Literature DB >> 17513111

The reliability of using accelerometer and gyroscope for gait event identification on persons with dropped foot.

Hongyin Lau1, Kaiyu Tong.   

Abstract

Identification of gait events using an optimal sensor set and a reliable algorithm would be useful in the clinical evaluation of patients with dropped foot. This article describes a threshold detection method for identifying gait events and evaluating the reliability of a system on ten subjects with dropped foot and three non-impaired controls. The system comprised three sensor units of accelerometers and gyroscopes attached at the thigh, shank and foot of the impaired leg in subjects with dropped foot, and the dominant leg in the controls. A performance index was devised to compare the values of different measuring directions of the sensor units and evaluate the system's reliability. The performance index, with the ideal value equal to 1, depended on the classification accuracy and timing variation of the turning points. These were obtained from the threshold detection method that distinguished the absolute maximum and minimum turning points from local maximum and minimum turning points. It was found that some specific turning points could effectively identify gait events with a high median value in the performance index. These turning points included: the minimum turning point in superior-inferior acceleration on the thigh at loading response (0.972); the minimum turning point in anterior-posterior angular velocity on the shank at pre-swing (0.955) and the maximum turning point in superior-inferior acceleration on the foot at initial swing (0.954). Combining the results of sensor measurements in different orientations and attachment locations could be used for gait event identification. It was shown that the threshold detection method is reliable. Portable gait-monitoring devices can be used for monitoring of daily activities and functional control.

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Year:  2007        PMID: 17513111     DOI: 10.1016/j.gaitpost.2007.03.018

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  23 in total

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3.  Gait Cycle Validation and Segmentation Using Inertial Sensors.

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Journal:  Med Biol Eng Comput       Date:  2008-03-18       Impact factor: 2.602

5.  A preliminary test of measurement of joint angles and stride length with wireless inertial sensors for wearable gait evaluation system.

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6.  Automatic identification of gait events using an instrumented sock.

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7.  Markov jump linear systems-based position estimation for lower limb exoskeletons.

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Journal:  Sensors (Basel)       Date:  2014-01-22       Impact factor: 3.576

8.  Estimation of step-by-step spatio-temporal parameters of normal and impaired gait using shank-mounted magneto-inertial sensors: application to elderly, hemiparetic, parkinsonian and choreic gait.

Authors:  Diana Trojaniello; Andrea Cereatti; Elisa Pelosin; Laura Avanzino; Anat Mirelman; Jeffrey M Hausdorff; Ugo Della Croce
Journal:  J Neuroeng Rehabil       Date:  2014-11-11       Impact factor: 4.262

9.  Fourier-based integration of quasi-periodic gait accelerations for drift-free displacement estimation using inertial sensors.

Authors:  Angelo Maria Sabatini; Gabriele Ligorio; Andrea Mannini
Journal:  Biomed Eng Online       Date:  2015-11-23       Impact factor: 2.819

10.  Effectiveness of variable-gain Kalman filter based on angle error calculated from acceleration signals in lower limb angle measurement with inertial sensors.

Authors:  Yuta Teruyama; Takashi Watanabe
Journal:  Comput Math Methods Med       Date:  2013-10-27       Impact factor: 2.238

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