Literature DB >> 20723901

Ambulatory estimation of foot placement during walking using inertial sensors.

H Martin Schepers1, Edwin H F van Asseldonk, Chris T M Baten, Peter H Veltink.   

Abstract

This study proposes a method to assess foot placement during walking using an ambulatory measurement system consisting of orthopaedic sandals equipped with force/moment sensors and inertial sensors (accelerometers and gyroscopes). Two parameters, lateral foot placement (LFP) and stride length (SL), were estimated for each foot separately during walking with eyes open (EO), and with eyes closed (EC) to analyze if the ambulatory system was able to discriminate between different walking conditions. For validation, the ambulatory measurement system was compared to a reference optical position measurement system (Optotrak). LFP and SL were obtained by integration of inertial sensor signals. To reduce the drift caused by integration, LFP and SL were defined with respect to an average walking path using a predefined number of strides. By varying this number of strides, it was shown that LFP and SL could be best estimated using three consecutive strides. LFP and SL estimated from the instrumented shoe signals and with the reference system showed good correspondence as indicated by the RMS difference between both measurement systems being 6.5 ± 1.0 mm (mean ± standard deviation) for LFP, and 34.1 ± 2.7 mm for SL. Additionally, a statistical analysis revealed that the ambulatory system was able to discriminate between the EO and EC condition, like the reference system. It is concluded that the ambulatory measurement system was able to reliably estimate foot placement during walking.
Copyright © 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20723901     DOI: 10.1016/j.jbiomech.2010.07.039

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  25 in total

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2.  Measurement of foot placement and its variability with inertial sensors.

Authors:  John R Rebula; Lauro V Ojeda; Peter G Adamczyk; Arthur D Kuo
Journal:  Gait Posture       Date:  2013-06-26       Impact factor: 2.840

3.  Gait analysis using floor markers and inertial sensors.

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Journal:  Sensors (Basel)       Date:  2012-02-07       Impact factor: 3.576

4.  Real-time gait cycle parameter recognition using a wearable accelerometry system.

Authors:  Che-Chang Yang; Yeh-Liang Hsu; Kao-Shang Shih; Jun-Ming Lu
Journal:  Sensors (Basel)       Date:  2011-07-25       Impact factor: 3.576

5.  Height compensation using ground inclination estimation in inertial sensor-based pedestrian navigation.

Authors:  Sang Kyeong Park; Young Soo Suh
Journal:  Sensors (Basel)       Date:  2011-08-15       Impact factor: 3.576

6.  A wearable ground reaction force sensor system and its application to the measurement of extrinsic gait variability.

Authors:  Tao Liu; Yoshio Inoue; Kyoko Shibata
Journal:  Sensors (Basel)       Date:  2010-11-16       Impact factor: 3.576

7.  Drift-free position estimation of periodic or quasi-periodic motion using inertial sensors.

Authors:  Win Tun Latt; Kalyana Chakravarthy Veluvolu; Wei Tech Ang
Journal:  Sensors (Basel)       Date:  2011-05-31       Impact factor: 3.576

Review 8.  Inertial sensor-based methods in walking speed estimation: a systematic review.

Authors:  Shuozhi Yang; Qingguo Li
Journal:  Sensors (Basel)       Date:  2012-05-10       Impact factor: 3.576

9.  Evaluating the Accuracy of Virtual Reality Trackers for Computing Spatiotemporal Gait Parameters.

Authors:  Michelangelo Guaitolini; Fitsum E Petros; Antonio Prado; Angelo M Sabatini; Sunil K Agrawal
Journal:  Sensors (Basel)       Date:  2021-05-11       Impact factor: 3.576

10.  Pre-operative ambulatory measurement of asymmetric lower limb loading during walking in total hip arthroplasty patients.

Authors:  Alicia Martínez-Ramírez; Dirk Weenk; Pablo Lecumberri; Nico Verdonschot; Dean Pakvis; Peter H Veltink
Journal:  J Neuroeng Rehabil       Date:  2013-04-20       Impact factor: 4.262

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