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WO2018166795A1 - Surveillance nocturne de l'asthme - Google Patents

Surveillance nocturne de l'asthme Download PDF

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Publication number
WO2018166795A1
WO2018166795A1 PCT/EP2018/054907 EP2018054907W WO2018166795A1 WO 2018166795 A1 WO2018166795 A1 WO 2018166795A1 EP 2018054907 W EP2018054907 W EP 2018054907W WO 2018166795 A1 WO2018166795 A1 WO 2018166795A1
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WIPO (PCT)
Prior art keywords
subject
sleep
monitored
concentration
processor
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Ceased
Application number
PCT/EP2018/054907
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English (en)
Inventor
Jing Su
Declan Patrick Kelly
Cornelis Reinder Ronda
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Koninklijke Philips NV
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Koninklijke Philips NV
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Publication date
Priority claimed from EP17170699.7A external-priority patent/EP3401817A1/fr
Application filed by Koninklijke Philips NV filed Critical Koninklijke Philips NV
Priority to CN201880018053.2A priority Critical patent/CN110603601B/zh
Publication of WO2018166795A1 publication Critical patent/WO2018166795A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Definitions

  • the present invention relates to a sleep monitoring system and method for detecting asthma symptoms during the sleep of a subject, as well as to a computer program product for implementing such a method.
  • asthma An example of such a sleep disorder is disrupted sleep though the onset of asthma symptoms including wheezing, shortness of breath and coughing, which may be caused by bronchospasms and variable degrees of inflammation of the airways of the lungs.
  • wheezing wheezing, shortness of breath and coughing
  • bronchospasms variable degrees of inflammation of the airways of the lungs.
  • Such nocturnal asthma symptoms have been associated with increased mortality and decreased quality of life, for example due to the poor quality of sleep experienced by the patient.
  • the patient may be presented with a questionnaire such as the asthma control test (ACT), which includes questions about night time sleep disruption due to the asthma over a period of time, typically four weeks.
  • ACT asthma control test
  • US 2016/0249838 Al discloses a system and method to detect a possible respiratory blockage by using personalized carbon dioxide (C0 2 ) concentration change patterns to prevent deaths by respiratory blockage such as by choking or asthma.
  • Blood C0 2 levels are monitored through a skin-mount patch including a non-dispersive infrared sensor and a warning signal is generated if these levels become abnormally high.
  • this solution is considered non-ideal for a number of reasons. Firstly, some patients may find it uncomfortable to wear such a patch whilst sleeping, as they find that the sensation of having to wear the patch disrupts their sleep.
  • this prior art system is not adapted to provide an overall quality of sleep indication as a function of the onset of asthma symptoms during the sleeping period, as the system is incapable of determining whether the patient is awake or asleep.
  • US 2016/0228037 Al discloses a device and method for assessing an asthma status of a subject including monitoring a breath related parameter of a subject suffering from asthma, comparing the breath related parameter to a baseline parameter of the subject;
  • the breath related parameter may be a C0 2 level in the inhaled and exhaled breath, which may be monitored using a capnograph. This again requires the patient to wear such a sensor, typically clipped to the nose, which may be perceived as being uncomfortable.
  • the present invention seeks to provide a sleep monitoring system that is capable of monitoring the effects of asthma symptoms during the sleep of a patient being monitored in an unobtrusive manner.
  • the present invention further seeks to provide a method of detecting asthma symptoms during the sleep of the subject being monitored in an unobtrusive manner.
  • a sleep monitoring system for detecting asthma symptoms during the sleep of a subject in a confined space
  • the system comprising a C0 2 sensor and a processor communicatively coupled to the C0 2 sensor, wherein the processor is adapted to monitor a change in a C0 2 concentration in a part of the confined space in close vicinity to the subject being asleep from sensor data produced by the C0 2 sensor over a monitoring period such that the change in the C0 2 concentration caused by exhalation of C0 2 by the subject into said part of the confined space is monitored before the exhaled C0 2 diffuses into the total volume of the confined space; compare the monitored change of the C0 2 concentration in said part of the confined space against a benchmark for said subject; and identify an asthma symptom exhibited by said subject if the monitored change of the C0 2 concentration in said part of the confined space exceeds the benchmark for said subject for at least part
  • the present invention is based on the insight that the amount of C0 2 expelled by a subject, i.e. a person, which is a function of the state of activity of that subject, can not only be used to accurately determine whether the subject is awake or asleep, but can further distinguish between normal sleep, i.e. sleep in which the subject does not suffer from asthma symptoms, and abnormal sleep, i.e. sleep in which such asthma symptoms compromise the sleep efficiency of the subject.
  • asthma symptom information can be derived during the subject's sleep without having to contact the subject being monitored, thereby providing clinical data with improved accuracy compared to self-reporting of asthma symptoms by the subject (patient) such that the subject's asthma can be controlled more accurately based on the provided asthma symptom information.
  • an important insight on which the present invention is based is that the C0 2 levels exhaled by the subject may be accurately measured without the subject having to wear a C0 2 monitor such as a capnograph, thereby reducing the risk that the C0 2 monitoring interferes with the ability of the subject to have an uninterrupted sleep, as such body worn monitors are typically experienced as being uncomfortable.
  • the sleep monitoring system preferably further comprises a monitoring result reporting device communicatively coupled to the processor and adapted to generate a report of said monitoring period, said report including an indication of identified asthma symptoms in order to report the monitoring result to a user of the system.
  • a monitoring result reporting device may be omitted, for example in a scenario where the sleep monitoring system provides those results to a remote device for interpretation, e.g. over a network such as the Internet in which case the monitoring results may be remotely interpreted, such as by a trained professional.
  • the processor further is adapted to sample the sensor data at a defined sampling frequency of at least 0.1 Hz.
  • a defined sampling frequency of at least 0.1 Hz.
  • changes in C0 2 concentration indicative of an asthma symptom occurring over a short period of time e.g. concentration changes caused by coughing or shortness of breath
  • the processor may be adapted to identify an asthma symptom in the form of a cough of the subject if a monitored change in said C0 2 concentration between at least two contiguous sensor data samples exceeds the benchmark by at least a defined amount.
  • the sleep monitoring system may further comprise a counter adapted to count the number of identified asthma symptoms during the monitoring period.
  • the counter may count of the number of detected coughs during the sleep monitoring period, which may provide clinically relevant information about the severity of the asthma symptoms the subject being monitored suffers from.
  • the sleep monitoring system is operable in a calibration mode in which the benchmark for the subject is obtained. This further improves the accuracy of the sleep monitoring system compared to systems in which predefined benchmarks, e.g. benchmarks based on at least one of age, gender, weight and size, are being utilized.
  • the monitoring period is defined by a first time period initiated by a first indication that the subject is attempting to sleep and terminated by a second indication that the subject is getting up; and wherein the processor is adapted to determine a sleep efficiency of the subject during the monitoring period by identifying an awake time period of the subject when a rate of increase in the monitored C0 2 concentration is greater than a first threshold; identifying a light sleep time period of the subject when a rate of increase in the monitored C0 2 concentration is between the first threshold and a second threshold; and identifying a deep sleep phase of the subject when a rate of increase in the monitored C0 2 concentration is below the second threshold.
  • This for example facilitates evaluation of the sleep efficiency of the subject being monitored, as well as the impact of the asthma symptoms on this sleep efficiency.
  • the processor may be further adapted to determine a cause for the subject being awake from a plurality of causes each having a characteristic rate of increase in C0 2 by the subject by evaluating a rate of increase in the monitored C0 2 concentration during a time period immediately preceding the awake time period.
  • the sleep monitoring system can distinguish between 'normal' waking up and waking up caused by discomfort associated with the onset of asthma symptoms, which information may be utilized in determining the sleep efficiency of the monitored subject.
  • the processor may be adapted to differentiate between causes for waking up including normal waking up and asthma symptoms including coughing, shortness of breath and wheezing.
  • the sleep monitoring system further comprises at least one further sensor communicatively coupled to the processor, wherein the processor is adapted to identify the asthma symptoms based on respective sensor data from the C0 2 sensor and the at least one further sensor.
  • the sleep monitoring system is configured to determine a sleep efficiency metric for the subject, where the sensor data provided by the further sensor may be used to determine the point in time at which the subject begins the attempt to fall asleep or to determine the point in time at which the subject wakes up.
  • the further sensor may be a light sensor, a sound sensor or a user interface sensor.
  • the sleep monitoring system further comprises an asthma medication release device responsive to the processor.
  • asthma medication may be automatically released in the proximity of the subject being monitored upon detection of asthma symptoms, thereby improving the management of the condition and reducing the risk of serious complications developing from the onset of these symptoms.
  • the sleep monitoring system may be provided as a single unit, stand-alone apparatus or the sleep monitoring system may be at least partially comprised by an air conditioning apparatus, an air purification apparatus, a respirator apparatus or a
  • the sleep monitoring system alternatively or additionally may be realized by a distributed architecture in which the sleep monitoring system comprises a first device comprising the CO 2 sensor and a second device comprising the processor, the first device and the second device each comprising a wireless communication module for establishing a wireless communication link between the first device and the second device, wherein the second device is a wearable device or a mobile communication device.
  • a method of detecting asthma symptoms during the sleep of a subject in a confined space comprising periodically receiving sensor data indicative of a CO 2 concentration in a part of the confined space in close proximity to the subject being asleep during a monitoring period such that the change in the C0 2 concentration caused by exhalation of C0 2 by the subject into said part of the confined space is monitored before the exhaled C0 2 diffuses into the total volume of the confined space; monitoring the C0 2 concentration over said monitoring period; comparing a change in the monitored C0 2 concentration in said part of the confined space against a benchmark for said subject; and identifying an asthma symptom exhibited by said subject if the monitored change of the C0 2 concentration in said part of the confined space exceeds the benchmark for said subject for at least part of said monitoring period.
  • Such a method facilitates the monitoring of asthma during the sleep of a subject such as a child (or adult) without having to physically contact the subject, thereby providing an unobtrusive manner of obtaining accurate data regarding the onset of asthma symptoms during sleep of the subject being monitored.
  • the method preferably further comprises determining a sleep efficiency of the subject during the monitoring period by identifying an awake time period of the subject when a rate of increase in the monitored C0 2 concentration is greater than a first threshold;
  • determining of said sleep efficiency further comprising determining a cause for the subject being awake by evaluating a rate of increase in the monitored C0 2 concentration during a time period immediately preceding the awake time period from a set of causes including normal waking up and asthma symptoms including coughing, shortness of breath and wheezing, such that the overall effect of the asthma symptoms on the quality of sleep of the monitored subject can be determined.
  • a computer program product comprising a computer readable storage medium having computer readable program instructions embodied therewith for, when executed on a processor of a sleep monitoring system of any of the herein described embodiments, cause the processor to implement the method according to embodiments of the present invention.
  • FIG. 1 schematically depicts a sleep monitoring system according to an embodiment
  • FIG. 2 is a graph depicting typical human ventilation volumes associated with different states of awareness
  • FIG. 3 is a graph depicting measured indoor C0 2 levels for a room in which a person is active
  • FIG. 4 is a graph depicting measured indoor C0 2 levels for a room in which a person is awake but resting;
  • FIG. 5 is a graph depicting measured indoor C0 2 levels for a room in which a person is asleep
  • FIG. 6 is a block diagram schematically depicting the various sleep phases during a typical sleep cycle of a person
  • FIG. 7 is a graph depicting the effects of a subject's coughing on C0 2 emissions in a location within a space proximal to the subject;
  • FIG. 8 is a flowchart of a method according to an example embodiment
  • FIG. 9 is a flowchart of an aspect of the method of FIG. 8 in more detail.
  • FIG. 10 schematically depicts a sleep monitoring system according to another embodiment.
  • FIG. 11 schematically depicts a sleep monitoring system according to yet another embodiment.
  • FIG. 1 schematically depicts a sleep monitoring system 10 according to an embodiment.
  • the sleep monitoring system 10 is adapted to monitor the sleep of a subject in a confined space such as a bedroom in which a sensor device 20 of the sleep monitoring system 10 is positioned.
  • the sensor device 20 at least comprises a C0 2 sensor 21 and may comprise one or more further sensors 23, which may include a light sensor, a sound sensor, e.g. a microphone, a user input sensor, e.g. a user interface, and so on.
  • the sensor device 20 may be a stand-alone device, e.g. a sensor box or the like that may be positioned in close vicinity to the subject to be monitored.
  • the sensor device 20 may be dimensioned such that it can be clipped or otherwise secured to a bed, e.g. to a headboard of the bed, in which the subject sleeps, such that a change in the C0 2 concentration caused by exhalation of C0 2 by the subject can be accurately monitored with the sensor device 20 before the C0 2 diffuses into the total volume of air within the confined space in which the sensor device 20 is positioned, e.g. a bedroom in which the subject sleeps.
  • the sensor device 20, or at least the C0 2 sensor 21, should be positioned such that accurate monitoring of fluctuations in C0 2 levels local to the subject being monitored as caused by the subject's breathing is facilitated.
  • the C0 2 sensor 21 may be positioned within 30 cm from the subject's mouth and nose although other suitable distances may be possible, e.g. depending on the ventilation conditions within the room in which the subject is located.
  • the sensor device 20 may form part of an apparatus adapted to alter the condition of the atmosphere within the confined space as will be explained in more detail below.
  • an apparatus may be adapted to adjust at least one of the purity, humidity, temperature and scent level in the atmosphere (air) in the confined space.
  • Such functionality for example may be included in an air purification apparatus, an air conditioning apparatus, an air humidification apparatus, a scent release apparatus or any apparatus that includes one or more of the above functionality.
  • the sleep monitoring system 10 typically comprises a computing device 30 including a processor 31.
  • the computing device 30 may be a separate device to the sensor device 20.
  • the computing device 30 may be any suitable computing device, such as a personal computer, e.g. a desktop computer or a laptop computer, a tablet computer, a personal digital assistant, a mobile communication device such as a smartphone, a wearable smart device such as a smart watch, and so on.
  • the computing device 30 may form an assembly with the sensor device 20. In such an assembly, the computing device 30 may be a discrete entity or may form part of an apparatus adapted to alter the condition of the atmosphere within the confined space, i.e. such an apparatus may comprise the processor 31.
  • the processor 31 may be any suitable processor, e.g. a generic processor or an application- specific processor.
  • the computing device 30 may further comprise a data storage device 33 communicatively coupled to the processor 31.
  • the computing device 30 is arranged to communicate with the sensor device 20 to obtain C0 2 levels in the confined space in which the subject is located as determined with the C0 2 sensor 21.
  • the C0 2 sensor 21 and the further sensor(s) 23 if present are communicatively coupled to the computing device 30 over a communication link 25 such that the processor 31 can receive sensor readings from such sensors.
  • a communication link may be a wired communication link, e.g. in case the sensors 21, 23 are integral to the computing device 30, or may be a wireless communication link, e.g. in case the sensors 21, 23 are located in a different device to the computing device 30, e.g. in a separate sensor device 20.
  • the respective devices communicatively coupled over such a wireless communication link may include a wireless transceiver (not shown).
  • the devices may communicate with each other through their respective wireless transceivers using any suitable wireless communication protocol, e.g. Bluetooth, Wi-Fi, a mobile communication protocol such as 2G, 3G, 4G or 5G, a suitable near-field communication (NFC) protocol or a proprietary protocol.
  • the respective devices may communicate directly with each other or may communicate with each other through an intermediary such as a wireless bridge, a router, a hub, and so on. Any suitable embodiment of wired or wireless communication between such respective devices may be contemplated.
  • the processor 31 may be further communicatively coupled to a data storage device 33, here shown to form part of the computing device 30.
  • a data storage device may be any suitable device for storing digital data, e.g. a random access memory, a cache memory, a Flash memory, a solid state storage device, a magnetic storage device such as hard disk, an optical storage device and so on.
  • the data storage device 33 may be separate from the computing device 30, e.g. a network storage device or a cloud storage device accessible to the processor 31 over a network such as a LAN or the Internet.
  • the processor 31 may store sensor data received from the connected sensors 21, 23 in the data storage device in order to collect and store historical sleep information obtained for the subject in the confined space, for example to analyze the sleep efficiency of that subject as will be explained in more detail below.
  • the computing device 30 further comprises a monitoring result reporting device 35 under control of the processor 31.
  • a monitoring result reporting device 35 may be any device that capable of producing an output that can be detected by one of the human senses.
  • the device 35 may be adapted to produce a visible or audible output.
  • the processor 31 may be adapted to generate a control signal indicative of a determined sleep efficiency of the subject with the processor 31, which control signal triggers the device 35 to produce a sensory output indicating the determined sleep efficiency.
  • the monitoring result reporting device 35 may comprise a display adapted to display the determined sleep efficiency (or sleep efficiency history) of the subject, and/or any data pertaining to monitored asthma symptoms during the sleep of the subject being monitored as will be explained in further detail below.
  • FIG. 2 provides proof of concept of the ability to detect different states of awareness, i.e. a distinction between a subject being awake or asleep.
  • FIG. 2 depicts a graph in which three sleep phases are identified. Phase I is awake, phase II is a transition to a state of sleep and phase III is a state of sleep, with the X-axis displaying time (in minutes) and the Y-axis displaying ventilation of the subject (in 1/min).
  • This graph therefore clearly depicts a distinct decrease in ventilation (breathing) volumes upon the subject going from a state of being awake to a state of being asleep. Consequently, the amount of C0 2 expelled going from a state of being awake to a state of being asleep is therefore also reduced.
  • the monitored amount of C0 2 expelled by a subject under monitoring during a unit period of time can be used as an indicator of whether the subject is awake or asleep. For example, if the amount of C0 2 expelled during such a unit period of time exceeds a defined threshold, this may be considered indicative of the subject being awake, whereas if the amount of C0 2 expelled during such a unit period of time falls below this defined threshold, this may be considered indicative of the subject being asleep.
  • FIG. 3-5 The feasibility of using the monitoring of C0 2 levels to monitor the sleep of a subject is further demonstrated by FIG. 3-5, in which the levels of C0 2 expelled by a subject during exercise (FIG. 3), rest (FIG. 4) and sleep (FIG. 5) were monitored with a C0 2 sensor over a period of time within the same confined space (i.e. a space having a constant volume of 29.25 m 3 ), with hermetically sealed windows and doors to minimize the loss of C0 2 from the confined space.
  • the monitored C0 2 levels translated into a rate of C0 2 increase of 16.5 ppm/min.
  • a rest state i.e.
  • the monitored C0 2 levels translated into a rate of C0 2 increase of 3.0 ppm/min, whereas in a sleep state of the subject, the monitored C0 2 levels translated into a rate of C0 2 increase of 1.6 ppm/min.
  • a person in a light state of sleep produces a higher volume of ventilation (breathing) per unit time compared to a person in a deep state of sleep
  • a distinction between a light sleep and a deep sleep of a monitored subject may also be made by monitoring a rate of increase of C0 2 levels in the confined space and comparing the determined rate of increase of C0 2 levels in the confined space against a further defined threshold, with a light sleep being detected when the determined rate of increase of C0 2 levels in the confined space is above the further defined threshold and a deep sleep being detected when the determined rate of increase of C0 2 levels in the confined space is below the further defined threshold.
  • the sleep monitoring system 10 may be configured to determine a particular physical state of the monitored subject in accordance with Table 1 (threshold 1 being higher than threshold 2):
  • threshold 1 and threshold 2 will depend from a number of factors, such as such as volume of the confined space, bodyweight and/or lung capacity of the monitored subject, rate of loss of C0 2 from the confined space, and so on.
  • the respective thresholds to be applied by the sleep monitoring system 10 may be obtained through calibration of the system. This may be achieved in any suitable manner.
  • at least the sensor device 20 of the sleep monitoring system 10 may be placed within the confined space and used to monitor the subject over a period of time, e.g. during a night, in which the subject sleeps within the confined space.
  • the data collected with the sensor device 20 may be evaluated to identify typical changes in the rate of increase of C0 2 levels within the confined space, which typical changes will be indicative of a change in physical state of the subject, e.g. a transition from a state of being awake to a state of light sleep or a transition from a state of light sleep to a state of deep sleep. Consequently, the various physical states can be readily identified in the collected data, such that the applicable values of Threshold 1 and Threshold 2 associated with (transitions between) these various physical states can be readily derived from the collected data. In order to improve the accuracy of the thus extracted thresholds, the data collection during calibration may be repeated a number of times, e.g. over a number of nights.
  • the sleep monitoring system 10 may have a calibration mode that can be user-activated.
  • the sleep monitoring system 10 may comprise a user interface, e.g. on the sensor device 20 or the computing device 30 that allows the user to activate the calibration mode, e.g. after installation of the sensor device 20 in the vicinity of the location in which the subject to be monitored intends to sleep.
  • the sleep monitoring system 20 is adapted to determine the sleep efficiency of the subject being monitored.
  • the sleep efficiency SE may be defined as follows:
  • ATtotai is the total time the subject is attempting to sleep
  • AT s i ee p is the total time the subject actually is asleep.
  • ⁇ ⁇ ⁇ may be defined as a first time period initiated by an indication that the subject is attempting to sleep and terminated by an indication that the subject is getting up.
  • the indication that the subject is getting up typically follows an indication that the subject has been asleep although this is not strictly necessary; for example in a scenario where the subject did not manage to sleep at all, such an indication of the subject being asleep would not be obtained.
  • the total time AT tot ai may be determined in a number of ways.
  • the start point of this period may be determined by collecting an indication with a further sensor 23 that the subject is attempting to sleep.
  • This for example may be a pressure sensor for detecting the subject entering the bed, which pressure sensor for instance may be attached to a pillow or mattress or the like.
  • the further sensor 23 may be a light sensor that detects a change in light level in the confined space.
  • the subject may provide a user input on a user input sensor 23 of the sensor device 20, e.g. on the user interface, to provide a particularly accurate indication of the subject initiating attempting to sleep.
  • the endpoint of the time period ⁇ ⁇ ⁇ may be determined in a similar manner, for example by detecting an alarm going off, by the subject switching on a light, from an increase in the rate at which C0 2 is expelled by the subject is determined with the C0 2 sensor 21, and so on.
  • ⁇ 8 ⁇ may be defined as a second time period initiated by an indication that the subject is asleep and terminated by an indication that the subject is awake that follows the indication that the subject is asleep.
  • the subject may experience a number of periods during which the subject is asleep.
  • the total period AT s i ee p that the subject was asleep may be obtained by summing all periods during which it was determined that the subject was asleep.
  • the total time AT s i ee p may be determined using the C0 2 sensor data collected with the sensor device 20.
  • the sensor device 20 may periodically sample the C0 2 levels in the confined space in which the subject is attempting to sleep, which periodic data may be used to determine the total time AT s ieep.
  • the total time AT s i ee p may be determined by counting the number of data points in the periodic data for which the rate of increase of the C0 2 level relative to the previously captured data point was below Threshold 1.
  • Threshold 1 Threshold
  • the sleep monitoring system 10 may be further refined, for example to factor in scenarios in which the monitored subject temporarily leaves the bed, e.g. for a toilet break or the like.
  • the sleep monitoring system 10 for example may be configured to continue determining the time period ⁇ ⁇ ⁇ if it is determined that the subject returns to bed within a defined period of time. This may be determined in any suitable manner, e.g. using sensor data provided by the C0 2 sensor 21 and/or one or more of the further sensors 23 as previously explained. Other refinement approaches will be apparent to the skilled person.
  • the sleep monitoring system 10 is further adapted to calculate the sleep onset latency (SOL) for the monitored subject.
  • the sleep onset latency may be defined as the time period between the point in time at which the subject attempts to go to sleep and the point in time at which the subject actually falls asleep.
  • the point in time at which the subject attempts to go to sleep and the may be determined the point in time at which the subject actually falls asleep may be determined as previously explained.
  • the sleep monitoring system 10 may be adapted to provide an indication of the calculated sleep efficiency SE, optionally including an indication of the sleep onset latency SOL, on the sensory output device 35 such that the monitored subject may be made aware of his or her sleep efficiency.
  • the sensory output device 35 may be included in a computing device 30 that is portable, e.g. a tablet device or mobile communications device such as a smart phone, or wearable device, e.g. a smart watch or the like that may be worn by the monitored subject during sleep.
  • a computing device 30 that is portable, e.g. a tablet device or mobile communications device such as a smart phone, or wearable device, e.g. a smart watch or the like that may be worn by the monitored subject during sleep.
  • a short range wireless communication between the sensor device 20 and the computing device 30 may be deployed, e.g. NFC or Bluetooth, which may be beneficial in terms of energy efficiency.
  • the sleep monitoring system 10 may be adapted to build a history of sleep efficiencies to allow evaluation of the sleep history of the subject to be monitored.
  • the processor 31 may be adapted to store sleep monitoring data and/or a sleep efficiency calculated from the sleep monitoring data in the data storage device 33.
  • the sleep monitoring system 10 may comprise a display as the sensory output device 35 on which the sleep history stored in the data storage device 33 may be displayed. In this manner, a history of the sleep efficiency of the monitored subject may be displayed and evaluated, which may provide valuable insights into typical sleep behaviors of the monitored subject. Such insights for instance may be used to determine if certain physical symptoms of the monitored subject may be explained by the sleep efficiency of the monitored subject over a period of time.
  • the sleep monitoring system 10 is further configured to determine asthma symptoms during the sleep period of the subject being monitored.
  • asthma symptoms broadly can be categorized in three different categories; coughing, shortness of breath and wheezing, each of which can be categorized by abnormal and distinguishable increases in C0 2 emissions by the subject being monitored by the system 10 as will be explained in more detail below.
  • FIG. 7 is a graph depicting the monitoring of C0 2 levels (y-axis, in PPM) within a confined space (here an office) over time (x-axis, in seconds) in which a subject is present.
  • the spikes at t ⁇ 110s and t ⁇ 510s are characteristic of a sudden increase in C02 levels within the monitored space caused by the subject coughing.
  • the processor 31 preferably is configured to sample the sensor data are provided by the C0 2 sensor 21 at least every 10 seconds, i.e. at a sample rate of at least 0.1 Hz, such that such transient sharp increases in C0 2 levels within the monitored space can be accurately detected by the sleep monitoring system 10.
  • the processor 31 may be configured to determine that an increase in C0 2 levels is to be interpreted as a coughing event when the monitored change in the C0 2 concentration between at least two contiguous sensor data samples exceeds a benchmark by at least a defined amount.
  • the sleep monitoring system 10 may further comprise a counter (not shown) in which the detected asthma symptoms, e.g. the number of coughing events, during the sleep of the subject being monitored are counted. This count for example may be used to quantify the severity of an asthma attack during the sleeping period of the monitored subject, and/or may be used in the determination of the sleep efficiency of the monitored subject as will be explained in further detail below.
  • the aforementioned benchmark utilized by the processor 31 typically is a personalized benchmark for the said subject.
  • the personalisation of the benchmark may be achieved in some embodiments by a user of the sleep monitoring device 10 selecting a particular benchmark from a plurality of pre-stored benchmarks through a user interface of the sleep monitoring system 10, for example by specifying one or more identifiers of the subject to be monitored such as age, gender, weight, height, lung capacity, and so on, based on which an appropriate pre-stored benchmark may be selected by the processor 31 for use in the monitoring of the subject.
  • the benchmark may be obtained in a calibration mode of the sleep monitoring system 10 as previously explained.
  • Such a benchmark for example may define changes in C0 2 concentration over time within the space in which the target subject is being monitored caused by the subject exhibiting normal breathing behaviour.
  • the benchmark may define the expectation value of changes in C0 2 concentration over time when the target subject is breathing normally whilst being awake, as the changes in the C0 2 concentration over time as caused by the onset of asthma symptoms typically causes the amounts of C0 2 emitted by the monitored subject to exceed the amounts of C0 2 emitted by the subject during normal breathing whilst awake.
  • asthma sufferers tend to brief through their mouths rather than their noses when suffering from an asthma attack, which typically is accompanied by an increased rate of breathing due to the fact that the breathing is more shallow compared to normal breathing. It is well-known per se in medical science that asthma sufferers suffer from chronic
  • the monitoring system 10 may be configured to count the number of fluctuations in the monitored C0 2 concentration over a defined period of time, e.g. to establish a pattern in the C0 2 signal obtained from the sensor 21 , which pattern may be evaluated to determine the type of asthma symptom.
  • the measured number N fluctuations in the monitored C0 2 concentration corresponds to the various asthma symptoms as follows: N (Shortness of breath) > N (Coughing) > N
  • the various d[C0 2 ]/dt thresholds or count (N) thresholds for establishing the particular types of asthma symptoms may be obtained through calibration or machine learning.
  • the sleep monitoring system 10 is adapted to implement a method of detecting asthma symptoms during the sleep of a subject within the context of determining the sleep efficiency of the monitored subject.
  • a flowchart of an example embodiment of such a method 100 is depicted in FIG. 8.
  • the method 100 starts in operation 110, e.g. by switching on the sleep monitoring system 10, after which the processor 31 monitors the sensor data provided by the C0 2 sensor 21 and one or more further sensors 23 if present to determine whether the monitored subject is awake or asleep, which is checked in operation 130.
  • Such monitoring of the sensor data by the processor 31 may be achieved in any suitable manner, e.g. periodically with any suitable periodicity such as at least once every 10 seconds as previously mentioned.
  • the determination of whether the subject is awake or asleep and the determination of the sleep efficiency and related parameters such as sleep onset may be determined as explained in more detail above.
  • the method 100 proceeds to operation 170 in which it is checked whether the monitoring period has lapsed. If this is not yet the case, the method 100 reverts back to previously explained operation 120. Otherwise, the method 100 proceeds to operation 180 in which the overall sleep efficiency of the monitored subject may be calculated as explained in more detail above before terminating in 190.
  • the method 100 proceeds to operation 140 in which the sleep level, e.g. normal sleep phases such as light sleep or deep sleep, or asthma affected sleep phases including sleep phases affected by coughing, shortness of breath or wheezing, is determined.
  • the sleep level e.g. normal sleep phases such as light sleep or deep sleep, or asthma affected sleep phases including sleep phases affected by coughing, shortness of breath or wheezing.
  • Such monitoring may be continued as symbolically represented by operation 150 until the monitored subject wakes up or until the monitoring period during which the sleep monitoring system monitors the subject has completed.
  • the method 100 optionally may comprise further operation 160 in which the cause for the subject waking up is determined. This is further explained with the aid of the flowchart in FIG. 9. Specifically, the processor 31 may evaluate a rate of increase in monitored C0 2 levels during a time interval
  • the processor 31 may compare the rate of increase in monitored C0 2 levels in this time interval against a first threshold indicative of shortness of breath in operation 162 such that if the monitored C0 2 levels at least meet this first threshold, the processor terminates in 163, which defines the reason for waking up as being caused by shortness of breath.
  • the processor 31 may compare the rate of increase in monitored C0 2 levels in this time interval against a second threshold indicative of coughing in operation 164 such that if the monitored C0 2 levels at least meet this second threshold, the processor terminates in 165, which defines the reason for waking up as being caused by coughing. If the rate of increase in monitored C0 2 levels also lie below this second threshold, the processor 31 may compare the rate of increase in monitored C0 2 levels in this time interval against a third threshold indicative of wheezing in operation 166 such that if the monitored C0 2 levels at least meet this third threshold, the processor terminates in 167, which defines the reason for waking up as being caused by wheezing.
  • the processor 31 determines that the waking up of the monitored subject was not caused by the onset of asthma symptoms and consequently terminates in 169, indicating 'normal' waking up, i.e. waking up for non- asthma related reasons of the monitored subject.
  • the sleep monitoring system 100 can build up a record of the number of asthma events and their duration during the sleep of the monitored subject, from which the deterioration of the sleep efficiency of the monitored subject can be quantified in any suitable manner.
  • Such information for example may be used by the subject or a medical consultant of the subject to evaluate the efficiency of an actual treatment regime and to adjust the treatment regime accordingly, e.g. increase the dosage and/or administration frequency of already used asthma medication, or to supplement or replace the already used asthma medication with new medication to suppress the onset of asthma symptoms during the sleep of the monitored subject.
  • the determination of the sleep efficiency may benefit from the determination of the number of times the monitored subject wakes up during the monitoring period as well as the reasons for the monitored subject waking up as previously explained with the aid of FIG. 9 and its detailed description, e.g. by counting the number of occasions the monitored subject has woken up because of nocturnal asthma symptoms.
  • the overall sleep efficiency may be expressed as the ratio between the total time asleep over the total monitoring period, e.g. the period in which the subject was in bed and trying to sleep.
  • a decreased sleep efficiency figure may also be derived based on the difference between the sleep efficiency without asthma disturbance and the overall sleep efficiency, each of which may be derived from the monitored data in a straightforward manner using the teachings of the present invention as described in this application.
  • the monitoring results may be made available either to a remote monitor or on the monitoring result reporting device 35.
  • Any useful results may be presented in any suitable manner.
  • Non-limiting examples of useful results include sleep efficiency, wake time, sleep disturbance time caused by asthma, a quantification in terms of ranking of the sleep quality, e.g. on a scale of 1-5, with an increasing score indicative of higher sleep quality, and so on.
  • such monitoring results may be supplemented by proposed suggestions to improve the sleep of the monitored subject, such as suggestions in adjusting asthma medication (for which the system may suggest that the subject discusses such adjustments with a medical professional where appropriate), the installation or use of devices that can reduce concentrations of airborne triggers of asthma, e.g. air purification devices or the like, and so on.
  • the sleep monitoring system 10 further comprises an asthma medication release device 40 responsive to the processor 31.
  • the asthma medication release device 40 may be an aerosol releasing device or the like adapted to release a flow 41 of the asthma medication in the direction of the mouth of the monitored subject, such that the processor 31 when detecting the onset of an asthma symptom in the monitored C0 2 data as previously explained can control the asthma medication release device 40 to release the asthma medication towards the monitored subject in order to automatically the asthma symptoms of the monitored subject.
  • the dosage of the asthma medication released by the asthma medication release device 40 may be based on the particular asthma symptom detected with the processor 31.
  • the released dosage may be higher when the monitored subject suffers from shortness of breath or is wheezing compared to when the monitored subject is coughing as in the latter scenario the breathing of the monitored subject typically is less shallow, such that a smaller dosage of the asthma medication may suffice in effectively treating the asthma.
  • the processor 31 may be responsive to a further sensor 23 adapted to detect a breathing cycle of the monitored subject, e.g. a motion sensor, camera or the like from which it may be determined whether the monitored subject is breathing in or out, such that the processor 31 can trigger the release of the asthma medication by the asthma medication release device 40 at the appropriate point in time such that the asthma medication reaches the monitored subject at the start of the subject breathing in air during the breathing cycle in order to maximize the fraction of the delivered asthma medication being inhaled by the monitored subject.
  • a further sensor 23 adapted to detect a breathing cycle of the monitored subject, e.g. a motion sensor, camera or the like from which it may be determined whether the monitored subject is breathing in or out, such that the processor 31 can trigger the release of the asthma medication by the asthma medication release device 40 at the appropriate point in time such that the asthma medication reaches the monitored subject at the start of the subject breathing in air during the breathing cycle in order to maximize the fraction of the delivered asthma medication being inhaled by the monitored subject.
  • FIG. 11 schematically depicts an example embodiment of a sleep monitoring system 10 embodied by an air purification apparatus having an air inlet 53, an air outlet 55 and an air purification path 51, e.g. a fluid conduit, extending between the air inlet 53 and the air outlet 55.
  • a fan 50 may be located in the air purification path 51 to control the flow rate of air through the air purification path 51.
  • the fan 50 may be controlled by the processor 31 integral to the air purification apparatus.
  • the processor 31 may be adapted to control a speed of the fan 50 in response to the detection of a particular sleep phase of the subject to be monitored, for example to maintain a desirable atmosphere within the space in which the subject is located.
  • the sensor device 20 is integral to the air purification apparatus and in addition to the previously described C0 2 sensor 21 and the one or more further sensors 23 may further comprise one or more additional sensors 25 for monitoring a pollution level in the air entering the air purification apparatus through the air inlet 53.
  • the processor 31 may be further adapted to regulate the fan speed of the fan 50 in response to sensor data provided by the one or more additional sensors 25 to ensure that the air quality in the confined space in which the air purification apparatus is placed is appropriately regulated.
  • sensor-based fan speed regulation is well-known per se, this is not further explained for the sake of brevity only.
  • the air purification apparatus further comprises one or more pollutant removal structures 110, e.g. filters or the like, as is well-known per se. This will therefore not be further explained for the sake of brevity only.
  • the air purification apparatus may further comprise an asthma medication delivery device 44 delivering a flow 41 including an asthma medication as previously explained. It will be immediately understood by the skilled person that although such an integral sleep monitoring system 10 is explained in more detail for an air purification apparatus, it is equally feasible to implement such an integral sleep monitoring system 10 in similar air treatment apparatuses such as air conditioners, air humidifiers, respirator devices, and so on.
  • embodiments of the sleep monitoring system 10 may also be used in a confined space in which multiple subjects are sleeping. For example, in such a scenario multiple sleep monitoring systems with (C0 2 ) sensing capability local to a particular subject may be deployed. Alternatively, a single sleep monitoring system 10 comprising multiple sensors which may be deployed local to a particular subject to be monitored may be contemplated. Although embodiments of the present invention are described in the context of C0 2 monitoring, it should be understood that alternative embodiments in which another gas affected by ventilation (breathing), e.g. 0 2 , may be monitored, e.g. to support or replace C0 2 monitoring data.
  • another gas affected by ventilation e.g. 0 2
  • VOC volatile organic compound
  • Other sensors that may be advantageously deployed to monitor sleep disorders and the onset of asthma symptoms include volatile organic compound (VOC) sensors, which for example may be deployed as the further sensors 23 to supplement the data obtained with the C0 2 sensor 21.
  • VOC volatile organic compound
  • Aspects of the present invention may be embodied as sleep monitoring system 10 and a method 100 for monitoring the sleep of a subject.
  • Aspects of the present invention may take the form of a computer program product embodied in one or more computer- readable medium(s) having computer readable program code embodied thereon.
  • the code typically embodies computer-readable program instructions for, when executed on a processor 31 of such a sleep monitoring system 10, implementing the sleep monitoring method 100.
  • the computer readable medium may be a computer readable signal medium or a computer readable storage medium.
  • a computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing.
  • Such a system, apparatus or device may be accessible over any suitable network connection; for instance, the system, apparatus or device may be accessible over a network for retrieval of the computer readable program code over the network.
  • a network may for instance be the Internet, a mobile communications network or the like.
  • the computer readable storage medium may include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
  • a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
  • a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof.
  • a computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
  • Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
  • Computer program code for carrying out the methods of the present invention by execution on the processor 31 may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages.
  • the program code may execute entirely on the processor 31 as a stand-alone software package, e.g. an app, or may be executed partly on the processor 31 and partly on a remote server.
  • the remote server may be connected to the sleep monitoring system 10 through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer, e.g. through the Internet using an Internet Service Provider.
  • LAN local area network
  • WAN wide area network
  • Internet Service Provider an Internet Service Provider
  • the computer program instructions may be loaded onto the processor 31 to cause a series of operational steps to be performed on the processor 31 , to produce a computer-implemented process such that the instructions which execute on the processor 31 provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
  • the computer program product may form part of the sleep monitoring system 10, e.g. may be installed on the sleep monitoring system 10.

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  • Biomedical Technology (AREA)
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  • Databases & Information Systems (AREA)
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  • General Health & Medical Sciences (AREA)
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  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

L'invention concerne un système de surveillance du sommeil (10) destiné à détecter des symptômes de l'asthme pendant le sommeil d'un sujet dans un espace confiné. Le système comprend un capteur de CO2 et un processeur (31) couplé de manière à communiquer avec le capteur de CO2, le processeur étant conçu pour surveiller un changement dans une concentration de CO2 dans une partie de l'espace confiné à proximité immédiate du sujet endormi à partir de données de capteur produites par le capteur de CO2 pendant une période de surveillance, de telle sorte que le changement dans la concentration en CO2 provoqué par l'expiration du CO2 par le sujet dans ladite partie de l'espace confiné est surveillé avant que le CO2 expiré ne se diffuse dans l'ensemble de l'espace confiné ; pour comparer le changement surveillé de la concentration en CO2 dans ladite partie de l'espace confiné avec une valeur de référence pour ledit sujet ; et pour identifier un symptôme d'asthme présenté par ledit sujet si le changement surveillé de la concentration en CO2 dans ladite partie de l'espace confiné dépasse la valeur de référence pour ledit sujet pendant au moins une partie de ladite période de surveillance. L'invention concerne également un procédé de détection de symptômes de l'asthme pendant le sommeil d'un sujet surveillé et un produit programme d'ordinateur pour implémenter un tel procédé sur un système de surveillance du sommeil.
PCT/EP2018/054907 2017-03-17 2018-02-28 Surveillance nocturne de l'asthme Ceased WO2018166795A1 (fr)

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