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Sensors 2012, 12(2), 2255-2283; doi:10.3390/s120202255

Gait Analysis Using Wearable Sensors

1
School of Mechanical Engineering, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing 210094, China
2
Department of Intelligent Mechanical Systems Engineering, Kochi University of Technology, 185 MIyanokuchi, Tosayamada-Cho, Kami-City, Kochi 782-8502, Japan
3
Nakano Lab, Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
*
Author to whom correspondence should be addressed.
Received: 18 January 2012 / Revised: 10 February 2012 / Accepted: 13 February 2012 / Published: 16 February 2012
(This article belongs to the Section Physical Sensors)
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Abstract

Gait analysis using wearable sensors is an inexpensive, convenient, and efficient manner of providing useful information for multiple health-related applications. As a clinical tool applied in the rehabilitation and diagnosis of medical conditions and sport activities, gait analysis using wearable sensors shows great prospects. The current paper reviews available wearable sensors and ambulatory gait analysis methods based on the various wearable sensors. After an introduction of the gait phases, the principles and features of wearable sensors used in gait analysis are provided. The gait analysis methods based on wearable sensors is divided into gait kinematics, gait kinetics, and electromyography. Studies on the current methods are reviewed, and applications in sports, rehabilitation, and clinical diagnosis are summarized separately. With the development of sensor technology and the analysis method, gait analysis using wearable sensors is expected to play an increasingly important role in clinical applications.
Keywords: gait analysis; wearable sensors; human kinematics; joint kinetics; electromyography; clinical application gait analysis; wearable sensors; human kinematics; joint kinetics; electromyography; clinical application
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Tao, W.; Liu, T.; Zheng, R.; Feng, H. Gait Analysis Using Wearable Sensors. Sensors 2012, 12, 2255-2283.

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