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WO2016088842A1 - Procédé et système pour analyser la démarche - Google Patents

Procédé et système pour analyser la démarche Download PDF

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Publication number
WO2016088842A1
WO2016088842A1 PCT/JP2015/084034 JP2015084034W WO2016088842A1 WO 2016088842 A1 WO2016088842 A1 WO 2016088842A1 JP 2015084034 W JP2015084034 W JP 2015084034W WO 2016088842 A1 WO2016088842 A1 WO 2016088842A1
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Prior art keywords
sensor
subject
angular velocity
axis
gait
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English (en)
Japanese (ja)
Inventor
茂 但野
量 武田
晴一 遠山
佐野　嘉彦
証英 原田
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Hokkaido University NUC
Nipro Corp
Harada Electronics Industry Co Ltd
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Hokkaido University NUC
Nipro Corp
Harada Electronics Industry Co Ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Measuring 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 or mobility of a limb

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  • the present invention relates to a gait analysis method and a gait analysis system using a body-mounted sensor (also referred to as “wearable sensor”), and more particularly to a gait analysis method and gait for reducing drift of gait data measured by a body-mounted sensor. It relates to an analysis system.
  • Non-Patent Document 1 a method using the H-Gait system previously proposed by the present inventors in Non-Patent Document 1 has been known.
  • a 10 m gait test is usually performed to evaluate patients with gait irregularities associated with stroke, spinal cord injury (SCI), osteoarthritis (OA), multiple sclerosis (MS), and the like.
  • SCI spinal cord injury
  • OA osteoarthritis
  • MS multiple sclerosis
  • body-worn sensors for 10-meter walking tests that provide clinicians with three-dimensional kinematic and spatiotemporal walking parameters.
  • the H-Gait system was developed with the intention of measuring walking for a short time, such as in a 10-meter walking test, for use in evaluating the walking ability and rehabilitation effects of patients with walking disorders.
  • Non-Patent Document 1 does not use a geomagnetic sensor that is affected by a surrounding magnetic field, but has a stretchable band that is in close contact with the subject's body, which is the pelvis (PE), left and right legs
  • Three-axis acceleration sensors and 3 are attached to the thighs (RT, LT), the left and right leg shins (RS, LS), and the left and right leg feet (RF, LF), respectively, in small pockets provided in these bands.
  • a body-mounted sensor configured to house a sensor unit having an axial angular velocity sensor (three-axis gyro sensor), acceleration and angular velocity are measured by each sensor unit while the subject walks on a flat road.
  • the initial posture of these sensor units is estimated using the gravitational acceleration component obtained from the acceleration data when the subject is standing and sitting, and the angle change is estimated using the angular velocity data when the subject is walking. .
  • An algorithm based on quaternion calculation is executed to estimate the attitude of the sensor unit.
  • the estimated posture of the sensor unit is converted into the posture of the body element by the rotation matrix obtained from the trial calculation, and the posture of the body element is determined based on the known motion trajectory analysis protocol for obtaining the motion trajectory of each lower limb part of the subject. It is used to construct a 3D wireframe model animation of the subject inside.
  • the gait analysis was performed on five subjects, and the results were compared with those from a camera-based motion capture system. As a result, 10.14 °, 7.88 ° and 9 ° for hip joint angle, knee joint angle and ankle joint angle, respectively.
  • An average rms error (RMSE) of .75 ° was obtained.
  • Tadano Takeda and Miyagawa, 3D walking analysis using wearable acceleration and angular velocity sensors based on quaternion calculation, Sensors 2013; 13; 9321-9343 (http://www.mdpi.com/1424-8220/13 / 7/9321)
  • an object of the present invention is to provide a gait analysis method and a gait analysis system that improve the gait analysis method described in Non-Patent Document 1 and reduce the drift of gait data measured by a body-mounted sensor.
  • the present invention advantageously solves the problems of the conventional walking analysis method described above, and the walking analysis method according to the present invention has a three-axis angular velocity sensor mounted on a plurality of body parts including the lower limbs of a subject.
  • the attitude angle of each axis of the sensor obtained from the measurement value of each triaxial angular velocity sensor is first time-differentiated twice to remove the linear drift error
  • the drift removal protocol for obtaining the attitude angle of each axis of the sensor from which the drift error has been removed by executing time integration twice is executed.
  • the gait analysis system of the present invention includes a body-mounted sensor having a triaxial angular velocity sensor that is mounted on each of a plurality of body parts including the lower limbs of the subject, and inputs measurement data from the body-mounted sensor to the subject.
  • a body-mounted sensor having a triaxial angular velocity sensor that is mounted on each of a plurality of body parts including the lower limbs of the subject, and inputs measurement data from the body-mounted sensor to the subject.
  • Each attitude angle of each sensor axis obtained from the measured values of the three-axis angular velocity sensors is first time-differentiated twice to remove the linear drift error, and then integrated twice for each sensor.
  • a drift removing means for obtaining a posture angle of the shaft is provided.
  • the drift error increases linearly with time, and the posture angle of each sensor axis obtained from the measured value of each triaxial angular velocity sensor is first twice.
  • a drift removal protocol that obtains the posture angle of each axis of the sensor by integrating the time twice after removing the linear drift error by time differentiation, from the posture angle displacement of each axis of the sensor as the subject walks.
  • the drift error can be effectively reduced, and the motion trajectory of each lower limb part of the subject can be obtained with high accuracy, and consequently, the three-dimensional wire frame model animation of the subject during walking can be constructed with high positional accuracy. it can.
  • the body-mounted sensor is mounted on each of a plurality of body parts including a lower limb of a subject, and a plurality of sensor units each having a triaxial acceleration sensor together with the triaxial angular velocity sensor.
  • the body part is used by using the gravitational acceleration vector obtained from the measurement value of the acceleration sensor of each lower limb part in at least two kinds of postures of the subject.
  • a calibration protocol for reducing the sensor mounting error may be executed.
  • the gait analysis method of the present invention when analyzing the gait of the subject using the body-mounted sensor, high-frequency noise is removed from the raw measurement data of each triaxial angular velocity sensor using a low-pass filter.
  • a filtering protocol may be executed, and an offset removal protocol is executed to remove the offset value from the measurement data of each angular velocity sensor by subtracting the mode value of the measurement data from the measurement data of each of the three-axis angular velocity sensors. Also good.
  • the body-mounted sensor is mounted on a plurality of body parts including a lower limb of a subject, and a plurality of sensor units each having a triaxial acceleration sensor together with the triaxial angular velocity sensor.
  • the gait analysis system includes a gravitational acceleration vector obtained from a measurement value of the three-axis acceleration sensor of each lower limb portion in at least two types of postures of the subject, and an error in mounting the sensor unit to the body portion Calibration means may be provided to reduce the.
  • the gait analysis system of the present invention may include filtering means for removing high-frequency noise from the raw measurement data of each angular velocity sensor using a low-pass filter, and each of the three-axis angular velocity sensors.
  • You may provide the offset removal means which removes an offset value from the measurement data of each triaxial angular velocity sensor by subtracting the mode value of the measurement data from the measurement data.
  • each of the body-mounted sensors is mounted at positions corresponding to a plurality of body parts including the subject's lower limbs of a stretchable exercise clothing worn by the subject. It is preferable to provide a plurality of sensor units having an axial acceleration sensor and a triaxial angular velocity sensor because the position of each sensor unit relative to the body part does not shift during the walking motion of the subject.
  • the low-pass filter of the filtering means is an infinite impulse response digital Butterworth filter because there is almost no signal deterioration in a low frequency band that passes through.
  • the motion trajectory analysis means for obtaining the motion trajectory of each lower limb part of the subject from the posture angle displacement of each axis of the sensor accompanying the walking of the subject. This is preferable because the motion trajectory can be obtained with high accuracy.
  • (A)-(E) are in the sagittal plane of the greater trochanter (GT), knee joint center (Knee), and ankle joint center (Ankle) of the left leg during three gait cycles of each of five subjects. It is explanatory drawing which shows the plot by. (A) to (E) are explanatory diagrams showing plots in the horizontal plane at the center of the knee joint (left figure) and ankle joint (right figure) during three walking cycles of each of five subjects.
  • gait analysis of five healthy subjects is measured using the H-Gait system (see Non-Patent Document 1) that constitutes the main part of the gait analysis system of this embodiment. It was.
  • This H-Gait system does not require an external magnetic field for reference, and the measured values are only from the 3-axis acceleration sensor and 3-axis angular velocity sensor of the sensor unit which is arranged at right angles and fixed at 7 places on the lower limb of the subject. Collected.
  • the body-mounted sensor used in the H-Gait system in this embodiment includes a plurality of body parts including the lower limbs of the subject, that is, the pelvis part, and the left and right large parts.
  • Five sensor units each mounted with a three-axis acceleration sensor and a three-axis angular velocity sensor stored in pockets provided at positions corresponding to the thigh and the left and right shins, respectively,
  • Three-axis acceleration sensors and three-axis angular velocities that are housed in pockets provided at positions corresponding to the insteps of the elastic ring bands attached to the left and right legs, respectively, and mounted at those positions.
  • the sensor unit is equipped with two sensor units, and each sensor unit is thus attached to a stretchable exercise suit that is in close contact with the subject's body. The positional deviation of each sensor unit with respect to the body portion during walking motion of the subject is prevented.
  • the data measured by each sensor unit is sent wirelessly during a walking test to a relay router installed at a fixed place, for example, as in the conventional H-Gait system, and from there, the data of the H-Gait system of this embodiment is preliminarily stored. It is transferred to a normal personal computer that stores the program, or it is sent to a storage medium such as a USB memory possessed by the subject wirelessly or by wire during a walking test and temporarily stored there, and from that storage medium after the walking test It is transferred to the personal computer.
  • the acceleration and angular velocity data measured by each sensor unit during the horizontal walking of the subject is thus collected in the personal computer, and the measured data is then used using an algorithm based on the quaternion of the H-Gait system. These are converted into a three-dimensional posture of each sensor unit and the body part to which they are attached.
  • a novel countermeasure is implemented in this embodiment. This new countermeasure includes a sensor mounting adjustment (calibration) protocol, a Butterworth filter design, removal of sensor offset values and a double differentiation / double integration method. By implementing these countermeasures, the drift is remarkably reduced as described later.
  • the hip / knee and ankle flexion / extension (FE) angles the hip / knee adduction-abduction (AA) angles, / Lower limb joint kinematics such as knee-ankle medial-lateral (IE) rotation angles are provided.
  • a moving wireframe model is created to visually confirm the walking movement.
  • spatio-temporal parameters such as walking cycle, pace, step length, stride length, stride length, stance ratio, and free leg ratio are calculated from the timing of foot contact (HC) and toe separation (TO).
  • the personal computer performs the walking analysis method that is generally the same as in the H-Gait system.
  • the walking posture is calculated by finding the gravitational acceleration direction from the gravitational acceleration component included in the output data of the acceleration sensor, and the initial three-dimensional posture of the body part to which the sensor is attached is calculated.
  • a three-dimensional posture subsequent to the initial three-dimensional posture is estimated by integration of angular velocities measured by a three-axis angular velocity sensor.
  • the angular displacement is expressed using a posture expression based on a quaternion.
  • FIG. 1 shows a three-dimensional wire frame model obtained from the study of the H-Gait system.
  • This wireframe model shows the posture of each body part, the subject's iliac crest width (bicristal breadth), superior anterior iliac spine width (iliospinal breadth), superior anterior iliac spine height (iliospinal height), tibial height ( Created with specific body dimensions such as tibial height and sphyrion height.
  • the sensor unit is attached to seven body parts of the lower limbs.
  • (2-1) Calibration protocol Calibration for reducing the mounting error of the sensor to the body part is executed. Execution of this calibration protocol by the personal computer constitutes a calibration means.
  • the procedure introduced in the walking analysis method of the H-Gait system is used. This procedure includes two simple steps: measuring the gravitational acceleration vector of each lower limb portion in two different postures, standing and sitting for the subject. Since acceleration data includes a gravitational acceleration component, the angle formed by the sensor with respect to the direction of gravity during standing and sitting, that is, a three-dimensional posture (posture) can be calculated.
  • the body-mounted sensor When standing and sitting, the body-mounted sensor is placed in a two-dimensional sagittal plane and assumes only rotational movement on the sagittal plane, and a rotation matrix that converts the dimensions of the sensor coordinate system to the global coordinate system Is guided. Execution of this protocol leads to minimization of wearing errors that occur with the use of body-worn sensors.
  • Offset removal protocol The angular velocity data from the triaxial angular velocity sensor includes an offset value.
  • This offset value is the mode value (mode of data) in the stationary state for each axis of the sensor unit. Value) and subtract it from the whole signal. Execution of this offset removal protocol by the personal computer constitutes an offset removal means.
  • the linear increase ei (t) is removed by two time differentiation operations.
  • the drift error is estimated to increase linearly with time, and according to equations (2) and (3), once the drift error is differentiated with respect to time, it becomes a constant (const), and when it is differentiated with time again, the constant is removed.
  • ⁇ Two time integrals are calculated in relation to the fact that attitude data is always required for further analysis. This requires the addition of appropriate integration constants (c1, c2) at each stage of the calculation as follows.
  • Integral constant c1 is considered the initial angular velocity.
  • the initial angular velocity is 0 (zero).
  • the integration constant c2 is considered to be the initial posture. Therefore, the initial posture calculated from the measurement data of the acceleration sensor in the stationary state (stance phase) is input to the integration constant c2.
  • the drift error of each joint angle is removed by the above-described signal processing and calculation method used for reducing the noise and offset of the triaxial angular velocity sensor data. Execution of this drift removal protocol by the personal computer constitutes drift removal means.
  • Gait is usually defined in terms of temporal and spatial factors that indicate both the time when a gait event occurs and the position and posture of the lower limb in space, respectively.
  • the walking cycle is generally divided into a stance phase and a swing phase. The first begins with an initial foot contact called heel contact (HC) and the second begins with a toe-off (TO) event.
  • HC heel contact
  • TO toe-off
  • the walking cycle GC
  • pace pace
  • SR stride length
  • SL step length
  • SW step width
  • STR stance ratio
  • HC and TO timing events for each foot and take into account spatio-temporal parameters and gait phase (time).
  • the timing of HC and TO can be detected by a tibial accelerometer.
  • the timing events are automatically and directly identified from the angular velocities measured and recorded by the sensor units arranged on both shins.
  • FIG. 2 shows the method used for detecting the HC and TO timing of the foot, the vertical axis shows the angular velocity and the relative position of the toe, and the horizontal axis shows the time.
  • HC timing is detected by a characteristic lateral angular velocity peak and is shown by a solid circle.
  • the TO timing is detected by measuring the negative peak of the relative distance of the toe position relative to the origin of the pelvic (PE) coordinate system and is indicated by a dashed circle.
  • HC is detected by a characteristic lateral angular velocity peak
  • TO timing is detected by measuring the negative peak of the relative distance of the toe position relative to the origin of the pelvis (PE) coordinate system.
  • the walking cycle, stance ratio and free leg ratio are calculated, and by measuring the HC position of both legs, the pace, stride length, step length and step width are Calculated.
  • FIG. 3 shows a wire frame model representing the body of the subject.
  • Xglobal, Yglobal, and Zglobal indicate coordinate axes of the global coordinate system, where the Xglobal axis is the walking direction, the Yglobal axis is the left lateral direction, and the Zglobal axis is the vertical direction.
  • Xlocal, ylocal, zlocal and x'local, y'local, z'local are coordinate axes of a new foot partial coordinate system based on each step of walking.
  • PE, RT, LT, RS, LS, RF, and LF indicate each body part.
  • FIG. 3 shows the relationship between the global coordinate system used in this embodiment and the new foot partial coordinate system created at each step.
  • RF right foot
  • HC HC
  • foot flat FF
  • foot partial coordinate systems xlocal, ylocal and zlocal are created from the heel position of RF.
  • LF FF and HC foot partial coordinate systems xlocal, ylocal and zlocal are created from the RF toe position.
  • the 3D poses of other body parts in the global coordinate system are calculated based on their relative poses with respect to RF. Therefore, the three-dimensional posture of the body part in the global coordinate system is calculated in the order of RF ⁇ RS ⁇ RT ⁇ PE ⁇ LT ⁇ LS ⁇ LF.
  • the motion trajectory of each joint during one walking cycle of each subject is obtained from the joint angle obtained by the above-described procedure by executing the motion trajectory analysis protocol similar to that in the conventional H-Gait system. It is done. Execution of this motion trajectory analysis protocol by the personal computer constitutes motion trajectory analysis means. Analysis of joint kinematics regarding gait tendencies is generally performed during the clinical gait analysis period. According to the gait analysis method of this embodiment, the crotch / knee / ankle flexion / extension (FE) angle, the crotch / knee abduction-abduction (AA) angle, and the crotch / knee / ankle medial-lateral (IE) rotation angle, etc. Kinematic gait parameters can be calculated.
  • Body dimensions are the body part dimensions between each anatomical feature, ie, the distance from the greater trochanter (GT) to the lateral tibial condyle (LCT), the distance from the LCT to the ankle joint (Ankle) (LCT-Ankle), ankle joint height (Ankle Height), right and left GT width (Right-Left GT Width).
  • GT greater trochanter
  • LCT lateral tibial condyle
  • Ankle ankle joint height
  • right and left GT width RVLight-Left GT Width
  • the subject was requested to perform a walking test consisting of a stationary state, a 10 m walking test, and a resting state again.
  • the subject has a sports suit made of spandex that fits the body with five small pockets for holding the sensor unit of the body-mounted sensor of the H-Gait system at positions corresponding to each body part excluding both feet.
  • Suit pants and an elastic band that fits the shoe and has a small pocket for holding the sensor unit at a position corresponding to the upper part of each foot.
  • Reflective markers were placed on 10 anatomical features of the lower limbs, and still images were taken from the front and both sides (see FIG. 1).
  • the walking distance was approximately 10 m, which was equivalent to 10 steps (5 steps for each left and right leg).
  • the IIR + offset removal protocol indicated by the broken line refers to the conventional H-Gait system (Non-Patent Document 1).
  • the IIR + offset removal + DDI protocol indicated by the solid line shows the result of the gait analysis method of this embodiment.
  • FIGS. 5A to 5E show one gait of each subject obtained by executing the same motion trajectory analysis protocol as in the conventional H-Gait system from the joint angle obtained by IIR + offset removal + DDI described above.
  • Figure 6 shows plots in the sagittal plane Zglobal-Xglobal of the greater trochanter (GT), knee joint center and ankle joint center of the right leg during the cycle.
  • the vertical axis indicates the z axis in the global coordinate system
  • the horizontal axis indicates the x axis in the global coordinate system.
  • FIG. 5 shows plots in the sagittal plane Zglobal-Xglobal of the greater trochanter (GT), knee joint center and ankle joint center of the left leg during the cycle.
  • the vertical axis indicates the z axis in the global coordinate system, and the horizontal axis indicates the x axis in the global coordinate system.
  • FIGS. 7A to 7E show three walks of each subject obtained by executing the same movement trajectory analysis protocol as in the conventional H-Gait system from the joint angle obtained by IIR + offset removal + DDI described above. Shown are plots projected on the horizontal plane Xglobal-Yglobal at the center of the knee joint (left) and ankle joint (right) during the cycle.
  • the vertical axis indicates the x axis in the global coordinate system
  • the horizontal axis indicates the y axis in the global coordinate system.
  • the left leg is shown on the left side (shown in red)
  • the right leg is shown on the right side (shown in blue)
  • the black line resulting from the locus of the ankle joint is the toe. Indicates the direction.
  • These trajectories are also plotted at a sampling rate of 33 Hz.
  • Table 3 shows the results of spatiotemporal parameters for each subject. Here, the walking cycle, pace, step length, step width, stride length, asymmetric index, stance ratio, and free leg ratio are shown.
  • the purpose of the gait analysis method and gait analysis system of this embodiment was to remove the drift effect in order to improve the measurement accuracy of gait using a body-mounted sensor.
  • the above results show that the implementation of a combination of multiple measures, ie, sensor mounting error reduction protocol, IIR digital fourth order Butterworth filter, offset removal protocol, and DDI method resulted in a reduction in signal drift.
  • FIGS. 4-1 to 3 show the difference in joint angle after walking for approximately 10 seconds.
  • the difference between the average of all 5 subjects when raw data and IIR + offset removal + DDI after 10 seconds is 2.1 ° for the hip joint angle, the knee joint angle, and the ankle joint angle, respectively. 3 ° and 15.6 °.
  • the difference between performing IIR + offset removal and IIR + offset removal + DDI was 6.2 °, 6.6 °, and 2.2 ° for hip, knee, and ankle angles, respectively. .
  • This means that the proposed measure can eliminate drift errors by an average of 17 ° compared to the integration of raw angular velocity data and an average of 5 ° compared to the conventional H-Gait system (Non-patent Document 1). Indicates that
  • FIGS. 5 and 6 indicate that according to the walking analysis method of this embodiment, the difference in joint trajectory between the left and right GTs, the knee joint, and the ankle joint is visualized using a wire frame model in the sagittal plane. It can be compared. These kinematic gait parameters allow comparison of knee stretch angles between different timings during the gait cycle.
  • the result shown in FIG. 7 enables comparison of relative trajectories in the horizontal plane between the knee joint center and the ankle joint center. According to this data, the left-right symmetry of the trajectories of the left and right knee joints and the ankle joint can be compared.
  • the spatiotemporal parameters provided in Table 3 make it possible to quantify the difference between left and right walking events. By combining kinematic and spatio-temporal parameters, it is possible to detect differences in walking between the left and right lower limbs, and how these differences affect the posture of the body part and the joint position during walking. Can know.
  • the walking analysis method and the walking analysis of the present invention The system is not limited to application to the H-Gait system, and can be applied to other commercially available wearable sensor systems using a triaxial acceleration sensor and a triaxial angular velocity sensor.
  • the data obtained with these systems is the data for follow-up diagnosis after total knee arthroplasty (TKA) by using gait parameters for gait recovery or quantifying the effects of special implants during gait. It would be useful in clinical settings.
  • TKA total knee arthroplasty
  • the drift error is effectively reduced from the posture angle displacement of each sensor axis accompanying the walking of the subject, and the motion trajectory of each lower limb portion of the subject is highly accurate.
  • a three-dimensional wire frame model animation of a walking subject can be constructed with high positional accuracy.

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Abstract

La présente invention a pour but de réduire l'erreur de dérive qui s'accumule à partir de l'intégration. L'invention concerne un procédé d'analyse de la démarche permettant d'analyser la démarche d'un sujet test à l'aide d'un capteur portable, ledit procédé comprenant l'exécution d'un protocole de suppression de dérive pour trouver l'angle d'orientation de chaque axe d'un capteur de vitesse angulaire triaxial en réalisant tout d'abord une double différenciation temporelle de l'angle d'orientation du capteur le long de chaque axe obtenue à partir de mesures effectuées par le capteur et, après suppression de l'erreur de dérive linéaire, en réalisant une double intégration temporelle.
PCT/JP2015/084034 2014-12-03 2015-12-03 Procédé et système pour analyser la démarche Ceased WO2016088842A1 (fr)

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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017014294A1 (fr) * 2015-07-23 2017-01-26 国立大学法人北海道大学 Procédé et système d'analyse de la démarche
JP2018108300A (ja) * 2017-01-05 2018-07-12 キヤノンマーケティングジャパン株式会社 情報処理装置、情報処理方法、プログラム
WO2019067821A1 (fr) 2017-09-28 2019-04-04 Vital Connect, Inc. Étalonnage de capteur prenant en compte des variables dépendantes du sujet et/ou des positions corporelles
WO2020194598A1 (fr) * 2019-03-27 2020-10-01 日本電気株式会社 Dispositif de distinction de marche, procédé de distinction de marche et support d'enregistrement de programme
CN112089580A (zh) * 2020-05-13 2020-12-18 滨州医学院 一种基于干扰补偿的下肢骨骼康复机器人运动控制方法
JP2022549479A (ja) * 2019-09-30 2022-11-25 エフ．ホフマン－ラ ロシュ アーゲー 疾患状態の予測方法

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20240065581A1 (en) * 2019-10-29 2024-02-29 Nec Corporation Gait measurement system, gait measurement method, and program recording medium
JP7495370B2 (ja) * 2021-03-24 2024-06-04 株式会社日立製作所 姿勢認識システム、姿勢認識方法及びプログラム

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2006068312A (ja) * 2004-09-02 2006-03-16 Tamagawa Seiki Co Ltd リハビリ用姿勢モニタリング方法及びリハビリ用姿勢モニタ
JP2011092274A (ja) * 2009-10-27 2011-05-12 Sumitomo Precision Prod Co Ltd 検出装置

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2006068312A (ja) * 2004-09-02 2006-03-16 Tamagawa Seiki Co Ltd リハビリ用姿勢モニタリング方法及びリハビリ用姿勢モニタ
JP2011092274A (ja) * 2009-10-27 2011-05-12 Sumitomo Precision Prod Co Ltd 検出装置

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
TAKEDA RYO ET AL.: "Drift Removal for Improving the Accuracy of Gait Parameters Using Wearable Sensor Systems", SENSORS(WEB, vol. 14, no. 12, pages 23230 - 23247 *

Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11484224B2 (en) 2015-07-23 2022-11-01 Nipro Corporation Gait analysis method and gait analysis system
WO2017014294A1 (fr) * 2015-07-23 2017-01-26 国立大学法人北海道大学 Procédé et système d'analyse de la démarche
JP2018108300A (ja) * 2017-01-05 2018-07-12 キヤノンマーケティングジャパン株式会社 情報処理装置、情報処理方法、プログラム
WO2019067821A1 (fr) 2017-09-28 2019-04-04 Vital Connect, Inc. Étalonnage de capteur prenant en compte des variables dépendantes du sujet et/ou des positions corporelles
CN111133318A (zh) * 2017-09-28 2020-05-08 维塔尔康奈克特公司 考虑受试者相关变量和/或身体定位的传感器校准
US12004852B2 (en) 2017-09-28 2024-06-11 Vital Connect, Inc. Sensor calibration considering subject-dependent variables and/or body positions
JP2020535856A (ja) * 2017-09-28 2020-12-10 ヴァイタル コネクト, インコーポレイテッドVital Connect, Inc. 被験者依存変数および／または体位を考慮するセンサ校正
JP7231161B2 (ja) 2017-09-28 2023-03-01 ヴァイタル コネクト，インコーポレイテッド 被験者依存変数および／または体位を考慮するセンサ校正
EP3688474A4 (fr) * 2017-09-28 2021-06-23 Vital Connect, Inc. Étalonnage de capteur prenant en compte des variables dépendantes du sujet et/ou des positions corporelles
JPWO2020194598A1 (ja) * 2019-03-27 2021-11-11 日本電気株式会社 歩行判別装置、歩行判別方法、およびプログラム
JP7173294B2 (ja) 2019-03-27 2022-11-16 日本電気株式会社 歩行判別装置、歩行判定システム、歩行判別方法、およびプログラム
WO2020194598A1 (fr) * 2019-03-27 2020-10-01 日本電気株式会社 Dispositif de distinction de marche, procédé de distinction de marche et support d'enregistrement de programme
US12123742B2 (en) 2019-03-27 2024-10-22 Nec Corporation Walk discrimination device, walk discrimination method, and program recording medium
JP2022549479A (ja) * 2019-09-30 2022-11-25 エフ．ホフマン－ラ ロシュ アーゲー 疾患状態の予測方法
CN112089580B (zh) * 2020-05-13 2023-02-28 滨州医学院 一种基于干扰补偿的下肢骨骼康复机器人运动控制方法
CN112089580A (zh) * 2020-05-13 2020-12-18 滨州医学院 一种基于干扰补偿的下肢骨骼康复机器人运动控制方法

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