Kinematic Analysis of Human Gait Based on Wearable Sensor System for Gait Rehabilitation

Quantitative analysis of gait phases is needed for gait rehabilitation. This study proposes a wireless wearable system for real-time monitoring of plantar pressure distribution and acceleration information during walking. The goal of this paper is to investigate the potential use of the support vect...

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Bibliographic Details
Published inJournal of medical and biological engineering Vol. 36; no. 6; pp. 843 - 856
Main Authors Chen, Weihai, Xu, Yingjun, Wang, Jianhua, Zhang, Jianbin
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2016
Springer Nature B.V
Subjects
Acceleration
Accelerometers
Biocompatibility
Biomedical Engineering and Bioengineering
Cell Biology
Data acquisition
Disease transmission
Engineering
Force plates
Gait
Human motion
Imaging
Original Article
Osteoarthritis
Plantar pressure
Pressure distribution
Quantitative analysis
Radiology
Rehabilitation
Stress concentration
Support vector machines
Walking
Wearable technology
Foot insole
Support vector machine (SVM)
Gait phase detection
Plantar pressure distribution
Wearable system
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Summary:Quantitative analysis of gait phases is needed for gait rehabilitation. This study proposes a wireless wearable system for real-time monitoring of plantar pressure distribution and acceleration information during walking. The goal of this paper is to investigate the potential use of the support vector machine technique with force-sensitive resistor and acceleration values to detect phases in the cyclic motion of the human dynamic gait. The device consists of a flexible insole with seven force-sensitive elements and a triaxial accelerometer that is integrated with an electronic board for high-frequency data acquisition, pre-filtering, and wireless transmission to a remote data computation and storage unit. The design and development of the device are presented, along with its experimental characterization and validation when applied to healthy participants and those diagnosed with osteoarthritis walking at various speeds, and benchmarked against an instrumented force platform. The experimental results verify that the proposed method is valid, with an accuracy of as high as 94.08%.
ISSN:1609-0985
2199-4757
DOI:10.1007/s40846-016-0179-z