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WO2016067028A2 - Dispositif d'aide physiologique - Google Patents

Dispositif d'aide physiologique Download PDF

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Publication number
WO2016067028A2
WO2016067028A2 PCT/GB2015/053237 GB2015053237W WO2016067028A2 WO 2016067028 A2 WO2016067028 A2 WO 2016067028A2 GB 2015053237 W GB2015053237 W GB 2015053237W WO 2016067028 A2 WO2016067028 A2 WO 2016067028A2
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WO
WIPO (PCT)
Prior art keywords
user
time
information
physiological state
terminal
Prior art date
Application number
PCT/GB2015/053237
Other languages
English (en)
Other versions
WO2016067028A3 (fr
Inventor
Robert Bowyer
Caroline HARGROVE
Original Assignee
Mclaren Applied Technologies Limited
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from GB201419158A external-priority patent/GB201419158D0/en
Priority claimed from GBGB1513372.1A external-priority patent/GB201513372D0/en
Application filed by Mclaren Applied Technologies Limited filed Critical Mclaren Applied Technologies Limited
Publication of WO2016067028A2 publication Critical patent/WO2016067028A2/fr
Publication of WO2016067028A3 publication Critical patent/WO2016067028A3/fr

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4857—Indicating the phase of biorhythm
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • 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
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • 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
    • 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
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

Definitions

  • This invention relates to assisting humans to improve their physiological state. Background of the invention
  • the present invention may comprise a method for modelling a user's physiological state, comprising: storing in a non-transient manner a physiological state model executable by a computer; receiving first information defining an expected sleep pattern of a user; receiving information defining a target time and a plurality of alternative behaviours; executing the model by means of a computer so as to model, for each of the plurality of alternative behaviours, the user's physiological state for a period at least up to the target time; selecting by means of the computer one of the alternative behaviours; and displaying to the user a graphical representation of the estimated physiological state of the user for the selected one of the alternative behaviours at each of a plurality of times comprised in a period beginning before and ending after the target time.
  • the said selecting step may comprise selecting more than one of the alternative behaviours, in which case the said displaying step may comprise displaying one or more of the selected behaviours.
  • the selecting step may comprises comparing one or more characteristics of the modelled physiological states with one or more predetermined criteria, and selecting the one or more states that conform most closely to the predetermined criteria.
  • the graphical representation may be a graph on which one axis represents time and the other axis represents the estimated physiological state of the user at the respective time.
  • the time axis may be non-linear.
  • the time axis may adopt a circular or part-circular path.
  • the said plurality of times may be at hourly intervals.
  • the said displaying step may comprise displaying user interface elements representing sleeping and waking times.
  • the method may include: accepting input from a user by way of the user interface elements to indicate a change in the user's sleeping pattern; executing the model by means of the computer so as to model for the currently selected one of the alternative behaviours the user's physiological state for a period up to a time after the target time; and displaying to the user a graphical representation of the estimated physiological state of the user for the selected one of the alternative behaviours at each of a plurality of times comprised in a period beginning before and ending after the target time.
  • the alternative behaviours may be alternative travel schedules.
  • the alternative behaviours may be alternative work schedules.
  • the method may comprise the steps of: receiving from a user criteria defining a travel plan; and interrogating a database to identify travel services satisfying the travel plan and retrieve data defining those services; the data defining the services being the said information defining the plurality of alternative behaviours.
  • the travel plan may comprise a start location and a destination location.
  • the start location may be in a different time zone from the destination location.
  • the method may comprise receiving information indicating when the user intends to change from the time zone of the start location to the time zone of the destination location.
  • the model may employ that information to influence the modelled physiological state.
  • the method may comprise, at a time subsequent to any one or more of the steps set out above: receiving from a physiological sensor device behaviour information characterising the behaviour of the user; modifying the information defining the expected sleep pattern of the user in accordance with the actual sleep information; executing the model by means of the computer so as to model for the currently selected one of the alternative behaviours, the user's physiological state for a period up to a time after the target time; and displaying to the user a graphical representation of the estimated physiological state of the user for the selected one of the alternative behaviours at each of a plurality of times comprised in a period beginning before and ending after the target time.
  • the behaviour information may be information characterising the actual sleep behaviour of the user.
  • the behaviour information may be derived from one or more environmental or physiological sensors.
  • the method may comprise sensing an environmental or physiological parameter by means of an electronic sensor, forming an input value in dependence on the sensed data and executing the model in dependence on the input value.
  • the sensor information may be formed in dependence on the sensing of one or more of the following parameters in respect of the user: light exposure, activity level, stress and body temperature, and the behaviour information is dependent on that or those sensed parameters.
  • the present invention may secondly comprise a computing device for modelling a user's physiological state, comprising: a memory storing in a non-transient manner a physiological state model executable by a computer; one or more interfaces for receiving first information defining an expected sleep pattern of a user and receiving information defining a target time and a plurality of alternative behaviours; a processor for executing the model so as to model, for each of the plurality of alternative behaviours, the user's physiological state for a period at least up to the target time, and for selecting by one of the alternative behaviours; and a display; the processor further being configured to display to the user a graphical representation of the estimated physiological state of the user for the selected one of the alternative behaviours at each of a plurality of times comprised in a period beginning before and ending after the target time.
  • the present invention may thirdly comprise a device for influencing a user's physiological state, comprising: an input device for repeatedly receiving state information indicative of the physiological state of the user; a processor configured to: (i) at a first time process the state information to estimate the phase of the user's circadian rhythm relative to a real-time clock; (ii) receive an input indicating a future time; (iii) determine a preferred phase of the user's circadian rhythm at the future time; (iv) determine a series of interventions each appropriate for implementation at a respective time for adapting the user's circadian rhythm to adopt the preferred phase at the future time; and (v) causing an output of the device to inform the user of the interventions and the respective times; wherein the processor is configured to, during the period between the first time and the future time vary the series of interventions and/or the respective times in dependence on state information received after the first time.
  • the state information may comprise information indicative of the activity state of the user.
  • the state information may comprise information indicative of the stress level of the user.
  • the input device may comprise a pulse monitor.
  • the stress level of the user may be indicated by the recovery rate of the user's pulse after elevation.
  • the input device may comprises a keypad whereby the user can indicate his or her activity state.
  • the interventions may include one or more of eating, sleeping, relaxation, stimulation and the use of a tool configured for preferentially stimulating the prefrontal cortex of the user.
  • the processor may be configured to: determine that the current time is within a predetermined time of a time corresponding to an intervention, the intervention being sleeping; estimate the current activity level of the user by means of information received from the input device; and if the current activity level of the user exceeds a predetermined threshold adapt the said intervention to be relaxation.
  • the device may be a portable device.
  • the device may comprise a primary unit that includes the processor and a secondary unit that includes the input device.
  • the primary unit and the secondary unit may be configured for wireless communication of the state information therebetween.
  • the secondary unit may be configured for attachment to the human body.
  • the input device may be a sensor capable of sensing a physiological parameter of a human.
  • the device may be configured to model the expected effect on the user of undertaking a specified activity at a plurality of times, and to inform the user of one or more of those times for which the expected effect is least deleterious.
  • Figure 1 is a schematic diagram of a system including a portable device for intervention management.
  • Figure 2 shows an algorithm for managing a user's jet lag.
  • Figures 3 and 4 show examples of user interfaces for helping to manage a user's jet lag.
  • Figure 5 is a schematic diagram of a system including a portable device for intervention management.
  • the systems described below are configured to gather information about the circumstances of a user of the device and to provide the user with advice for managing their physiological state.
  • the systems are configured to help the user to optimise their physiological state at a specified future time, by reducing the effects of jet lag. Similar systems could be used for other purposes, for example to assist sports participants to improve their preparation to perform at a specific time in the future.
  • FIG. 1 shows a system comprising a portable terminal 1 .
  • the portable terminal 1 can be carried by a user and includes a processor 1 1 , a memory 12, a display 13 and a keypad 14.
  • the keypad could be integrated with the display, as in the case of a touchscreen.
  • the memory 12 contains a non-volatile store 15 which stores in a non- transient way program code that can be executed by the processor 1 1 to cause the terminal to perform the functions described herein.
  • the processor can cause information to be output to the display 13 for provision to a user, and can receive information from the user by means of keypad 14.
  • the terminal also has a communication interface 16, by means of which it can communicate with a remote server 2, for example via the internet 3.
  • the interface 16 could be an interface for wireless communication: for example a cellular radio transceiver or an IEEE 802.1 1 transceiver; or for wired communication: for example an Ethernet or USB interface.
  • the terminal 1 could be a mobile phone, tablet, watch or notebook computer, or could take any other convenient physical form.
  • Memory 15 stores in a non-transient form a program or application which enables the device 1 to assist a user to estimate their future physiological state, and also to model the effect on their future physiological state of various activities undertaken at various times.
  • Information indicating outputs of the modelling can be output to the user by display 13, or another output means such as a loudspeaker. This enables the user to select one or more interventions or actions that are calculated to improve the user's mental state at some time in the future.
  • Figure 2 is a simplified flowchart for the operation of the program.
  • a user provides the program with certain initial input data.
  • the input data includes: (i) a date and time at which the user wishes to optimise their performance and (ii) constraints on the user's travel plans.
  • the constraints could, for example, be a starting location, a destination location and an intended date of travel.
  • the initial input data could include other information that can assist the system to model the user's physiological state, for example the user's normal sleep pattern (e.g. normal times of going to sleep and waking up), whether the user normally adjusts to a destination time zone on departure or arrival, how well the user tends to sleep when travelling, intended food consumption and other information about the user's health, habits and intentions. If this information is not entered it can - to the extent it is required by the program - be set to default values. For example, the user can be assumed to sleep from 1 1 pm to 7am, and to adjust to a destination time zone on arrival.
  • the terminal 1 communicates with the server 2.
  • the server 2 stores travel information including details of transport timetables.
  • the terminal interrogates the server 2 to request a list of transport services that satisfy the supplied constraints: for example services between the starting location and the destination location specified by the user and on the travel date specified by the user.
  • the server returns that list to the terminal.
  • the list may be as follows: Option Start Dest. Dep't Departure time Arrival time Operator date
  • timing information includes indications of the time zones of the departure and arrival locations.
  • Ancillary information may also be given about each service. That ancillary information could be one or more of the operator, mode of transport, model of vehicle, class of service, price and so on.
  • the services, or more generally travel options could each include multiple stages (e.g. connecting flights) and/or modes of transport, and could include stop-overs.
  • the terminal 1 models the user's physiological state for each of the available travel options. In a simple example this may be done using the following schema.
  • the user's level of alertness is modelled on an arbitrary scale from 0 to 100, with 100 representing high alertness and 0 representing low alertness.
  • the user's alertness score is set to a baseline at a time prior to the date of travel. For example, it may be assumed to be 100 at the user's waking time on the day preceding the date of travel.
  • the user's alertness at a subsequent time is estimated by adding to the baseline value a series of values each representing the user's decline or recovery during a respective period (e.g. an hour) in the period between the baseline time and the subsequent time.
  • the values may be selected in the following way:
  • the respective value is a set value a, which is negative;
  • the respective value is ⁇ , where ⁇ is a number between 0 and 1 .
  • the user may be assumed to sleep between their designated sleeping and waking times in their local timezone, and to switch from the departure timezone to the destination timezone on arrival at the destination.
  • the alertness score is constrained so that it cannot exceed 100.
  • the system takes the following steps:
  • the user's alertness score is assumed to be 100 at 07:00 on 31 July.
  • the values ⁇ , ⁇ and ⁇ could be varied manually by a user, or the terminal could automatically vary those values in dependence on information input directly by a user or (as will be described in more detail below) as gleaned from peripheral sensing devices.
  • the user could manually adjust their anticipated waking or sleeping times.
  • the baseline value for the user could be established in dependence on information about their current physiological state, for example as determined in dependence on manual inputs from the user or from peripheral sensing devices.
  • the model could adjust the estimated decline and recovery rates dependent on what the user reports they have eaten or drunk.
  • the value ⁇ could be reduced if the user has drunk alcohol or eaten a high-protein meal.
  • the user's physiological state is modelled for the target time using each potential travel schedule provided by the server. This yields a series of alertness levels as follows:
  • step 23 the terminal 1 presents to the user at least one of the travel options together with an indication of the predicted alertness level for the target time consequent on adopting that option.
  • the terminal first presents only, or highlights in a list, the travel option estimated to yield the highest alertness level for the target time: so as to suggest that option to the user.
  • the terminal first displays an indication of only the travel option that is estimated to yield the highest alertness level, and provides the user with the ability to scroll through the other travel options and view details of each one together with the alertness level estimated for that option.
  • An illustration of what the terminal might display at this stage is shown in figure 3.
  • Figure 3 shows the display of 13 of the device 1 when implementing step 23. The display shows the currently selected travel details at 30.
  • the terminal shows the target time.
  • the terminal shows the user's estimated alertness at the target time if that travel option were to be selected. The user can change the selected travel option by clicking at 33, which will cause the device to show a list of travel options, and then selecting one of those options.
  • step 24 the screen shown in figure 4 is displayed.
  • This screen shows at 40 the peak alertness levels estimated for segments (e.g. morning and afternoon) of a number of days. By clicking on the estimate for one of those days the user can cause the terminal to display the graphic shown at 41 in respect of that day.
  • the graphic shows the estimated alertness level of the user hour-by-hour for that day in the bar chart at 42. This shows in an intuitive way how the user's alertness is expected to vary over time, allowing the user readily to consider re-scheduling an event to a time when he or she will be expected to be most alert.
  • the zone marked by arc 43 represents the user's waking period during that day.
  • the icons 44 and 45 indicate the times of the user waking and going to sleep. The user can move those icons to indicate different waking or sleeping times.
  • the icons 44, 45 will show the user's sleeping and waking times for that day, and allow them to be changed. In response to such a change the terminal will recompute the estimated alertness levels for the user. This enables the user to easily model the effect of changes on their sleeping pattern to help decide how to optimise their performance at a particular time. By selecting another day in zone 40, similar changes can be made to the user's anticipated sleep pattern for that day, and the consequent effect on the user's mental state at a later time modelled automatically by the terminal.
  • the user interface shown in figure 4 provides remarkable ease of use and facility to gain an understanding of future physiological states.
  • the bar chart showing the user's modelled state over the course of a day gives an intuitive representation of changes in the user's state over that day, and allows the user easily to understand whether it would be beneficial either to change the time at which they intend to perform (e.g. by rescheduling a meeting to a time when they will be more alert) or to explore changing other parameters, such as their sleeping/waking times on that or previous days.
  • the user interface elements shown at 44 and 45 which represent the user's sleeping and waking times provide an intuitive way for the user to cause the device to model different possible sleeping patterns.
  • the terminal can store an indication of that option and its details, and can then repeatedly re-run its model of the user's future alertness so as to provide an up-to-date estimate of the user's future level of alertness.
  • the model When the model is re-run it need not be run starting from the original baseline alertness value, but from a current alertness value representing the current alertness of the user. That current alertness level could be derived by summation from the original baseline alertness value in the manner described above. Alternatively, it could be derived by adjusting the algorithm so as to modify the rate at which credits are made or debits are deducted (i.e. by altering one or more of ⁇ , ⁇ and ⁇ in response to information about the user's current state. Alternatively, the model could take an estimate of the user's current state as a baseline. For example:
  • the terminal may make an estimate of the quality of the user's sleep, and adjust its estimate of the user's current alertness accordingly. If according to the model the user's alertness score would be recovering at a rate of ⁇ per hour, the value ⁇ in respect of the current hour's sleep can be adjusted in dependence on an estimate of the user's quality of sleep. That estimate may be determined from a peripheral sensing device which could be incorporated in to the terminal 1 or could be in a separate unit that communicates with the terminal.
  • the sensing device could, for instance, be a heart rate monitor (lower heartrate indicating a higher value of ⁇ ) or an accelerometer carried or worn by the user (lower levels of motion indicating a higher value of ⁇ ).
  • the user could from time to time indicate their level of alertness to the device. This could be done directly, by the user entering a value such as "78" representing their current alertness. Alternatively it could be done by the user undergoing a test using the terminal, for example a test of the user's reaction time (a lower reaction time indicating a higher current level of alertness) or of the steadiness of the user's hand (a greater degree of steadiness indicating a higher current level of alertness).
  • One or more of the sensor devices may be capable of detecting a physiological parameter of a wearer that is indicative of the activity and/or sleep state of the wearer. Examples include pulse rate, respiration rate, actigraphy, muscle activity and body temperature. With such a sensor the system can estimate when the user is asleep and/or when the user is active. With that information the system can estimate the user's circadian rhythm, in the manner described in more detail below.
  • One or more of the sensor devices may be capable of detecting a characteristic of the environment around the wearer, for example ambient temperature, humidity or light intensity. With that information the system can adapt the interventions recommended to the wearer in dependence on the current nature of the environment around the wearer.
  • a characteristic of the environment around the wearer for example ambient temperature, humidity or light intensity.
  • the sensor devices may, for example, include:
  • - pulse sensors for measuring the user's pulse, which can be used to estimate the user's state of alertness and to estimate the user's stress level in dependence on the recovery rate of the user's pulse after exercise;
  • - motion sensors for measuring motion of the user, which can be used to estimate whether the user is resting, and if the user is asleep, to estimate the quality of sleep;
  • ambient temperature sensors and ambient light sensors which can be used to sense whether the user is in a cool and/or light place, which might promote alertness, or vice versa and may be used to help estimate changes to the user's circadian rhythm or to the types of intervention that may best adapt the circadian rhythm.
  • the device may attempt to fit its estimate of the user's circadian rhythm to the sensed data so as to help estimate the user's physiological state. Since the user's circadian rhythm continues with considerable regularity, it is not necessary for the terminal to collect data about the user continuously. It is sufficient to fit data that has been collected from time to time to an assumed circadian cycle to estimate the phase of the cycle with respect to a real-time clock.
  • the terminal may be configured to suggest interventions that may be adopted by the user to improve their alertness at a later time.
  • interventions include: - Advice to eat or sleep at particular times.
  • - Advice on the nature of the food or drink to be consumed for example foods to avoid/consume to optimise timely alertness, recommended fluid consumption (type and/or quantity) for ideal hydration for mental focus, super-food advice (e.g. advising an increase in anti-oxidant uptake to counteract or buffer potential negative effects of sleep deprivation to protect against oxidative stress and to support the user's immune system to prevent illness), advice on healthy foods to eat, foods to avoid or favour in order to optimise sleep routine (e.g. light snack or heavy meal), and advice on safe nutrition supplements to promote alertness or physical performance.
  • super-food advice e.g. advising an increase in anti-oxidant uptake to counteract or buffer potential negative effects of sleep deprivation to protect against oxidative stress and to support the user's immune system to prevent illness
  • advice on healthy foods to eat foods to avoid or favour in order to optimise sleep routine (e.g. light snack or heavy meal)
  • advice on safe nutrition supplements to promote alertness or physical performance.
  • - Advice to listen to pre-recorded messages and/or music stored on the device.
  • Those could be invigorating audio, such as up-tempo music or meditations or affirmations for improving mental focus or performance, or restful audio such as white or natural noises or meditations or affirmations for promoting relaxation.
  • - Advice to undertake cognitive training or stimulation e.g. by means of a game or other routine implemented on an electronic device which could be the terminal itself or another device such as a tablet computer or smartphone.
  • the cognitive training could be such as to stimulate the user's prefrontal cortex.
  • the terminal may provide advice to assist the user to get to sleep. For example, in one mode the terminal may simply advise the user to sleep at a time determined for sleeping. In another mode the terminal may estimate the physiological state of the user, and if the user's state is not significantly fatigued the terminal may instead of advising sleep advise that the user undertakes a restful activity such as relaxation.
  • the terminal can be equipped with a loudspeaker to automatically provide an audible alert to a user at or shortly before a designated eating, sleeping or waking time
  • the terminal may measure the effect of certain activities on the user's physiology. For example, it may measure the change in a user's level of stress in response to a short period of sleep. That response may differ for different users.
  • the algorithm may use information on the user's response to such activities to help decide whether and when to advise that the user undertakes such activities.
  • the terminal 1 performs processing locally to determine what advice to provide to the user.
  • processing could be distributed between the terminal and a remote server.
  • system models and presents to the user information about their anticipated levels of alertness.
  • the system could be used to model other physiological attributes, such as stress, physical recovery, medical disorders or required drug dosage rates.
  • the user's mental state is modelled for changes in time zone. More generally, the user's mental state can be modelled for changes in the time zone observed by the user. For example the user might not move from a location governed by one time zone to a location governed by another time zone, but might instead remain in one time zone but change his sleeping patterns, for example to accommodate shift work or an overnight sports event.
  • the system could model possible preparations for other individuals: for example to help prepare patients who are to undergo operative procedures overnight.
  • FIG. 5 shows a system comprising a portable terminal 101 , a wearable sensor device 102 and a server 103.
  • the portable terminal 101 can be carried by a user and includes a display 1 1 1 for providing information to the user.
  • the portable terminal and the wearable sensor device include respective short-range communication modules 1 12, 121 by means of which they can communicate wirelessly with each other.
  • the portable terminal also includes a data interface 1 13 by means of which it can communicate over a data network 104, such as the internet, with the server 103.
  • the data interface 1 13 could, for example be a wireless interface such as a cellular radio terminal or a Wi-Fi (IEEE 802.1 1 ) client, or a wired interface such as a USB or Ethernet interface.
  • the portable terminal includes a user input device 1 14, such as a keypad or touch-sensitive screen covering.
  • the portable terminal and the wearable sensor device include sensors 1 15, 122 for gathering information about the environment or about the physiological state of a user or wearer.
  • the wearable sensor device can be worn by a user who is also carrying the portable terminal 101 .
  • the wearable sensor device can gather information by means of sensor 122 and transmit that information to the portable terminal via modules 1 12, 121 .
  • the portable terminal can augment that information with: (i) information it has gathered from its own sensor 1 15, (ii) inputs given by the user through input device 1 14, and (iii) information received from the server 103 via data network 104 and data interface 1 13.
  • a processor 1 16 of the terminal is configured to execute program code stored non-transiently in a memory 1 17 of the terminal. In that way the processor can analyse the information available to the terminal and in dependence on that analysis control the display 1 1 1 to display messages to the user.
  • the algorithm implemented by the processor can be configured so that the messages are effective to assist the user to reduce the effect of jet lag.
  • One or more of the sensor devices is/are capable of detecting a physiological parameter of a wearer that is indicative of the activity and/or sleep state of the wearer. Examples include pulse rate, respiration rate, actigraphy, muscle activity and body temperature. With such a sensor the system can estimate when the user is asleep and/or when the user is active. With that information the system can estimate the user's circadian rhythm, in the manner described in more detail below.
  • One or more of the sensor devices may be capable of detecting a characteristic of the environment around the wearer, for example ambient temperature, humidity or light intensity. With that information the system can adapt the interventions recommended to the wearer in dependence on the current nature of the environment around the wearer.
  • a user who is intending to make a long flight uses the input device 14 to configure the terminal 1 in advance of the flight with the following information:
  • time zone of start point (e.g. GMT + 00:00),
  • processor 1 16 These inputs are received by processor 1 16 and stored in memory 1 17 as part of a set of state information 130.
  • the memory 1 17 also stores an algorithm 131 implemented as a program executable by the processor 1 16 for processing the state information 130 together with the time as indicated by a real-time clock 1 18 of the terminal 101 to form advice messages for the user.
  • the state information can also be populated with information such as sensed data from the sensor input devices 1 15, 122.
  • the messages provided by the terminal may relate to a range of interventions, but in one example they may relate to eating times and sleeping times. Then using the algorithm defined in its software the processor processes the inputs available to it and estimates preferred times for the user to eat and sleep in the period running up to the time when they wish to be at maximum performance ("peak time"). Those preferred times can be indicated on the display. The algorithm may calculate those times in various ways.
  • the algorithm may simply advise the user to eat and sleep at times that are appropriate to the destination time zone: for example to sleep from 1 1 :00pm to 7:00am and to eat at 8:00am, 1 :00pm and 7:00pm in the destination time zone irrespective of the current time zone of the user.
  • the algorithm may take account of inputs provided by the user as to the user's preferred eating and/or sleeping time.
  • the algorithm may advise the user to eat and sleep at a series of times that graduate from times appropriate to the current time zone (at the initiation of the algorithm) to times appropriate to the destination time zone (at or near the peak time).
  • the algorithm may cause the terminal to take input from the user regarding the user's perception of their current state, and dependent on that, the time of day local to the user and the interval before the peak time the algorithm may adapt its advice regarding eating and sleeping times. For example, the user may arrive at a destination in the mid-morning after a long flight and the peak time may be the next day. The user needs to know whether to sleep or stay awake. In this situation if the user indicates he is very tired the algorithm might advise the user to sleep for a short period or to get exposure to sunlight, whereas if the user indicates he is alert then the algorithm might advise the user to exercise. The same evening, the algorithm might advise the user to sleep if he indicates he is feeling tired, or to eat if he is feeling alert.
  • the algorithm may take account of constraints indicated by the user. For example, if the user is on a flight it may be impossible to eat or sleep at certain times because the user is boarding or leaving the flight, or passing through an airport, or because meals are served on the plane at set times.
  • the algorithm may adapt its advice regarding eating and sleeping times in dependence on these constraints.
  • the terminal forms an estimate of the timing of the user's circadian rhythm. Normally, a person's circadian rhythm operates on a period of approximately 24 hours. By default the terminal may assume that the user's normal circadian rhythm is composed of a 16-hour waking period followed by an 8-hour sleeping period, and that during the 16-hour waking period the user has two activity peaks at 6 and 10 hours respectively from the start of the waking period. That assumed rhythm may then be applied and varied in the following ways. 1 .
  • the terminal estimates the current phase of the user's circadian rhythm relative to a time-of-day clock.
  • the terminal adapts the assumed rhythm to the user's normal behaviour.
  • the user's normal circadian rhythm may operate on a 23-hour cycle, or may have only a single daily activity peak.
  • the terminal adapts the length of the user's current circadian cycle to the circumstances of the user. For example, if the user has changed time zones significantly the circadian cycle may be somewhat extended (e.g. from a normal period of 24 to 25 hours) or contracted (e.g. from a normal period of 24 hours to 23 hours). These operations are performed in dependence on inputs received from the sensors and from a user interface, for example by the user manually or orally inputting data to the terminal.
  • the algorithm implemented by the terminal may invite the user to provide manual or oral input regarding their level of tiredness/alertness from time to time during each day. Based on those inputs the terminal may estimate the timing of the user's circadian rhythm by estimating a best fit between the pattern of inputs received from the user and a normal circadian rhythm. Another approach is to have the user input the times at which they go to bed and wake up. That information may be used to centre the assumed sleep period of the circadian rhythm at the mid-point of the going-to-bed and waking times. Another approach is for the terminal to interpret data received from the sensors indicating the user's level of activity/alertness and to estimate a best fit between that data and a normal circadian rhythm. Another approach is the terminal to interpret data received from the sensors indicating the times at which the user goes to bed and wakes up and to use that information may be used to centre the assumed sleep period of the circadian rhythm at the mid-point of the going-to-bed and waking times.
  • the terminal may use direct inputs from the user of the type described above and/or data received from the sensors to track the pattern of the user's tiredness/alertness over multiple days. Using that data the algorithm can detect the average timings of key characteristics of the user's circadian rhythm, such as its period, the average sleep time and the timing(s) of any activity peak(s) during the waking period of the rhythm. The normal rhythm of the user as applied by the terminal can then be adapted accordingly.
  • the terminal may use direct inputs from the user of the type described above and/or data received from the sensors. For example, if the user has input that he or she has travelled to a location having a different time zone then the terminal may adjust the length of the user's circadian rhythm by a predetermined amount (e.g. one hour) to take it closer to the expected circadian rhythm at that time zone. In another example, if the sensors indicate that the user is experiencing bright light at a time that corresponds to a sleep time of the circadian rhythm at its currently estimated phase, or darkness at a time that corresponds to a waking time of the circadian rhythm at its currently estimated phase then the terminal may adjust the estimated phase of the user's circadian cycle accordingly.
  • a predetermined amount e.g. one hour
  • the algorithm may then identify how the user's circadian rhythm can be adjusted with the minimum deviation so that the time at which the user desires to peak will fall at a time when the user's circadian rhythm indicates he will be alert.
  • the terminal may then advise interventions such as eating or sleeping in accordance with that minimally adjusted circadian rhythm.
  • One way to achieve this is to estimate the minimum adjustment of the user's circadian rhythm that will cause an activity peak in the circadian rhythm to fall at or within a predetermined time window of the peak time.
  • the terminal initially assumes that the user's circadian rhythm consists of a 16-hour waking period followed by an 8-hour sleep period, with activity peaks at 6 and 10 hours from the start of the waking period, and suppose that the user has indicated that they went to bed at 1 1 pm GMT on day 0 and woke at 7am GMT on day 1 .
  • the terminal takes the start of the circadian rhythm to be at 7am GMT.
  • the user travels to a time zone that is 5 hours ahead of GMT and indicates that he wishes to peak for an event that occurs at 2pm in that time zone on day 4.
  • the user inputs information about the new time zone and his waking and sleeping times into the terminal on an ongoing basis, or the terminal infers them from its sensors.
  • the user's circadian rhythm at the phase in which it stands for day 1 begins at 2am. That means the assumed activity peaks of the user are at 8am and 12pm in the new time zone. The peak time is 2pm in the new time zone.
  • the terminal determines that for minimum disruption to the user's circadian rhythm the user's circadian rhythm can be extended by one hour in each of days 2 and 3 so that in day 4 the second peak falls on the desired peak time. Having automatically determined that, the terminal generates advice for the user to help implement that adaptation, for example by encouraging the user to go to bed one hour later each day than would be dictated by his or her current circadian rhythm.
  • the user may desire to peak at 1 pm in the new time zone.
  • the terminal determines that for minimum disruption to the user's circadian rhythm the user's circadian rhythm can be shortened by half an hour in each of days 2 and 3 so that in day 4 the second peak falls on the desired peak time. Having automatically determined that, the terminal generates advice for the user to help implement that adaptation, for example by encouraging the user to go to bed half an hour earlier each day than would be dictated by his or her current circadian rhythm. Note that in the second example, the advice is directed at influencing the user to move their circadian rhythm in the opposite direction than would be dictated by simply adjusting to natural behaviour in the new time zone.
  • the terminal may display an indicator of the user's expected readiness to perform at the peak time. That indicator may be based on the user's current state, as indicated by user or sensor input(s), and the time remaining until the peak time.
  • the user may configure the terminal with an indication of aspects of their performance that they would like to optimise for the peak time. For example, those may be mental aspects, physical aspects or personal appearance.
  • the terminal may take this information into account in advising interventions, for example by choosing to adapt a suitable part of the user's circadian rhythm to the peak time. Normally a user will become aware some time before a flight that they will need to take the flight and perform at some peak time thereafter. The terminal may therefore provide a range of outputs during the distinct phases of the period leading up to the peak time.
  • the terminal may perform circadian modelling for the user, as described above, and in dependence on that modelling provide the user with an expected list of sleeping and eating times for the period running up to the peak time. Those times may include events before, during and after the flight. Subsequently the terminal may gather additional information regarding the user's physiological state, for example whether the user is asleep or active and the user's level of stress (e.g. as derived from sensor input devices 1 15, 122 as absolute pulse rate, pulse rate stability, respiration rate, respiration rate stability or pulse recovery rate). Additionally, the user may use input device 1 14 to indicate to the terminal when he has eaten or slept.
  • circadian modelling for the user, as described above, and in dependence on that modelling provide the user with an expected list of sleeping and eating times for the period running up to the peak time. Those times may include events before, during and after the flight. Subsequently the terminal may gather additional information regarding the user's physiological state, for example whether the user is asleep or active and the user's level of stress (e.g. as derived
  • the terminal can use the information about the user's physiological state - as derived from sensors or manual inputs - to update its estimate of circadian rhythm and to adjust its recommended sleeping and eating times accordingly.
  • This provides significant advantages over both ad hoc methods and simple pre-planning methods.
  • the user can adapt his behaviour plan to events - for example delaying a meal time if a flight is delayed - but without objective analysis of current state or of the effect of such a change. If a user adopts pre-planned eating and sleeping times, he cannot readily adapt, for example to a missed sleep period.
  • the terminal can be equipped with a loudspeaker to automatically provide an audible alert to a user at or shortly before a designated eating, sleeping or waking time
  • the sensor inputs 1 15, 122 can, for example, include:
  • - pulse sensors for measuring the user's pulse, which can be used to estimate the user's state of alertness and to estimate the user's stress level in dependence on the recovery rate of the user's pulse after exercise
  • - motion sensors for measuring motion of the user, which can be used to estimate whether the user is resting, and if the user is asleep, to estimate the quality of sleep
  • ambient temperature sensors and ambient light sensors which can be used to sense whether the user is in a cool and/or light place, which might promote alertness, or vice versa and may be used to help estimate changes to the user's circadian rhythm or to the types of intervention that may best adapt the circadian rhythm.
  • the interventions that may be advised by the terminal are not limited to recommended eating and sleeping times. As mentioned above, they may include any of the following interventions, which the terminal may recommend at pre-computed times in dependence on the user's current state and the time remaining until the peak time:
  • - Advice on the nature of the food or drink to be consumed for example foods to avoid/consume to optimise timely alertness, recommended fluid consumption (type and/or quantity) for ideal hydration for mental focus, super-food advice (e.g. advising an increase in anti-oxidant uptake to counteract or buffer potential negative effects of sleep deprivation to protect against oxidative stress and to support the user's immune system to prevent illness), advice on healthy foods to eat, foods to avoid or favour in order to optimise sleep routine (e.g. light snack or heavy meal), and advice on safe nutrition supplements to promote alertness or physical performance.
  • super-food advice e.g. advising an increase in anti-oxidant uptake to counteract or buffer potential negative effects of sleep deprivation to protect against oxidative stress and to support the user's immune system to prevent illness
  • advice on healthy foods to eat foods to avoid or favour in order to optimise sleep routine (e.g. light snack or heavy meal)
  • advice on safe nutrition supplements to promote alertness or physical performance.
  • - Advice to listen to pre-recorded messages and/or music stored on the device.
  • Those could be invigorating audio, such as up-tempo music or meditations or affirmations for improving mental focus or performance, or restful audio such as white or natural noises or meditations or affirmations for promoting relaxation.
  • - Advice to undertake cognitive training or stimulation e.g. by means of a game or other routine implemented on an electronic device which could be the terminal itself or another device such as a tablet computer or smartphone.
  • the cognitive training could be such as to stimulate the user's prefrontal cortex.
  • the user may indicate to the terminal that an activity of a certain type and duration is to be undertaken in a defined window: for example the user may indicate that a flight from London to Tokyo is to be undertaken between 9am on 1 June and 9pm on 3 June.
  • the user may optionally provide the terminal with a finite list of options for when the activity may be undertaken (e.g. available commercial flight times), or the terminal may gather such options automatically from a remote database.
  • the terminal may then estimate the effect on the user of undertaking those activities at different times during the window, and may advise the user on which times, or which of the options, will permit the user to perform best at a future time.
  • the terminal may implement an algorithm that models the expected performance level of a user at future times. That model may be implemented by giving the user an initial score, e.g. 50, and then incrementing or decrementing that score for each interval (e.g. hour) during the period in question depending on the activities anticipated to be undertaken during that interval.
  • the score may be adjusted as follows for each interval, in dependence on the primary activity in that interval:
  • the terminal can model the anticipated effect of undertaking activities at different times on the user, and identify the time at which the activity can be undertaken to achieve the highest score at the end of the modelling period.
  • the terminal can select one or more times and output them to a user as advised times for undertaking the activity.
  • the terminal may provide advice to assist the user to get to sleep. For example, in one mode the terminal may simply advise the user to sleep at a time determined for sleeping. In another mode the terminal may estimate the physiological state of the user, and if the user's state is not significantly fatigued the terminal may instead of advising sleep advise that the user undertakes a restful activity such as relaxation.
  • the terminal may measure the effect of certain activities on the user's physiology. For example, it may measure the change in a user's level of stress in response to a short period of sleep. That response may differ for different users.
  • the algorithm may use information on the user's response to such activities to help decide whether and when to advise that the user undertakes such activities.
  • the terminal 101 may be a dedicated physiological management terminal or it may be integrated into another device such as a smartphone or tablet computer.
  • the terminal may communicate over the internet to assist the user with other travel-related activities such as flight check in, seat assignment, providing information on scheduling or delays and booking ancillary services such as taxis and grooming services.
  • the terminal provides a user with advice for managing their physiological state with a view to achieving performance at a specific future time to counteract jet lag.
  • the algorithm implemented by the terminal is configured to minimise or reduce the effect of jet lag by tailoring sleep and meal routines before, during and after travel (e.g. long-haul flights), based on inputs that may include indicators of circadian rhythm, stress levels of a user, and sleep and activity levels of the user, with a view to promoting optimal mental and/or physical performance at a designated time.
  • the terminal may operate in a similar way to help optimise performance in other circumstances, for example to help shift workers adapt to different work times.
  • the terminal 101 performs processing locally to determine what advice to provide to the user.
  • that processing could be distributed between the terminal and the server 103.

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Abstract

L'invention concerne un dispositif permettant d'agir sur l'état physiologique d'un utilisateur et comprenant un dispositif d'entrée recevant à répétition des informations d'état indiquant l'état physiologique de l'utilisateur, et un processeur configuré pour : (i) traiter à un premier instant les informations d'état pour estimer la phase du rythme circadien de l'utilisateur par rapport à une horloge en temps réel ; (ii) recevoir une entrée indiquant un instant futur ; (iii) déterminer une phase préférée du rythme circadien de l'utilisateur à l'instant futur ; (iv) déterminer une série d'interventions, chacune appropriée pour être mise en œuvre à un instant donné, pour adapter respectivement le rythme circadien de l'utilisateur pour qu'il adopte la phase préférée à l'instant futur ; (v) et déclencher une sortie du dispositif pour informer l'utilisateur des interventions et des instants respectifs. Le processeur est configuré pour, pendant la période séparant le premier instant de l'instant futur, faire varier la série d'interventions et/ou les instants respectifs en fonction des informations d'état reçues après le premier instant.
PCT/GB2015/053237 2014-10-28 2015-10-28 Dispositif d'aide physiologique WO2016067028A2 (fr)

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GB201419158A GB201419158D0 (en) 2014-10-28 2014-10-28 Device for physiological assistance
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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017219003A1 (fr) * 2016-06-17 2017-12-21 Predictive Safety Srp, Inc. Système et procédé de détection d'invalidité
WO2020004126A1 (fr) * 2018-06-25 2020-01-02 株式会社ニューロスペース Dispositif de présentation d'informations, procédé de présentation d'informations, et support d'enregistrement
JP2022515374A (ja) * 2018-12-18 2022-02-18 コーニンクレッカ フィリップス エヌ ヴェ 覚醒レベルを決定するシステム及び方法
US11985741B2 (en) 2020-05-18 2024-05-14 Mate. Llc Human-centric lighting controller
US12035430B2 (en) 2020-05-18 2024-07-09 Mate. Llc Centrally-controlled tunable lighting

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1125237B1 (fr) * 1998-10-30 2005-08-24 Walter Reed Army Institute of Research Systeme et methode permettant de prevoir les performances cognitives d'un etre humain sur la base de donnees tirees d'un actigraphe
US7118530B2 (en) * 2001-07-06 2006-10-10 Science Applications International Corp. Interface for a system and method for evaluating task effectiveness based on sleep pattern
US7806695B1 (en) * 2002-08-20 2010-10-05 George Peter T Jet lag forecaster
GB2471902A (en) * 2009-07-17 2011-01-19 Sharp Kk Sleep management system which correlates sleep and performance data
JP2012226564A (ja) * 2011-04-20 2012-11-15 Sony Corp 情報処理装置、情報処理方法、およびプログラム

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
None

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US10956851B2 (en) 2016-06-17 2021-03-23 Predictive Safety Srp, Inc. Adaptive alertness testing system and method
US10970664B2 (en) 2016-06-17 2021-04-06 Predictive Safety Srp, Inc. Impairment detection system and method
US10430746B2 (en) 2016-06-17 2019-10-01 Predictive Safety Srp, Inc. Area access control system and method
US11282024B2 (en) 2016-06-17 2022-03-22 Predictive Safety Srp, Inc. Timeclock control system and method
US10586198B2 (en) 2016-06-17 2020-03-10 Predictive Safety Srp, Inc. Cognitive testing system and method
US10586197B2 (en) 2016-06-17 2020-03-10 Predictive Safety Srp, Inc. Impairment detection system and method
US10395204B2 (en) 2016-06-17 2019-08-27 Predictive Safety Srp, Inc. Interlock control system and method
US10867272B2 (en) 2016-06-17 2020-12-15 Predictive Safety Srp, Inc. Geo-fencing system and method
WO2017219003A1 (fr) * 2016-06-17 2017-12-21 Predictive Safety Srp, Inc. Système et procédé de détection d'invalidité
US10867271B2 (en) 2016-06-17 2020-12-15 Predictive Safety Srp, Inc. Computer access control system and method
US11074538B2 (en) 2016-06-17 2021-07-27 Predictive Safety Srp, Inc. Adaptive alertness testing system and method
WO2020004126A1 (fr) * 2018-06-25 2020-01-02 株式会社ニューロスペース Dispositif de présentation d'informations, procédé de présentation d'informations, et support d'enregistrement
JP2022515374A (ja) * 2018-12-18 2022-02-18 コーニンクレッカ フィリップス エヌ ヴェ 覚醒レベルを決定するシステム及び方法
JP7548585B2 (ja) 2018-12-18 2024-09-10 コーニンクレッカ フィリップス エヌ ヴェ 覚醒レベルを決定するシステム及び方法
US11985741B2 (en) 2020-05-18 2024-05-14 Mate. Llc Human-centric lighting controller
US12035430B2 (en) 2020-05-18 2024-07-09 Mate. Llc Centrally-controlled tunable lighting

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