WO2016038215A1 - Système et procédé pour étudier quantitativement le contrôle postural de personnes - Google Patents

Système et procédé pour étudier quantitativement le contrôle postural de personnes Download PDF

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Publication number
WO2016038215A1
WO2016038215A1 PCT/EP2015/070895 EP2015070895W WO2016038215A1 WO 2016038215 A1 WO2016038215 A1 WO 2016038215A1 EP 2015070895 W EP2015070895 W EP 2015070895W WO 2016038215 A1 WO2016038215 A1 WO 2016038215A1
Authority
WO
WIPO (PCT)
Prior art keywords
postural control
quantitative parameters
body parts
sensor system
quantitative
Prior art date
Application number
PCT/EP2015/070895
Other languages
German (de)
English (en)
Inventor
Karen OTTE
Alexander Brandt
Sebastian Mansow-Model
Original Assignee
Motognosis Ug
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 Motognosis Ug filed Critical Motognosis Ug
Priority to EP15775634.7A priority Critical patent/EP3190966A1/fr
Publication of WO2016038215A1 publication Critical patent/WO2016038215A1/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
    • A61B5/40—Detecting, measuring or recording for evaluating the nervous system
    • A61B5/4005—Detecting, measuring or recording for evaluating the nervous system for evaluating the sensory system
    • A61B5/4023—Evaluating sense of balance
    • 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
    • A61B5/1113—Local tracking of patients, e.g. in a hospital or private home
    • A61B5/1114—Tracking parts of the body
    • 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
    • A61B5/1126—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique
    • A61B5/1127—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique using markers
    • 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
    • A61B5/1126—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique
    • A61B5/1128—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique using image analysis
    • 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
    • A61B5/1121—Determining geometric values, e.g. centre of rotation or angular range of movement
    • A61B5/1122—Determining geometric values, e.g. centre of rotation or angular range of movement of movement trajectories

Definitions

  • the present invention relates to a system and method for sensor-based generation of quantitative parameters that describe the postural control of a person in the performance of stand-assessments and can be used in clinical and therapeutic diagnostics.
  • assessments short and specific exercises that involve a specific motor task.
  • a problem here is when the assessment of postural control is only subjective by the staff. On the one hand, this can only be carried out roughly qualitatively with the naked eye; only an assessment is made in rough categories. For example, in the Berg Balance Scale, one of the most established routine tests for assessing balance behavior, the various subtasks are evaluated only in the integer categories 0 (poor) to 4 (good). Finer changes in the symptoms, for example during therapy, can not be detected.
  • the assessments made vary widely, both among individuals and between different investigators. Thus, these are only comparatively comparable and suitable for comparative or historical diagnostics.
  • An embodiment of the invention uses a marker-based 3D sensor system.
  • marker-based systems different markers can be attached to a person at fixed positions, which are recorded with a measuring system of several sensors.
  • the markers are arranged so that several markers describe a person's limb in a defined manner.
  • the movement of the markers in the room can then be detected by the measuring system and can be recorded and further processed by the measuring system.
  • the defined positions of the markers allow the human joints and extremities to be derived as a model and made available for further processing.
  • This invention embodiment has the advantage that works very accurate, but brings a number of disadvantages. For example, the markers must be laboriously attached and calibrated to the body prior to measurement, and the measurements are spatially bound to fixed system installations.
  • An alternative embodiment of the invention uses a markerless 3D sensor system.
  • Markerless systems are, for example, a combination of RGB video cameras, or 3D cameras that can generate a depth image of the environment via emitted infrared light.
  • the result of these camera systems is a set of 3D points in rasterized form, so-called depth pixels.
  • the disadvantage of this embodiment of the invention is that there is no marker information for the identification of specific body points, so that from the depth pixel images using body model-based analysis and / or machine learning algorithms first people must be recognized and transferred to a skeleton model with spatial body points.
  • the noise behavior of the individual body measuring points is compensated depending on the measuring system used.
  • a 'moving average' or a 'lowpass' filter can be applied to any body point signal.
  • the length of the moving average window would depend on the sampling rate of the measuring system and should not exceed one second.
  • the filtering allows compensation of system-related noise while preserving desired signal characteristics (for example, signal excursions in the case of dropouts and compensatory movements).
  • all measured position data are normalized by transforming them into a uniform coordinate system which remains the same over different measurements. This allows better comparability between different measurements and is necessary for all analyzes that do not only consider body-internal relations.
  • a concrete example of such a normalization is the compensation of variations in the sensor orientation in relation to the measured person taking into account the horizontal and vertical angle of the sensor as well as the rotation angle of the measurement subject by transforming all measurement points by compensating rotation.
  • the movement of the body point of the lower back in three-dimensional space is considered.
  • This describes the fluctuation behavior of a person when looking at the movement relative to a base point.
  • the base point can be calculated, for example, as the initial lot of the body to the ground, as the center of the feet or as the center of the ankle over the total measurement.
  • the movement is then described as a vector from the base point to the hip point and can describe the fluctuation behavior by means of angle changes (see drawing). Gen 13, 14 and 15).
  • the movement in the metric coordinate system can be described using measured values such as the speed, acceleration and deflection of the hip point. In order to achieve the independence of these measured values from the height of the hip point, all metric measured values are normalized by this height.
  • compensatory movements of the arms are considered. As the balance diminishes, the arm posture may change and the arms may make compensatory movements. This behavior serves to stabilize the body. Quantification of these arm movements and posture is possible by, for example, the angular velocity, acceleration and displacement of the movements.
  • the arm vector from the shoulder point to the elbow point (see drawing 16) or hand point is used to calculate the angles between the vectors of individual frames.
  • the angle between the body vector and the arm vector can be used as a basis for calculation.
  • leg movement is quantified.
  • the body reacts subconsciously with a trapping motion in which an attempt is made to prevent a fall.
  • This movement is typically a lunge in which the leg tries to catch the body. In case of illness, this behavior may be delayed or not sufficient to prevent a fall.
  • measurements such as step length / width, number of steps per measurement, reaction time, speed and acceleration of the foot are used.
  • collected quantitative values can be compared with previously obtained values from a standard cohort. These values are provided by the system and are used to classify the new measured values into one or more control groups. The comparison can be supported by automatic grouping methods such as classification methods or clustering methods.
  • the system gives execution instructions to the person to be measured. This must be instructed in advance, how it has to behave during the measurement and how the measurement is carried out correctly. This can be done by another person (operator) or by the system itself. Visual and auditory media (image and sound) can be used.
  • the instructions provided by the system can be used in combination with a markerless measuring system alone and autonomously in non-clinical environments such as home. Further applications are available in the rehabilitation environment or sports facilities.
  • Another embodiment relates to the automatic verification of the implementation and corresponding feedback.
  • the performance of the measurement should be checked before and during the recording and the subject should be made aware of potential sources of error. This includes in particular, but not exclusively, the examination of the measuring environment for interfering influences (light sources, furniture), the starting position and posture before and during the measurement, as well as dangerous situations (eg too much instability).
  • the person may be alerted in an optional step if the measurement was invalid and should be repeated. This is especially useful in a scenario in which no operator additionally checks the measurement.
  • a specially developed software was used, which was used by an operator, while a test person carried out the assessment at a defined distance of 2 meters in front of the sensor.
  • This software displayed in real time the RGB video received from the sensor and visualized the body points received from the Kinect SDK as a superimposition of the RGB video, allowing the operator to visually verify the person tracking.
  • the operator was shown the implementation instructions of the current assessment phase, which he communicated to the test person. The operator started each assessment manually by pressing a button, whereupon the software played an acoustic signal and started the data acquisition. Then, a countdown was displayed for each phase, and the system automatically skipped to the next phase or stopped recording, with an audible signal playing again at the phase transition and end of recording.
  • the data recorded by the software was stored on the laptop PC in the form of a comma-separated value file (.csv).
  • This file contains the 3D point coordinates of each articulation point over the entire measurement.
  • each measured frame is provided with a consecutive number and a time stamp.
  • the measurement data was read into the MATLAB software for further processing.
  • the spatial and temporal course of the joint points was also used as 'joint signal'.
  • a moving average filter of length 30 (corresponding to 1 s) was applied to all 3 dimensions of each joint signal, as illustrated in drawing 4.
  • the origin of the vectors was first calculated. For this, the mean position of both ankles was determined over the entire measurement. Starting from this point, a vector for the hip (middle) point was determined for each measurement time point. Subsequently, the angles between temporally successive vectors in the 2D projection planes (XY and ZY, see drawings 13 and 14) and in 3D space (see drawing 15) were calculated. In order to determine the speed of the fluctuation behavior, the difference of successive angles representing the angular velocities of the fluctuation vectors during the measurements was calculated. The mean value of the angular velocity of a measurement serves in this example as quantification and comparison value of the fluctuation behavior to the norm cohort.
  • the average angular velocity of the arm movements for the right and left arms was determined.
  • the angular deflection was described by a vector from the shoulder point to the elbow point of the respective arm (see drawing 16).
  • Figure 6 shows the distribution of the groups as a histogram of the closed-end 3D body swing speed with open eyes, with 22 MS patients (23.2%) above the 95th percentile and 7 MS patients (7.4%) above the 99th. In Figure 7 this is shown for closed eyes, with 33 MS patients (34.7%) above the 95th percentile and 30 MS patients (31.6%) even above the 99th.
  • Table 4 shows the correlation of closed-state 3D body velocity with the various clinical scores recorded in Table 1. Overall, the correlations with gait, motor skills, visual, cerebellar and comprehensive disease scores are moderate to good, mostly of high significance. The correlation between EDSS and closed loop 3D body swing speed with closed eyes is illustrated in FIG.

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  • Health & Medical Sciences (AREA)
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  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

La présente invention concerne un système pour étudier quantitativement le contrôle postural de personnes en réalisant des évaluations de posture, qui comprend : - un système de détection en 3D pour mesurer dans le temps le positionnement dans l'espace des parties du corps d'une personne, - des moyens pour extraire des informations du système de détection, - des moyens pour montrer et lire des informations audiovisuelles, - des moyens pour déterminer des paramètres quantitatifs concernant aussi bien les modifications du corps dans son intégralité que de chaque partie du corps, en particulier des membres.
PCT/EP2015/070895 2014-09-11 2015-09-11 Système et procédé pour étudier quantitativement le contrôle postural de personnes WO2016038215A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
EP15775634.7A EP3190966A1 (fr) 2014-09-11 2015-09-11 Système et procédé pour étudier quantitativement le contrôle postural de personnes

Applications Claiming Priority (2)

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DE102014013828.3 2014-09-11
DE102014013828.3A DE102014013828A1 (de) 2014-09-11 2014-09-11 System und Verfahren zur quantitativen Untersuchung der posturalen Kontrolle von Personen

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Cited By (1)

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US10653351B2 (en) 2017-10-28 2020-05-19 Tata Consultancy Services Limited Systems and methods for quantification of postural balance of users in an augmented reality environment

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ZA201701187B (en) 2016-08-10 2019-07-31 Tata Consultancy Services Ltd Systems and methods for identifying body joint locations based on sensor data analysis

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10653351B2 (en) 2017-10-28 2020-05-19 Tata Consultancy Services Limited Systems and methods for quantification of postural balance of users in an augmented reality environment

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DE102014013828A1 (de) 2016-03-31
EP3190966A1 (fr) 2017-07-19

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