WO2008107832A1 - Estimation du stress - Google Patents

Estimation du stress Download PDF

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Publication number
WO2008107832A1
WO2008107832A1 PCT/IB2008/050757 IB2008050757W WO2008107832A1 WO 2008107832 A1 WO2008107832 A1 WO 2008107832A1 IB 2008050757 W IB2008050757 W IB 2008050757W WO 2008107832 A1 WO2008107832 A1 WO 2008107832A1
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WO
WIPO (PCT)
Prior art keywords
person
stress
spectral distribution
level
eye
Prior art date
Application number
PCT/IB2008/050757
Other languages
English (en)
Inventor
Ralph Kurt
Frank Wartena
Ronaldus M. Aarts
Petronella H. Pelgrim
Joanne H. D. M. Westerink
Wilhelmus J. J. Stut
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 WO2008107832A1 publication Critical patent/WO2008107832A1/fr

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
    • A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
    • A61B3/113—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for determining or recording eye movement
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1103—Detecting eye twinkling
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
    • A61B5/163—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state by tracking eye movement, gaze, or pupil change
    • 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
    • A61B5/4884—Other medical applications inducing physiological or psychological stress, e.g. applications for stress testing
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6813—Specially adapted to be attached to a specific body part
    • A61B5/6814—Head
    • A61B5/6821—Eye

Definitions

  • the present invention relates to a system, method and computer program for estimating a condition of a person, in particular a level of stress or tiredness that a person is experiencing.
  • an alertness monitoring system uses reflectance measurement of infrared light pulses to monitor eye movement of a vehicle or machine operator.
  • the data is used to measure eye and eyelid movement for determining the presence of slow or drifting eye movements, and/or eyelid closure and optionally one or more of, absence of saccadic movement, loss of eye co-ordination, wavering eyelids, partial eye closure, and drooping eyelids as indicators of loss of attention and drowsiness.
  • the eye movements of a subject are analyzed using reflected infra red light to obtain measures of the blink amplitude velocity ratio and the saccade amplitude velocity ratio.
  • the eye movements are recorded over a period of some seconds.
  • the average values of the eye movement measurements over this period are determined and are continuously compared with eye movement data indicative of degrees of alertness which correlate to blood alcohol content values so that the monitor provides an indication of the operator's legal fitness to operate the vehicle or machine from the point of view of drowsiness no matter how it is caused.
  • the system is focused on the alertness of the operator, which is a property that can change very rapidly and requires therefore intrinsically a short measurement (typically within seconds). It is an object of the invention to provide a system and method for determining a person's condition over an extended period of time.
  • a system for estimating a condition of a person, in particular a level of stress or tiredness that a person is experiencing.
  • the system comprises measurement means for performing a plurality of eye movement measurements of the person during a time interval and accumulating means for accumulating the measurements and determining a spectral distribution thereof. It further comprises analyzing means for estimating the condition based on the spectral distribution. In this way, a good estimation can be made of a person's condition, in particular the "accumulated" stress of a person over an extended period of time.
  • the invention is based on the insight that extreme situations such as a staring view, very concentrated or fixed viewpoint, very monotonous eye movements (with a fixed speed or frequency) as experienced when driving along a straight road or in a mass production line, or very fast eye movements as required e.g. in a race car, when playing a computer game or working in a stock exchange office are perceived as stressful and they are experienced as extremely tiring when performed for an elongated/extended period of time. In all these extreme situations, the spectral distribution of fast, slow and medium speed eye movements is not balanced. On the other hand situations in which fast, slow and medium speed eye movements are in a good balance over time are perceived as relaxed and less tiring.
  • the accumulating means are adapted for classifying the measurements in a class or interval in order to obtain the spectral distribution. This is an easy way of determining the spectral distribution without the need of any complicated algorithms or calculations. According to an embodiment, at least 100 but preferably at least 500 or even
  • the analyzing means are adapted for categorizing the level of stress as high or normal. In this way a clear and easily understandable feedback about a person's stress level can be given. In case of an even spectral distribution of the measurements the level of stress is categorized as normal. In case of an uneven or unbalanced distribution of the measurements or in case of peaks in the distribution of the measurements the level of stress is categorized as high.
  • the system comprises output means for generating a signal depending on the estimated level of stress.
  • these output means may send a warning, such as an acoustic signal to the user or a signal forcing the user make a break for relaxation exercises.
  • the measurement means are adapted to measure the eye movement, by measuring at least one of the following parameters: speed of eye movements, frequency of eye movements, amplitude of eye movements, direction of eye movement, focus distance (measured by eye curvature) and pupil size variation (reacts on different brightness/ color levels). These parameters are very suitable for estimating the stress of the user.
  • the measuring means for measuring the eye movements may comprise an optical sensing system, such as a camera mounted on a PC in an office environment or in a car. They also may comprise suitable sensing means, such as optical, mechanical or electrical sensors integrated in specially designed goggles or glasses.
  • the system comprises a movement sensor for sensing the movement of the head of the person. It is advantageous to take the movement of the head into account, allowing the eye movement detection to be more robust.
  • the measurement means comprise multiple eye movement trackers and are adapted to combine the measurements of these trackers. As a result of combining the measurements the system becomes more robust.
  • a method for estimating a condition of a person, in particular a level of stress or tiredness that a person is experiencing comprising the following steps: - performing a plurality of eye movement measurements of the person during a time interval, accumulating the measurements and determining a spectral distribution thereof, and estimating the condition based on the spectral distribution.
  • the method may be implemented by means of a suitable computer program.
  • FIG. 1 shows a block diagram of the system according to the present invention
  • Figure 2 shows a block diagram of the measurement means
  • Figure 3 shows a diagram of the distribution of the values of the accumulated measurements in typical situations.
  • Figure 1 shows a non-obtrusive eye movement detection system that allows to deduce/calculate/estimate the level of stress that an analyzed person is experiencing based on the analysis of accumulated measurement signals. It comprises measurement means 10 for measuring one or more parameters indicative of eye movements of the person during a certain time interval, accumulating means 20 for accumulating the measurements an determining a spectral distribution thereof, analyzing means 30 for estimating the stress level of the person based on the spectral distribution and output means 40 for generating a signal depending on the estimated level of stress.
  • the system comprises further measurement means 50 for measuring the movements of the head of the person.
  • the measurement means 10 are adapted for detecting the eye movement pattern of a person.
  • the measurement means may comprise suitable optical sensing means such as a camera.
  • a camera for eye movement detection is well known in the art and is feasible, low cost and reliable.
  • a camera for eye movement detection is well known in the art and is feasible, low cost and reliable.
  • outside-in systems one or more cameras record the eye of the participant and determine eye-movement parameters through imaging algorithms.
  • the cameras are positioned in front of the participant.
  • One of the advantages of these systems is given by the fact that the camera can be integrated into a monitor, and therefore is basically invisible to an analyzed person.
  • inside-out systems the person has to wear a special device on the head.
  • the image of the eye is led into a mini-camera by using mirrors. This mini-camera records the eye and the actual line of vision is found out through imaging algorithms.
  • the measurement means 10 may comprise other suitable sensing means such as mechanical or electrical sensors.
  • suitable sensing means such as mechanical or electrical sensors.
  • the use of such sensors for eye movement detection is well known in the art.
  • the sensors may be mounted near the eye. They may be for example included in smart electronic contact lenses or specially designed goggles or glasses. Parameter such as the eye movement speed, frequency of movements, amplitude (x and y direction) of the movements, direction of eye movement, focus distance (measured by eye curvature), pupil size variation (reacts on different brightness/ color levels) and others can be detected and used for estimating the level of stress.
  • FIG. 2 shows a block diagram of measurement means 10 comprising IR sensors.
  • the measurement means 10 comprise an IR pulse generator 12, generating IR- light in the direction of the eye and IR sensors or detectors 13,14 detecting the IR light reflected by the eye. Detectors 13,14 detect reflected light in different directions (e.g. horizontally and vertically) across the eye. This reflected light corresponds to the movement of the eye ball. From the movement of the eye ball, the speed of the eye movement may be derived, according to algorithms well known in the art.
  • the measurement signals are transferred to the accumulating means 20 by means of wireless transmitter 16. Preferably, the reflected light of both eyes is measured (not shown).
  • the reflection of IR-signals from the eye reference is made to the earlier cited patent US 7,071,831 B2.
  • the accumulating means 20 and the analyzing means 30 may be implemented by a suitably programmed processor and a memory.
  • the accumulating means 20 accumulate the measurements over a prolonged time period of several minutes or even hours.
  • the measurements may exist of a plurality of measurements of a certain parameter representative of the eye movement, each of them being averaged over a certain time interval.
  • the total time period of the measurements may be 1 hour. This time period is divided in a plurality of sub-periods of for example 2 seconds each, resulting in a total of 1800 sub-periods.
  • the parameter is measured during each sub-period and the mean value thereof is determined.
  • the 1800 measurements thus obtained are each classified in a suitable interval or class. In this way, a spectral distribution (histogram) of the measurements is created.
  • the number of sub periods preferably is at least 100 but it may also be much higher for instance at least 5000.
  • the analyzing means 30 perform an analysis of the spectral distribution in order to estimate the stress of a person.
  • Figure 3 shows the spectral distribution of the values of the accumulated measurements in typical situations.
  • the diagram shows the accumulated intensity I, or in other words the occurrence rate of the values of the frequency f of eye movements over a certain measurement period.
  • a first typical spectrum is indicated as “a” and is a typical spectrum of a person that is steering or is very concentrated.
  • the spectrum includes a high accumulated intensity of low frequencies of eye movements. This means that low frequencies of eye movements occurred much more often during the time period of the measurements than high frequencies of eye movements.
  • the spectrum "b” is a typical spectrum of a person during a relatively monotonous (eye) activity such as reading or working in an assembly line production. In this case the measurement values are more evenly distributed but very high and very low frequency values are absent.
  • the spectrum “c” is a typical spectrum of a person doing an activity for which very fast eye movements are required as e.g. during car racing or computer games.
  • the spectrum includes a high accumulated intensity of high frequencies of eye movements.
  • the spectrum “d” is a typical spectrum of a person performing normal
  • the system here described is based on the insight that all extreme situations including staring view, very concentrated or fixed viewpoint, very monotonous eye movements (with a fixed speed or frequency) as experienced when driving along a straight road or in a mass production lines, and very fast eye movements as required e.g. in a race car, when playing a computer game or working in a stock exchange office are perceived as stressful and they are experienced as extremely tiring when performed for an elongated/extended period of time.
  • situations in which fast, slow and medium speed eye movements are in a good balance in time are perceived as relaxed and less tiring.
  • the analyzing means 30 determine certain characteristics of this distribution, which are representative of the stress level. Such characteristics are for example the full width at half-maximum of the distribution, the number, the height, the width, and slope of its peaks, the absence of certain values, its median, the kurtosis, etc.
  • a relatively broad and balanced spectrum is considered to be normal.
  • the accumulated stress level is categorized as normal.
  • the output means 40 can send a warning to the user, such as an acoustic signal or in some cases it could force you to make a break for relaxation exercises similar as know from RSI.
  • the system according to the invention could be linked to the monitor and display the presented information in a way forcing counterbalancing of the eye movement (e.g. by altering speed of scrolling, movement on screen, dataflow, light level, font size etc.)
  • Figure 3 shows how the distribution of the frequency of eye movements may be used to estimate the level of accumulated stress of a person.
  • the distribution of other parameters related to eye movements may be used, such as the eye movement speed, the amplitude of the eye movements in horizontal and vertical direction, the direction of eye movement, the focus distance (measured by eye curvature) or the pupil size variation (reacts on different brightness/ color levels).
  • the system according to the invention could according to a preferred embodiment also perform smart background or baseline subtraction (from time to time).
  • the spectrum could be fit by a lower order polynomial function and subtracted, i.e. this becomes the new zero line. After that subtraction all positive values (counts) in the classes (said predefined intervals) remain, whereas negative counts are set to zero. From here clustered accumulation continues. One could in this way easier detect peaks and also detect, when a certain monotonous behavior occurs that falls in a class that was underrepresented in the previous time period.
  • the spectral distribution shown in figure 3 may be obtained by measuring the (mean) frequency of the eye movements for each sub-period and classifying the values thus obtained as explained herein above.
  • the spectral distribution of the frequency of movements may also be obtained by measuring the eye movement over the whole time interval in the time domain and converting this measurement to the frequency domain by a Fast Fourier Transform. In this way, the spectral distribution shown in figure 3 is obtained without classification of measurement values of sub periods.
  • the system may use multiple eye movement trackers, for example a stationary camera and a sensor on the head and combine the signals generated by these trackers to achieve a more robust eye movement detection.
  • the combination of both signals can be performed with a so-called Kalman filter. This is very suitable for parameter estimation and parameter tracking and is able to remove artifacts. If there is no known relation between both trackers, a look up table can be implemented that has a specific entry for each possible value of the outputs of the reference devices (trackers).
  • a Kalman filter For parameter estimation, a Kalman filter, an extended Kalman filter, or a particle filter can be used. These filters are adaptive and are very suitable for parameter estimation and parameter tracking, they are well-known and widely used in various domains, like robotics, physics, chemistry and engineering, see IEEE Signal Processing Magazine 20(5), Sept. 2003, pp.19-38 for an overview.
  • the described system could also be used as learning tool, to analyze your day or the last hour helping you to improve e.g. your time management. Thereto the system could be linked to a user's agenda of this day.
  • a movement sensor 50 for example an accelerometer on the head of the user.
  • This movement sensor 50 may be integrated into the user's glasses or goggles. This allows the detection of head movements. Taking these head movements into account makes the eye movement detection more robust.
  • This input can also be used with the Kalman filter, which is mentioned above.

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  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Veterinary Medicine (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • General Health & Medical Sciences (AREA)
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Abstract

Le système décrit permet d'estimer un niveau de stress ou de fatigue ressenti par une personne. Le système comprend des moyens de mesure (10) pour effectuer une pluralité de mesures de mouvements oculaires de la personne pendant un intervalle de temps et des moyens d'accumulation (20) pour cumuler les mesures et déterminer une répartition spectrale de celles-ci. Le système comprend également des moyens d'analyse (30) pour estimer le niveau de stress à partir de la répartition spectrale.
PCT/IB2008/050757 2007-03-07 2008-03-03 Estimation du stress WO2008107832A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP07103681 2007-03-07
EP07103681.8 2007-03-07

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WO2008107832A1 true WO2008107832A1 (fr) 2008-09-12

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Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012021316A2 (fr) * 2010-08-09 2012-02-16 Uop Llc Procédé d'hydrocraquage sélectif pour la production soit de pétrole soit de distillat
US9545224B2 (en) 2010-11-08 2017-01-17 Optalert Australia Pty Ltd Fitness for work test
CN111616666A (zh) * 2014-03-19 2020-09-04 直观外科手术操作公司 使用眼球凝视跟踪的医疗装置、系统和方法
WO2022055383A1 (fr) 2020-09-11 2022-03-17 Harman Becker Automotive Systems Gmbh Système et procédé permettant de déterminer une demande cognitive
EP3984449A1 (fr) 2020-10-19 2022-04-20 Harman Becker Automotive Systems GmbH Système et procédé permettant de déterminer des caractéristiques de battement cardiaque
WO2022250560A1 (fr) 2021-05-28 2022-12-01 Harman International Industries, Incorporated Système et procédé destinés à quantifier un état mental
US11792386B2 (en) 2014-03-19 2023-10-17 Intuitive Surgical Operations, Inc. Medical devices, systems, and methods using eye gaze tracking for stereo viewer

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5601090A (en) * 1994-07-12 1997-02-11 Brain Functions Laboratory, Inc. Method and apparatus for automatically determining somatic state
US6102847A (en) * 1995-12-22 2000-08-15 Stielau; Guenter Bio-feedback process and device for affecting the human psyche
US6120461A (en) * 1999-08-09 2000-09-19 The United States Of America As Represented By The Secretary Of The Army Apparatus for tracking the human eye with a retinal scanning display, and method thereof
US20040143170A1 (en) * 2002-12-20 2004-07-22 Durousseau Donald R. Intelligent deception verification system
US20060203197A1 (en) * 2005-02-23 2006-09-14 Marshall Sandra P Mental alertness level determination

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5601090A (en) * 1994-07-12 1997-02-11 Brain Functions Laboratory, Inc. Method and apparatus for automatically determining somatic state
US6102847A (en) * 1995-12-22 2000-08-15 Stielau; Guenter Bio-feedback process and device for affecting the human psyche
US6120461A (en) * 1999-08-09 2000-09-19 The United States Of America As Represented By The Secretary Of The Army Apparatus for tracking the human eye with a retinal scanning display, and method thereof
US20040143170A1 (en) * 2002-12-20 2004-07-22 Durousseau Donald R. Intelligent deception verification system
US20060203197A1 (en) * 2005-02-23 2006-09-14 Marshall Sandra P Mental alertness level determination

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012021316A2 (fr) * 2010-08-09 2012-02-16 Uop Llc Procédé d'hydrocraquage sélectif pour la production soit de pétrole soit de distillat
WO2012021316A3 (fr) * 2010-08-09 2012-06-07 Uop Llc Procédé d'hydrocraquage sélectif pour la production soit de pétrole soit de distillat
US9545224B2 (en) 2010-11-08 2017-01-17 Optalert Australia Pty Ltd Fitness for work test
CN111616666A (zh) * 2014-03-19 2020-09-04 直观外科手术操作公司 使用眼球凝视跟踪的医疗装置、系统和方法
US11792386B2 (en) 2014-03-19 2023-10-17 Intuitive Surgical Operations, Inc. Medical devices, systems, and methods using eye gaze tracking for stereo viewer
WO2022055383A1 (fr) 2020-09-11 2022-03-17 Harman Becker Automotive Systems Gmbh Système et procédé permettant de déterminer une demande cognitive
EP3984449A1 (fr) 2020-10-19 2022-04-20 Harman Becker Automotive Systems GmbH Système et procédé permettant de déterminer des caractéristiques de battement cardiaque
WO2022250560A1 (fr) 2021-05-28 2022-12-01 Harman International Industries, Incorporated Système et procédé destinés à quantifier un état mental

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