower back pain) would have utility for assessing the benefit of therapies, or for providing cognitive feedback on pain management. Current subjective measurement tools such as the Oswestry Disability Index and the 36-Item Short-Form Health Survey are used to assess subjective quality of life in subjects with chronic pain conditions. Objective measurements of pain are not well defined, but there is some evidence that heart rate is correlated with pain intensity.

    [0010] Accordingly, there is a clearly established need for systems and methods which measure quality-of-life outcomes in ambulatory/home settings, and which have minimal impact on the daily routine of the person whose QOL is being monitored. This is a particular need in clinical trials for non-contact or minimal contact sensors where the effects of interventions such as drugs, ointments, physiotherapy, nutriceuticals, behavior changes etc. are being evaluated.

    [0011] WO 2008/037020 A1 describes systems and/or methods for assessing the sleep quality of a patient in a sleep session, wherein data is collected from the patient and/or physician including, for example, sleep session data in the form of one or more physiological parameters of the patient indicative of the patient's sleep quality during the sleep session, a subjective evaluation of sleep quality, etc.; patient profile data; etc. Furthermore, it is described that a sleep quality index algorithm, which optionally may be an adaptive algorithm, is applied, taking into account some or all of the collected data.

    SUMMARY



    [0012] The invention is defined by the appended claims.

    [0013] This disclosure provides various embodiments of an apparatus, system, and method for monitoring of quality-of-life parameters of a subject, using contact-free or minimal-contact sensors, in a convenient and low-cost fashion. The typical user of the system is a remote observer who wishes to monitor the QOL of the monitored subject in as non-invasive fashion as possible. The system typically includes: (a) one or more contactless or minimal-contact sensor units suitable for being placed close to where the subject is present (e.g., on a bedside table), (b) an input device for electronically capturing subjective responses such as a cell-phone, PDA etc., (c) a device for aggregating data together and transmitting to a remote location, (d) a display unit for showing information to the local user, and (e) a data archiving and analysis system for display and analysis of the quality-of-life parameters. The component (e) can also be used as a feedback device for interventional programs. For convenience, the sensor unit, input unit, data aggregation/transmission unit, and the display/monitoring unit can be incorporated into a single stand-alone unit, if desired (for example, all of these functions could be integrated on a cell-phone platform). The sensor units may include one or more of a non-contact measurement sensor (for detection of parameters such as sound, general bodily movement, respiration, heart rate, position, temperature), and one or more minimal contact sensors (e.g. weighing scales, thermometer). In one or more aspects of this disclosure, a system may incorporate a processing capability (which can be either at the local or remote sites) to generate quality-of-life parameters based on the objective and subjective measurements from a user. As a specific example, an overall sleep quality-of-life could be generated by combining the subjective response of the user to the Insomnia Severity Index together with an objective measurement of sleep duration.

    [0014] In one or more embodiments, the disclosed approaches (pharmaceutical, device-based or behavioral) are useful in improving the quality-of-life parameters for these subjects. In particular, non-contact or minimal-contact measurement of quality-of-life parameters such as sleep, stress, relaxation, drowsiness, temperature and emotional state of humans is disclosed, together with means for automated sampling, storage, and transmission to a remote data analysis center. In one or more embodiments, one aspect of the system measures objective data with as little disruption as possible to the normal behavior of the subject.

    [0015] In one particular embodiment, a quality-of-life monitoring system for human subjects, includes a plurality of multi-parameter physiological and environmental sensors configured to detect a plurality of physiological and environmental parameters related to a quality of life assessment, wherein each of said plurality of sensors either have no contact or minimal contact with a monitored subject; a timer that controls sampling of the detected parameters and allows a chronological reconstruction of recorded signals relating thereto; an input device which captures subjective responses from the monitored subject; a data storage device configured to record sampled signals; a data transmission capability so that data collected from a subject can be transmitted to a remote data monitoring center, and messages can be transmitted to the monitoring sensors; and a data monitoring and analysis capability so that overall quality-of-life parameters can be calculated based on the measured signals.

    [0016] In another embodiment, a method for assessing a quality of life index includes measuring multi-parameter physiological and environmental parameters which are related to a quality of life assessment of a monitored subject with no contact or minimal contact with the monitored subject; collecting subjective responses from the monitored subject about their quality-of-life; analyzing objective and subjective measurements to generate a quantitative quality-of-life index; and generating suggested interventions to affect the measured quality of life index of the monitored subject.

    BRIEF DESCRIPTION OF THE DRAWINGS



    [0017] Embodiments of the disclosure will now be described with reference to the accompanying drawings in which:

    FIG. 1 is a diagram illustrating an overall schematic of an embodiment;

    FIG. 2 is a specific example of an embodiment in which a contactless sensor is used to monitor the sleeping state of a subject, by placement in a nearby location (bedside locker);

    FIG. 3 is an example of an input device embodiment that could be used to capture subjective responses from individuals;

    FIG. 4 is an alternative example of an embodiment in which a web-site could be used to capture the subjective responses from an individual;

    FIG. 5 is an example of an embodiment in which some of the raw data captured by a specific contactless sensor used in a sleep trial;

    FIG. 6 shows example results of the system in measuring sleep apnea in a clinical trial; and

    FIGS. 7A and 7B shows schematic representations of behavioral interventions based on one or more embodiments of this disclosure.


    DETAILED DESCRIPTION



    [0018] FIG. 1 is a diagram illustrating an overall schematic of an embodiment of this disclosure. Monitored subject 101 may be observed by a plurality of contactless 102 and minimal contact sensors 103. Subject 101 may also has access to input device 104 capable of obtaining subjective feedback from the subject through written text or recorded sound. Data aggregation and transmission device 105 collects the data from the sensors 102, 103 and 104, and may also control data sampling and input parameters used by the various sensors and devices. Optionally, display/feedback device 107 can be provided to the local user (e.g., this might indicate whether a signal is being collected from them, or give feedback on the most recent set of QOL parameters measured). Data aggregation and transmission device 105 may be configured to communicate in a bilateral way with remote data archiving and analysis system 106. Data archiving and analysis system 106 may store data from a plurality of subjects, and can carry out analysis of the recorded signals and feedback. It may also communicate with data display device 107 which can show the results of the analysis to a user, or with an optional separate display device 108 which shows the QOL parameters to a remote user.

    [0019] FIG. 2 illustrates an embodiment of a contactless sensor that objectively monitors the sleeping state of a subject. In this embodiment, the sensor unit may contain one or more of a radio-frequency based biomotion sensor, a microphone (to pick up ambient sound), a temperature sensor (to pick up ambient temperature), a light sensor (to pick up ambient light levels), and an infrared detector for measuring the subject temperature. The contactless sensor may be placed on a bedside table, for example.

    [0020] FIG 3 illustrates an example of an embodiment of an input device for collecting user input. The input device would typically include alphanumeric keypad 301, display 302, microphone 303, and loudspeaker 304. This allows the generation of questions using either visual or audio means, and a person can then answer the questions using either text or audio input.

    [0021] FIG. 4 illustrates an embodiment using a personal computer with an internet browser to capture subjective perceptions of sleep.

    [0022] FIG. 5 provides an example of raw signals captured using a contactless sensor in a trial for measuring sleep quality-of-life. FIG. 4A shows the signal when a person is asleep and then turns over on their side. FIG. 4B shows the signal when the person is in deep sleep.

    [0023] FIG. 6 is an example of how the contactless system can estimate apnea-hypopnea index in a clinical trial with an accuracy similar to that of the current polysomnogram (PSG) estimates.

    [0024] FIG 7 is an example of a behavioral intervention based on use of the system to enhance sleep quality. FIG. 7(A) shows the components of a intervention based over several weeks, in which there is an initial session at which detailed information about sleep is provided, and the person is given the system for measurement of their sleep quality-of-life index (SQOLI).

    [0025] FIG. 7(B) shows an example of a specific algorithm that could be used within the intervention, based on the feedback from the SQOLI monitoring. For example, if they achieve an SQOLI greater than target, they can increase their time in bed by 30 minutes. If they fail, they can reduce time in bed by 15 minutes.

    [0026] A typical embodiment of a system of this disclosure may include one or more non-contact sensors or minimal-contact sensors that can include one or more of the following:
    1. (a) A biomotion sensor which measures movement, and which derives respiration, heart rate and movement parameters. An example of such a sensor is more fully described in the article written by P. de Chazal, E. O'Hare, N. Fox, C. Heneghan, "Assessment of Sleep/Wake Patterns Using a Non-Contact Biomotion Sensor", Proc. 30th IEEE EMBS Conference, Aug 2008, published by the IEEE.
      In one embodiment, the biomotion sensor may use a series of radio-frequency pulses at 5.8 GHz to generate echoes from a sleeping subject. The echoes may be mixed with the transmitted signals to generate a movement trace which includes movements due to breathing, heart rate, and positional changes.
    2. (b) An audio sensor which measures ambient sound. A specific example of a microphone appropriate for inclusion in the system would be the HK-Sound Omni, -27 dB microphone with part number S-OM9765C273S-C08.
    3. (c) A temperature sensor which measures environmental temperature (typically to ±1C). A specific example of a temperature sensor appropriate for inclusion would be the National Semiconductor LM20, SC70 package.
    4. (d) A light level sensor would measure light level. A specific example of a light level sensor appropriate for inclusion is the Square D® Clipsal Light-Level Sensor.
    5. (e) A body-temperature measuring sensor. A specific example of a sensor that may be used in the system is the body thermometer Part No. 310 from the YuanYa Far Asia Company.


    [0027] The minimal contact sensors may include one or more of the following:
    1. (a) A weighing scales for measuring body weight. A specific example is the A&D UC-321PBT.
    2. (b) A blood pressure device, such as the A&F UA767PBT.
    3. (c) A continuous positive airway pressure device for treating sleep apnea, such as the ResMed Autoset Spirit S8.
    4. (d) A pedometer for measuring step-counts (such as the Omron Pocket Pedometer with PC software, HJ-720ITC).
    5. (e) A body-worn accelerometer for measuring physical activity during the day (such as the ActivePAL device).
    6. (f) A body composition analyzer such as the Omron Body Composition Monitor with Scale, HBF-500, which calculates visceral fat and base metabolic rate.
    7. (g) Other contactless or minimally contacting devices could also be included.


    [0028] In one or more embodiments, the system may include a data-acquisition and processing capability which provides a logging capability for the non-contact and minimal-contact sensors described above. This typically could include, for example, an analog-to-digital converter (ADC), a timer, and a processor. The processor may be configured to control the sampling of the signals, and may also apply any necessary data processing or reduction techniques (e.g., compression) to minimize unnecessary storage or transmission of data.

    [0029] A data communication subsystem may provide communication capability which could send the recorded data to a remote database for further storage and analysis, and a data analysis system including, for example, a database, can be configured to provide processing functionality as well as input to a visual display.

    [0030] In one specific embodiment of the system, data acquisition, processing, and communications can utilize using, for example, a Bluetooth-enabled data acquisition device (e.g. the commercially available BlueSentry® device from Roving Networks). Other conventional wireless approaches may also be used. This provides the ability to sample arbitrary voltage waveforms, and can also accept data in digital format.

    [0031] In this embodiment, the Bluetooth device can then transmit data to a cell phone using the Bluetooth protocol, so that the data can be stored on a cell-phone memory. The cell phone can also carry out initial processing of the data. The cell phone can also be used as a device for capturing subjective data from the user, using either a text-based entry system, or through a voice enabled question-and-answer system. Subjective data can also be captured using a web-page.

    [0032] The cell phone can provide the data transmission capability to a remote site using protocols such as GPRS or EDGE. The data analysis system is a personal computer running a database (e.g., the My SQL database software), which is capable of being queries by analysis software which can calculate useful QOL parameters. Finally a data display capability can be provided by a program querying the database, the outputs of the analytical program and using graphical or text output on a web browser.

    [0033] As an example of the clinical use of a specific embodiment, the system was used to measure quality-of-life related to sleep in a specific clinical trial scenario. A group of 15 patients with chronic lower back pain (CLBP), and an age and gender matched cohort of 15 subjects with no back pain were recruited. After initial screening and enrollment, study participants completed a baseline assessment. Gender, age, weight, height, BMI and medication usage were recorded. All subjects completed baseline self report measures of sleep quality (Pittsburgh Sleep Quality Index Insomnia Severity Index [16], quality of life (SF36v2) [17] and pain as part of the SF36v2 questionnaire (bodily pain scale of the SF36v2). The CLBP subjects also completed the Oswestry Disability Index (ODI) as a measure of functional disability related to their low back pain. All subjects then underwent two consecutive nights of objective monitoring using the non-contact biomotion sensor mentioned above, while simultaneously completing a subjective daily sleep log; the Pittsburgh Sleep Diary. Table 1 shows some objective measurements of sleep using the system, and includes the total sleep time, sleep efficiency, sleep onset latency. Other objective parameters which could be measured would include: number of awakenings (>1 minute in duration) and wake-after-sleep-onset.
    Table 1: Objective sleep indices obtained using the system
    VariableControl Group (mean ±sd)CLBP Group (mean ±sd)p-value
    Total sleep time (mins) 399 (41) 382 (74) 0.428
    Sleep Efficiency (%) 85.8 (4.4) 77.8 (7.8) 0.002
    Sleep Latency (mins) 9.4 (10.2) 9.3 (11.1) 0.972


    [0034] The objective sleep indices described in Table 1 were obtained using a sleep stage classification system that processed the non-contact biomotion sensor data to produce sleep and awake classifications every 30 seconds. This was developed using the following observations:

    [0035] Large movements (e.g., several cm in size) can be easily recognized in the non-contact signal. Bodily movement provides significant information about the sleep state of a subject, and has been widely used in actigraphy to determine sleep/wake state. The variability of respiration changes significantly with sleep stage. In deep sleep, it has long been noted that respiration is steadier in both frequency and amplitude than during wakefulness of REM sleep.

    [0036] Accordingly, a first stage in processing of the non-contact biomotion signal was to identify movement and respiration information. To illustrate how this is possible, FIG 4A shows an example of the signal recorded by the non-contact sensor when there is a significant movement of the torso and arms due to the person shifting sleeping position. An algorithm based on detection of high amplitude and frequency sections of the signal was used to isolate the periods of movement.

    [0037] For periods where there is no significant limb or torso movement, respiratory-related movement is the predominant recorded signal and estimates of breathing rate and relative amplitude are obtained using a peak and trough identifying algorithm. Figure 4B illustrates the signal recorded by the sensor during a period of Stage 4 sleep that demonstrates a steady breathing effort.

    [0038] To validate the performance of the system in correctly labeling 30-second epochs, we recorded signals simultaneously with a full polysomnogram (PSG) montage. We compared the sleep epoch annotations from the PSG and the non-contact biomotion sensor and report the overall classification accuracy, sleep sensitivity and predictivity, wake specificity and predictivity. The overall accuracy is the percentage of total epochs correctly classified. The results are shown in Table 2, and provide evidence that the system can objectively measure sleep with a high degree of accuracy.
    Table 2: Accuracy of objective recognition of sleep state using the contactless method
    Overall By sleep state 
    Awake 69% Awake 69%
    Sleep 87% REM 82%
    Pred. of Awake 53% Stage 1 61%
    Pred. of Sleep 91% Stage 2 87%
    Accuracy 82% Stage 3 97%
        Stage 4 98%


    [0039] Table 3 shows some of the subjective measurements from the same subjects, and includes their subjective assessment of sleep duration, sleep efficiency, number of awakenings, and sleep latency for each night, as well as their overall PSQI and ISI scores.
    Table 3 Subjective sleep indices obtained using the system
    VariableControl Group (mean ±sd)CLBP Group (mean ±sd)p-value
    Pittsburgh Sleep Quality Index 2.1 (2.1) 11.7 (4.3) <0.001
    Insomnia Severity Index 2.8(4.6) 13.4 (7.3) <0.001
    Estimated Sleep Onset Latency 11.7 (4.3) 45.3 (27.7) <0.001
    Estimated Sleep Efficiency 95.3 (5.8) 73.4 (16.5) <0.001
    Estimated Night Time Awakenings ≥3 2/15 15/15 <0.001


    [0040] The system can report these subjective and objective measurements of sleep but, in one aspect, it can also report parameters related to overall Sleep Quality of Life Index (SQOLI) which combines objective and subjective measurements. There are a number of ways in which this could be done. For example, we could define the following SQOL indices:








    [0041] The skilled user will be able to construct other combined measurements of sleep quality of life which capture the most meaningful outcomes for a particular application.

    [0042] In another embodiment, the system may be used to capture quality-of-life in patients with chronic cough (e.g., patients suffering from chronic obstructive pulmonary disease). In this embodiment, two contactless sensors may be used: the non-contact biomotion sensor described above, and a microphone. The system can measure objectively sounds associated with each coughing episode, and the respiratory effort associated with each cough. This provides a more accurate means of collecting cough frequency than relying on sound alone. There are also subjective measurements of cough impact on quality of life (e.g., the parent cough-specific QOL (PC-QOL) questionnaire described in "Development of a parent-proxy quality-of-life chronic cough-specific questionnaire: clinical impact vs psychometric evaluations," Newcombe PA, Sheffield JK, Juniper EF, Marchant JM, Halsted RA, Masters IB, Chang AB, Chest. 2008 Feb;133(2):386-95).

    [0043] As another exemplary embodiment, the system could be used as a screening tool to identify sleep apnea severity and incidence in a clinical trial setting. In this embodiment, the contactless biomotion sensor is used to detect periods of no-breathing (apnea) and reduced amplitude breathing (hypopnea). FIG. 5 shows the estimated sleep apnea severity of the patients enrolled in a clinical trial, prior to therapy, as an example of how the system can be used.

    [0044] The user skilled in the art will realize that the system can be used in a number of clinical trial settings where measurement of quality-of-life is important. As specific examples of such uses, we can consider:

    [0045] Measurement of sleep quality of life in patients with atopic dermatitis (AD). Subjects with AD often have poor quality of life due to daytime itchiness combined with poor sleep quality due to subconscious scratching during sleep. In a clinical trial designed to assess the impact of an intervention such as a new drug or skin-cream, the system can be used to capture subjective and objective quality of life parameters as a final outcome measure. The outcome of the sleep quality-of-life index measurement can be a recommendation on whether to use a certain active medication, and the dosage of that medication

    [0046] Measurement of sleep quality in infants in response to feeding products. For example, lactose intolerance is known to affect quality-of-life in babies due to disrupted sleep, stomach pain, and crying episodes. Feeding products which aim to overcome lactose intolerance can be assessed by combination of objective sleep indices plus parent-reported crying episodes, to form an overall quality-of-life index.

    [0047] As a further specific embodiment, sleep quality can be enhanced by providing a behavioral feedback program related to sleep quality of life. A person self-reporting insomnia can use the system as follows to enhance their sleep quality of life.

    [0048] On a first visit with a physician, a person can self-report general dissatisfaction with their sleep quality of life. They can then choose to undertake a cognitive behavioral therapy program in the following steps.

    Step 1: They undertake an induction session with a therapist or self-guided manual. In this induction step, the individual is introduced to information about basic physiological mechanisms of sleep such as normal physiological sleep patterns, sleep requirements, etc. This step ensures there are no incorrect perceptions of sleep (i.e. a person believing that 3 hours sleep a night is typical, or that you must sleep exactly 8 hrs per day for normal health).

    Step 2: Bootzin stimulus control instructions. In this step, subject-specific information is established, and basic behavioral interventions are agreed. For example, firstly, the subject and therapies agree a target standard wake-up time (e.g., 7AM). They then agree behavioral interventions such as getting out of bed after 20 minutes of extended awakening, and the need to avoid sleep-incompatible bedroom behavior (e.g., television, computer games, ...). They may agree to eliminate daytime naps.

    Step 3: Establish initial target. Based on discussions above, the patient and therapist may then agree a sleep quality of life index (SQOLI) which will act as a target. As a specific example, the SQOLI may be based on achieving 85% sleep efficiency and a subjective "difficulty falling asleep" rating of <5 (on a 1-10.scale where 10 is very difficult and 1 is easy) The behavioral program will then consist of a week in which the patient tries to achieve the target based on going to bed 5 hours before the agreed wake-up time (e.g. at 2AM in our example). The disclosure we have described above in FIGS. 1 to 5 provides the objective measurements of sleep efficiency and combines with the subjective user feedback to produce an SQOLI. At the end of the first week, the patient and therapist review the SQOLI measurements and determine the next step.

    Step 4: Feedback loop based on Sleep Quality of Index. If the subject has achieved the desired SQOLI in the first week, then a new target is set. As a specific example, the subject will now go to bed 5.5 hours before the agreed wake up time, but will still try to achieve the same targets of 85% sleep efficiency and "difficulty falling asleep" metric < 5. In subsequent weeks, the algorithm will be applied that the person can increase their sleep time by 30 minutes, provided they have met the targets in the previous week. This process can continue until a final desired steady state sleep quality of life index is reached (e.g., sleeping 7.5 hrs per night with a sleep efficiency of >85%).



    [0049] The person skilled in the art will realize that a number of behavioral interventions have been developed and described in the literature for improving sleep quality. However a limitation of all these current approaches is that they do not have a reliable and easy means for providing the sleep quality of life metric, and it is this limitation which the current disclosure overcomes. Furthermore, the person skilled in the art will also realize that a number of pharmaceutical interventions are appropriate for improvement of sleep quality (e.g. prescription of Ambien®), and that the disclosure described here can support these medical interventions also.

    STATEMENT OF INDUSTRIAL APPLICABILITY



    [0050] The apparatus, system and method of this disclosure finds utility in contactless and minimum contact assessment of quality-of-life indices in clinical and consumer trials, and in interventions to improve the quality of life.


    Claims

    1. A quality-of-life monitoring system for monitoring human subjects, the system comprising:

    one or more contactless sensor units configured to measure physiological data pertaining to a sleep quality of life assessment of the monitored subject;

    an input device configured to capture subjective responses from the monitored subject pertaining to the sleep quality-of-life; and

    a data analysis unit operable to:

    set a target sleep quality of life index for the monitored subject;

    receive, from the input device, the captured subjective responses;

    receive, from the one or more contactless sensors, the measured physiological data;

    analyze the measured physiological data and the captured subjective responses to generate a quantitative sleep quality of life index;

    generate suggested interventions to affect the sleep quality of life index of the monitored subject;

    wherein the suggested interventions comprise increasing the monitored subject's allowed sleep time, if the generated sleep quality of life index is greater than the target sleep quality of life index, and reducing the monitored subject's allowed sleep time, if the generated sleep quality of life index is not greater than the target sleep quality of life index.


     
    2. The monitoring system of claim 1, wherein the one or more contactless sensors are configured to receive a reflected radio-frequency signal reflected off the monitored subject.
     
    3. The monitoring system of any one of claims 1 to 2, wherein the one or more contactless sensors are physiological sensors, and wherein the monitoring system outputs one or more objective measurements of sleep, one or more subjective measurements of sleep, and one or more environmental parameters derived from measurements made by one or more environmental sensors that provide input to the monitoring system.
     
    4. The monitoring system of claim 3, wherein each of said one or more physiological sensors and one or more environmental sensors are arranged at least 50 cm from the monitored subject to provide an open space therebetween.
     
    5. The monitoring system of any one of claims 3 to 4, wherein there is no direct mechanical coupling between the one or more physiological and environmental sensors and the monitored subject.
     
    6. The monitoring system of any one of claims 1 to 5, wherein the measured physiological data comprises at least one of sound, general bodily movement, respiration, heart rate, position and temperature.
     
    7. A method for assessing a sleep quality of life index, the method comprising:

    setting a target sleep quality of life index for a monitored subject;

    measuring a physiological parameter which is related to a quality of life assessment of a monitored subject with one or more no contact or minimal contact sensors;

    collecting subjective responses from the monitored subject about their sleep quality of life;

    analyzing the measured physiological parameters and the collected subjective responses to generate a quantitative sleep quality of life index;

    generating suggested interventions to affect the measured sleep quality of life index of the monitored subject;

    wherein the suggested interventions comprise increasing the monitored subject's allowed sleep time, if the generated sleep quality of life index is greater than the target sleep quality of life index, and reducing the monitored subject's allowed sleep time, if the generated sleep quality of life index is not greater than the target sleep quality of life index.


     
    8. The method of claim 7, wherein the one or more no contact or minimal contact sensors are arranged more than 50 cm from the monitored subject.
     
    9. The method of claim 8, wherein the one or more sensors receive reflected radio-frequency signals reflected off the monitored subject.
     
    10. The method of any one of claims 7 to 9, wherein the suggested interventions comprise outputting suggested interventions that would improve the calculated sleep quality of life index of the monitored subject.
     
    11. The method of any one of claims 7 to 9, wherein the proposed change pertains to a potential change in a pharmaceutical dosing.
     
    12. The method of any one of claims 7 to 11, wherein the objective physiological data comprises at least one of sound, general bodily movement, respiration, heart rate, position and temperature.
     


    Ansprüche

    1. Lebensqualitätsüberwachungssystem zur Überwachung von menschlichen Testpersonen, wobei das System aufweist:

    eine oder mehr kontaktlose Sensoreinheiten, die eingerichtet sind, physiologische Daten zu messen, die eine Bewertung der Schlaflebensqualität der überwachten Testperson betreffen;

    eine Eingabevorrichtung, die eingerichtet ist, die Lebensschlafqualität betreffende, subjektive Antworten von der überwachten Testperson aufzuzeichnen; und

    eine Datenanalyseeinheit, die betreibbar ist, um:

    eine Ziellebensschlafqualitätskennzahl für die überwachte Testperson festzulegen;

    von der Eingabevorrichtung die erfassten subjektiven Antworten zu empfangen;

    von dem einen oder mehr kontaktlosen Sensoren die gemessenen physiologischen Daten zu empfangen;

    die gemessenen physiologischen Daten und die erfassten subjektiven Antworten zu analysieren, um eine quantitative Schlaflebensqualitätskennzahl zu erzeugen;

    Eingriffsvorschläge zu erzeugen, um die Schlaflebensqualitätskennzahl der überwachten Testperson zu beeinflussen;

    wobei die Eingriffsvorschläge das Erhöhen der zulässigen Schlafzeit der überwachten Testperson, falls die erzeugte Schlaflebensqualitätskennzahl größer als die Zielschlaflebensqualitätskennzahl ist, und das Verringern der zulässigen Schlafzeit der überwachten Testperson umfassen, falls die erzeugte Schlaflebensqualitätskennzahl nicht größer als die Zielschlaflebensqualitätskennzahl ist.


     
    2. Überwachungssystem nach Anspruch 1, wobei der eine oder die mehreren kontaktlosen Sensoren eingerichtet sind, ein reflektiertes Radio- bzw. Hochfrequenzsignal zu empfangen, das von der überwachten Testperson reflektiert wurde.
     
    3. Überwachungssystem nach einem der Ansprüche 1 bis 2, wobei der eine oder die mehreren kontaktlosen Sensoren physiologische Sensoren sind, und wobei das Überwachungssystem eine oder mehr objektive Messungen des Schlafs, eine oder mehr subjektive Messungen des Schlafs, und einen oder mehr Umgebungsparameter, die aus Messungen gewonnen werden, die von einem oder mehr Umgebungssensoren durchgeführt werden, die dem Überwachungssystem eine Eingabe bereitstellen, ausgibt.
     
    4. Überwachungssystem nach Anspruch 3, wobei jeder der einen oder mehreren physiologischen Sensoren und einen oder mehreren Umgebungssensoren zumindest 50 cm von der überwachten Testperson entfernt angeordnet sind, um einen offen Raum zwischen diesen bereitzustellen.
     
    5. Überwachungssystem nach einem der Ansprüche 3 bis 4, wobei es keine direkte mechanische Kopplung zwischen dem einen oder mehreren physiologischen Sensoren und Umgebungssensoren sowie der überwachten Testperson gibt.
     
    6. Überwachungssystem nach einem der Ansprüche 1 bis 5, wobei die gemessenen physiologischen Daten Geräusche und/oder allgemeine Körperbewegungen und/oder Atmung und/oder Herzfrequenz und/oder Position und/oder Temperatur aufweisen.
     
    7. Verfahren zur Bewertung einer Schlaflebensqualitätskennzahl, wobei das Verfahren umfasst:

    Festlegen einer Ziellebensschlafqualitätskennzahl für eine überwachte Testperson;

    Messen eines physiologischen Parameters, der eine Bewertung der Lebensqualität einer überwachten Testperson mit einem oder mehreren kontaktlosen Sensoren oder Minimalkontaktsensoren betrifft;

    Sammeln subjektiver Antworten von der überwachten Testperson über deren Schlaflebensqualität;

    Analysieren der gemessenen physiologischen Parameter und der gesammelten subjektiven Antworten, um eine quantitative Schlaflebensqualitätskennzahl zu erzeugen;

    Erzeugen von Eingriffsvorschlägen, um die gemessene Schlaflebensqualitätskennzahl der überwachten Testperson zu beeinflussen;

    wobei die Eingriffsvorschläge das Erhöhen der zulässigen Schlafzeit der überwachten Testperson, falls die erzeugte Schlaflebensqualitätskennzahl größer als die Zielschlaflebensqualitätskennzahl ist, und das Verringern der zulässigen Schlafzeit der überwachten Testperson umfassen, falls die erzeugte Schlaflebensqualitätskennzahl nicht größer als die Zielschlaflebensqualitätskennzahl ist.


     
    8. Verfahren nach Anspruch 7, wobei der einen oder die mehreren kontaktlosen Sensoren oder Minimalkontaktsensoren mehr als 50 cm von der überwachten Testperson entfernt angeordnet werden.
     
    9. Verfahren nach Anspruch 8, wobei der eine oder die mehreren Sensoren reflektierte Radio- bzw. Hochfrequenzsignale empfangen, die von der überwachten Testperson reflektiert werden.
     
    10. Verfahren nach Anspruch 7 bis 9, wobei die Eingriffsvorschläge das Ausgeben von Eingriffsvorschlägen umfassen, die die berechnete Schlaflebensqualitätskennzahl der überwachten Testperson verbessern.
     
    11. Verfahren nach einem der Ansprüche 7 bis 9, wobei die vorgeschlagene Änderung eine potenzielle Änderung in einer pharmazeutischen Dosierung betrifft.
     
    12. Verfahren nach einem der Ansprüche 7 bis 11, wobei die objektiven physiologischen Daten ein Geräusch und/oder allgemeine Körperbewegung und/oder die Atmung und/oder die Herzfrequenz und/oder eine Position und/oder eine Temperatur umfassen.
     


    Revendications

    1. Système de surveillance de la qualité de vie permettant de surveiller des sujets humains, le système comprenant :

    un ou plusieurs ensembles capteurs sans contact conçus pour mesurer des données physiologiques se rapportant à une évaluation de la qualité de vie de sommeil, du sujet surveillé ;

    un dispositif d'entrée conçu pour capturer des réponses subjectives du sujet surveillé se rapportant à la qualité de vie de sommeil ; et

    une unité d'analyse de données ayant pour fonction :

    de définir un indice cible de la qualité de vie de sommeil, pour le sujet surveillé ;

    de recevoir, à partir du dispositif d'entrée, les réponses subjectives capturées ;

    de recevoir, à partir du ou des capteurs sans contact, les données physiologiques mesurées ;

    d'analyser les données physiologiques mesurées et les réponses subjectives capturées afin de produire un indice quantitatif de la qualité de vie de sommeil ;

    de produire des interventions suggérées pouvant affecter l'indice de la qualité de vie de sommeil, du sujet surveillé ;

    les interventions suggérées comprenant l'augmentation du temps de sommeil prévu du sujet surveillé si l'indice produit de la qualité de vie de sommeil est supérieur à l'indice cible de la qualité de vie de sommeil, et la réduction du temps de sommeil prévu du sujet surveillé si l'indice produit de la qualité de vie de sommeil n'est pas supérieur à l'indice cible de la qualité de vie de sommeil.


     
    2. Le système de surveillance de la revendication 1, dans lequel le ou les capteurs sans contact sont conçus pour recevoir un signal de radiofréquence reflété à partir du sujet surveillé.
     
    3. Le système de surveillance de l'une quelconque des revendications 1 à 2, dans lequel le ou les capteurs sans contact sont des capteurs physiologiques, et dans lequel le système de surveillance délivre une ou plusieurs mesures objectives du sommeil, une ou plusieurs mesures subjectives du sommeil, et un ou plusieurs paramètres environnementaux dérivés des mesures effectuées par un ou plusieurs capteurs environnementaux destinés à procurer une entrée au système de surveillance.
     
    4. Le système de surveillance de la revendication 3, dans lequel chaque capteur, parmi le ou les capteurs physiologiques et le ou les capteurs environnementaux, est agencé à au moins 50 cm du sujet surveillé afin d'assurer un espace ouvert entre eux.
     
    5. Le système de surveillance de l'une quelconque des revendications 3 à 4, dans lequel il n'y a pas d'accouplement mécanique direct entre le ou les capteurs physiologiques et environnementaux et le sujet surveillé.
     
    6. Le système de surveillance de l'une quelconque des revendications 1 à 5, dans lequel les données physiologiques mesurées comprennent le son, et/ou le mouvement corporel général, et/ou la respiration, et/ou la fréquence cardiaque, et/ou la position, et/ou la température.
     
    7. Procédé d'évaluation d'un indice de la qualité de vie de sommeil, le procédé comprenant :

    l'établissement d'un indice cible de la qualité de vie de sommeil, pour un sujet surveillé ;

    la mesure d'un paramètre physiologique se rapportant à une évaluation de la qualité de vie d'un sujet surveillé à l'aide d'un ou plusieurs capteurs sans contact ou à contact minimal ;

    la collecte de réponses subjectives du sujet surveillé par rapport à sa qualité de vie de sommeil ;

    l'analyse des paramètres physiologiques mesurés et des réponses subjectives collectées afin de produire un indice quantitative de la qualité de vie de sommeil ;

    la production d'interventions suggérées pouvant affecter l'indice mesuré de la qualité de vie de sommeil, du sujet surveillé ;

    les interventions suggérées comprenant l'augmentation du temps de sommeil prévu du sujet surveillé si l'indice produit de la qualité de vie de sommeil est supérieur à l'indice cible de la qualité de vie de sommeil, et la réduction du temps de sommeil prévu du sujet surveillé si l'indice produit de la qualité de vie de sommeil n'est pas supérieur à l'indice cible de la qualité de vie de sommeil.


     
    8. Le procédé de la revendication 7, dans lequel le ou les capteurs sans contact ou à contact minimal sont agencés à plus de 50 cm du sujet surveillé.
     
    9. Le procédé de la revendication 8, dans lequel le ou les capteurs reçoivent des signaux de radiofréquence reflétés à partir du sujet surveillé.
     
    10. Le procédé de l'une quelconque des revendications 7 à 9, dans lequel les interventions suggérées comprennent des interventions suggérées délivrées pouvant améliorer l'indice calculé de la qualité de vie de sommeil, du sujet surveillé.
     
    11. Le procédé de l'une quelconque des revendications 7 à 9, dans lequel la modification proposée se rapporte à une modification potentielle d'un dosage pharmaceutique.
     
    12. Le procédé de l'une quelconque des revendications 7 à 11, dans lequel les données physiologiques objectives comprennent le son, et/ou le mouvement corporel général, et/ou la respiration, et/ou la fréquence cardiaque, et/ou la position, et/ou la température.
     




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    REFERENCES CITED IN THE DESCRIPTION



    This list of references cited by the applicant is for the reader's convenience only. It does not form part of the European patent document. Even though great care has been taken in compiling the references, errors or omissions cannot be excluded and the EPO disclaims all liability in this regard.

    Patent documents cited in the description




    Non-patent literature cited in the description