WO2009057033A2 - Calcul de l'état d'un utilisateur - Google Patents

Calcul de l'état d'un utilisateur Download PDF

Info

Publication number
WO2009057033A2
WO2009057033A2 PCT/IB2008/054426 IB2008054426W WO2009057033A2 WO 2009057033 A2 WO2009057033 A2 WO 2009057033A2 IB 2008054426 W IB2008054426 W IB 2008054426W WO 2009057033 A2 WO2009057033 A2 WO 2009057033A2
Authority
WO
WIPO (PCT)
Prior art keywords
user
energy
input
computing
energy level
Prior art date
Application number
PCT/IB2008/054426
Other languages
English (en)
Other versions
WO2009057033A3 (fr
Inventor
Frank Wartena
Ronaldus M. Aarts
Original Assignee
Koninklijke Philips Electronics N.V.
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
Application filed by Koninklijke Philips Electronics N.V. filed Critical Koninklijke Philips Electronics N.V.
Publication of WO2009057033A2 publication Critical patent/WO2009057033A2/fr
Publication of WO2009057033A3 publication Critical patent/WO2009057033A3/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
    • 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 system, method and a computer program for computing a condition of a user.
  • US 2003/0065257 Al discloses a diet and activity-monitoring device including a housing configured to be mounted on the subject and a display integral with the housing for displaying information to the subject.
  • the device also includes a body activity monitor operatively disposed within the housing for monitoring the body activity of the subject, a consumption notation control operable by the subject to indicate food consumption, and a timer operable to output a time indicative signal.
  • the device further includes a processor operable to receive and process the body activity signal, time indicative signal and the food consumption signal, for use in determining a food consumption indicator or a body activity indicator that is stored in a memory portion of the processor for recall by the subject on the display screen.
  • the device represents the information related to the user's body activity and food consumption separately and gives specific goals for both.
  • a system for computing an energy level of a user.
  • the system comprises computing means for computing the energy level based on an energy capacity of the user and at least one of: a parameter related to the input of energy of the user, and a parameter related to the output of energy of the user.
  • the energy level of a person in the sense of the present invention is a measure of the current condition of the user. This measure may be considered to relate to the current user ability to deal with stress, which in psychology is called "coping". Additionally, the measure may be considered an indicator of the "balance" of the user, which in physiology is called homeostasis.
  • Energy input according to the present invention refers to those activities which make a person feel more energetic. Examples of parameters related to the input of energy of the user are:
  • Sleep quality duration, sleep-wake cycle, wake up time, movements during the night, subjective quality measure, etc
  • Food number of meals per day, type of food, subjective food quality, etc.
  • Energy output according to the present invention refers to those activities which make a person feel less energetic.
  • Activity step counts per day, duration of fitness activities, subjective quality measure, etc
  • the energy capacity of a person is a measure of how much energy a user may "accumulate". It may vary considerably from person to person. Some persons still feel energetic after prolonged periods of sleeping little or dealing with a lot of stress. These persons may be considered to have a high energy capacity. Other persons already feel down after one night of bad sleep or can only deal with a very limited amount of stress. Such persons can be considered to have a small energy capacity.
  • the system can calculate the human energy level of a user by subtracting the energy usage of the user from his/her energy capacity.
  • the energy usage is determined by the parameters related to the energy input and energy output of the user.
  • the computed energy level information provides more value to the user than just an indication that the user took 6000 steps or consumed 2000 Kcal as given by prior art systems.
  • the system comprises communication means for communicating the energy level, for example by SMS, email, or by means of an icon on a dedicated device.
  • the communication means are adapted to communicate the energy level by displaying a battery level indicator.
  • batteries e.g. laptops, PDAs, mobile phones, MP3- players, etc. All of these devices have some way to show the amount of energy they have left and give a warning when the battery is almost empty and the device needs to be charged.
  • a similar case can be made for people. When they do their work, they extract energy from their internal “battery”. When people sleep, eat, relax or do pleasant activities, or when they are on vacation they charge their "battery”. So, the use of a battery metaphor is a very intuitive way of communicating the energy level to the user.
  • the communication means are adapted to communicate a low energy level warning.
  • a "human low battery warning” indicates to the user in a very simple way that he/she should change his/her behavior by sleeping more, eating better or relaxing a little bit to prevent the user from being over-stressed or getting a burnout. This simple warning can help people to take a break when they need it and to make sure that their human "battery" does not get empty.
  • the communication means are adapted for communicating the energy level based on preferences of the user. For example, the user can select when he/she wants to receive a low battery warning (e.g. battery level ⁇ 25%) and in what way (e.g. SMS, email, icon on dedicated device).
  • a low battery warning e.g. battery level ⁇ 25%
  • a way e.g. SMS, email, icon on dedicated device.
  • the energy capacity of each user should be assessed in order for the system to work properly. This means that during operation of the system the user should provide input about his/her current state, over time. Based on these data, the system, which is a self learning system, will be able to make an assessment of the user's battery capacity. Inputs to this assessment are demographics as age, sex, fitness level, etc and user input as when he/she feels energetic or very tired.
  • the computing means are adapted to determine the parameters related to the input and output of energy of the user based on manual input by the user.
  • a more complex version would include observing means for observing the user, in which case the computing means are adapted to determine the parameters related to the input and output of energy of the user based on the observation of the user.
  • Such observing means are for example a sleep duration counter integrated into an alarm clock, a step counter or even a heart rate monitor to measure stress during the day.
  • These observing means may be part of a wearable non-obtrusive - device, e.g. a wrist watch, for both (part of) the measurement as well as the computation of the user's energy level.
  • a method for computing an energy level of a user based on: an energy capacity of the user and at least one of: a parameter related to the input of energy of the user, and a parameter related to the output of energy of the user.
  • the method according to the invention is implemented by means of a computer program.
  • Figure 1 shows schematically an exemplary embodiment of the invention.
  • Figure 2 shows an exemplary way of communicating a user's energy level.
  • like reference numerals refer to like elements.
  • the system comprises an input 110 for parameters related to the energy input of a user, an input 120 for parameters related to the energy output of the user and an input 130 for information related to the situation of the user at a certain moment or during a certain period.
  • the system furthermore comprises a computing unit 140 for computing an energy level based on the inputs 110, 120, 130 and a communication unit 150 for communicating the energy level to the user.
  • the system comprises an input 160 for personalizing the settings for the computation and communication of the energy level.
  • the energy level is communicated to the user by means of a battery metaphor, including a "low battery warning” if the energy level is low, which is shown in figure 2.
  • the energy level or "battery level” of a person in the sense of the present invention is not some physical measure such as kJ but is a measure of the current condition of the user. This measure may be considered to represent the current user ability to deal with stress, which in psychology is called “coping”. Additionally or alternatively, the measure may be considered to be an indicator of the "balance" of the user, which in physiology is called homeostasis.
  • Energy input refers to those activities which make a person feel more energetic. Examples of parameters related to the energy input of a user are:
  • Sleep quality duration, sleep-wake cycle, wake up time, movements during the night, subjective quality measure , etc
  • the system should calculate an optimum sleeping period. Sleeping too short or too long is not good for the human energy level and will thus reduce it. Energy output refers to those activities which make a person feel less energetic. Examples of parameters related to the energy output of a user are:
  • Activity step counts per day, duration of fitness activities, subjective quality measure, etc
  • the user can select which inputs to use. The more inputs the system gets, the more reliable the computation of the energy level will be.
  • the energy capacity or "battery capacity" of a person is a measure of how much energy a user may "accumulate”. It may vary considerably from person to person.
  • Ai,Bi,Ci are parameters related to input energy of the user Ko, Lo, Mo are parameters related to output energy of the user a, b, c and k, 1, m are personalization parameters to reflect the contribution of the above parameters to the user's energy input and output. These personalization parameters will be adjusted over time as the system learns the user's energy behavior.
  • the system will need to be calibrated by the user so that the system is able to deal with the specific situation of a user.
  • This calibration is done by means of input 130 by letting the user indicate a particularly relaxing period or a particularly stressful period during an initial training period.
  • the user can indicate to the system at the end of the day how he/she felt that day to train the system.
  • the user can also calibrate the system by adjusting the computed battery level, for example if the user feels much better than the calculated battery level.
  • the user needs to personalize the settings for the computation of the energy level by means of input 160.
  • Examples of personalization of the computation are age, sex and other personal data, questionnaires with questions such as "what is your normal sleeping pattern", "how active are you”.
  • the settings for the computation of the energy level may also comprise information on the relation between certain parameters and the perceived energy level of the user, for example I need 7 hours of sleep to feel good or I need to play sports at least twice a week in order to feel good, etc.
  • the system can compute a "human battery level" which can range for instance from 0% to 100%.
  • the energy level cannot become negative or become larger than 100%. If the energy level becomes larger than 100%, the user's energy capacity has not been estimated correctly and the system should be recalibrated.
  • the user can personalize the settings for the communication of his energy level. He/she can select for example when a low battery warning should be communicated (for example if battery level ⁇ 25%) and in what way (e.g. SMS, email, icon on dedicated device). Based on this warning the user can take appropriate action to "charge the battery” and prevent health issues.
  • a low battery warning for example if battery level ⁇ 25%
  • a way e.g. SMS, email, icon on dedicated device
  • the system can exist in various shapes.
  • the simplest version will be a PC or Web application that only gets manual inputs from the user in the categories described herein above, sleep, activity, food and stress. Based on these manual inputs and personalization settings by the user the system will compute an energy level and display this to the user.
  • the inputs 110, 120 would include observing units for observing the user.
  • the observing units may be measurement devices such as a sleep duration counter integrated into an alarm clock, a step counter or even a heart rate monitor to measure stress during the day.
  • measurement devices would be arranged in a wearable, non-obtrusive device, such as a wrist watch, for both (part of) the measurement as well as the computation of the energy level.
  • a further physiological parameter that can be used is the Heart Rate
  • HRV HRV is an important measure for emotions and physical exercise and can be used as another input parameter.
  • An example embodiment would determine the time between heart beats (inter beat intervals - IBIs) and average these with a low pass filter with cut off frequency of 1 Hz. If the resulting signal contains a lot of low frequency energy (e.g. below 0.04 Hz) it is an indication of a high activity of the sympatic part of the autonomic nerve system (ANS) which is not good because it indicates that the user is in a stressed state. This has a negative influence on the human energy level. If there is relatively much high frequency energy say above 0.15 Hz then this indicates a high activity of the parasympatic part of the ANS which gives bonus points because this denotes the user as being in a relaxed state.
  • ANS autonomic nerve system
  • An even more advanced embodiment is to measure the levels of certain hormones and muscle tension.
  • the former can be measured by blood samples, both in vitro as well in vivo, the latter is preferred.
  • corticotropin-releasing factor CRF
  • CRF corticotropin-releasing factor
  • CRF is central to the endocrine component of the neuroendocrine response to stress.
  • CRF induces secretion of the adrenocorticotropic hormone (ACTH), in turn stimulates the secretion of other glucocorticoid hormones (e.g., Cortisol). Measuring of these hormones gives a good measure of the stress level of a subject.
  • the observing units may also comprise a camera, which may be stationary or built into a mobile phone, as an extra input to the system.
  • a camera When the camera is aimed at the face of the user it can analyze facial expressions. This can help to identify if the user is relaxed, stressed or tired. Specifically the area around the eyes and the eyebrows shows this very well. Facial expression analysis is known in literature however it has not been used in the context of a human energy level.
  • the output of the computation can be given also on a variety of devices such as a PC, the alarm clock or your mobile phone.
  • the invention could be applied as a standalone device, as a web or PC application or as part of a larger health management application.
  • the innovative concepts described in the present application can be modified and varied over a wide range of applications.

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  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Medical Informatics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Public Health (AREA)
  • Biomedical Technology (AREA)
  • Pathology (AREA)
  • General Health & Medical Sciences (AREA)
  • Surgery (AREA)
  • Molecular Biology (AREA)
  • Physics & Mathematics (AREA)
  • Animal Behavior & Ethology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Biophysics (AREA)
  • Veterinary Medicine (AREA)
  • Data Mining & Analysis (AREA)
  • Databases & Information Systems (AREA)
  • Epidemiology (AREA)
  • Primary Health Care (AREA)
  • Medical Treatment And Welfare Office Work (AREA)
  • Alarm Systems (AREA)

Abstract

L'invention vise à pallier l'absence actuelle d'une manière aisée de faire savoir à des personnes qu'elles doivent prendre une pause et se détendre, manger ou dormir mieux. Le système (100) selon l'invention offre un avertissement de batterie faible pour être humain, qui indique à l'utilisateur de façon très simple qu'il doit modifier son comportement en dormant davantage, en mangeant mieux ou en se détendant plus pour empêcher l'utilisateur d'être trop stressé ou épuisé. Ce simple avertissement peut aider des personnes à prendre une pause lorsqu'elles en ont besoin et à s'assurer que leur batterie humaine ne s'épuise pas.
PCT/IB2008/054426 2007-11-02 2008-10-27 Calcul de l'état d'un utilisateur WO2009057033A2 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP07119908 2007-11-02
EP07119908.7 2007-11-02

Publications (2)

Publication Number Publication Date
WO2009057033A2 true WO2009057033A2 (fr) 2009-05-07
WO2009057033A3 WO2009057033A3 (fr) 2009-07-30

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2014064580A1 (fr) 2012-10-23 2014-05-01 Koninklijke Philips N.V. Système de mesure de stress
EP2775901A4 (fr) * 2011-11-11 2015-07-15 Firstbeat Technologies Oy Procédé et système pour évaluer un état physiologique décrivant les ressources d'une personne
CN105559761A (zh) * 2015-12-18 2016-05-11 安徽寰智信息科技股份有限公司 一种穿戴式健康行为向导系统

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20010016689A1 (en) * 2000-02-23 2001-08-23 Ilkka Heikkila Measurement relating to human body
US20030065257A1 (en) * 2000-01-19 2003-04-03 Mault James R. Diet and activity monitoring device

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030065257A1 (en) * 2000-01-19 2003-04-03 Mault James R. Diet and activity monitoring device
US20010016689A1 (en) * 2000-02-23 2001-08-23 Ilkka Heikkila Measurement relating to human body

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2775901A4 (fr) * 2011-11-11 2015-07-15 Firstbeat Technologies Oy Procédé et système pour évaluer un état physiologique décrivant les ressources d'une personne
WO2014064580A1 (fr) 2012-10-23 2014-05-01 Koninklijke Philips N.V. Système de mesure de stress
JP2015532165A (ja) * 2012-10-23 2015-11-09 コーニンクレッカ フィリップス エヌ ヴェＫｏｎｉｎｋｌｉｊｋｅ Ｐｈｉｌｉｐｓ Ｎ．Ｖ． ストレス測定システム
US10758179B2 (en) 2012-10-23 2020-09-01 Koninklijke Philips N.V. Stress-measuring system
CN105559761A (zh) * 2015-12-18 2016-05-11 安徽寰智信息科技股份有限公司 一种穿戴式健康行为向导系统

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Publication number Publication date
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