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Micromachines 2018, 9(9), 442; https://doi.org/10.3390/mi9090442

MEMS Inertial Sensors Based Gait Analysis for Rehabilitation Assessment via Multi-Sensor Fusion

1
School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, China
2
Dalian Neusoft University of Information, Dalian 116023, China
3
Dalian Medical University, Dalian 116027, China
*
Author to whom correspondence should be addressed.
Received: 31 July 2018 / Revised: 30 August 2018 / Accepted: 30 August 2018 / Published: 3 September 2018
(This article belongs to the Special Issue MEMS Accelerometers)
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Abstract

Gait and posture are regular activities which are fully controlled by the sensorimotor cortex. In this study, fluctuations of joint angle and asymmetry of foot elevation in human walking stride records are analyzed to assess gait in healthy adults and patients affected with gait disorders. This paper aims to build a low-cost, intelligent and lightweight wearable gait analysis platform based on the emerging body sensor networks, which can be used for rehabilitation assessment of patients with gait impairments. A calibration method for accelerometer and magnetometer was proposed to deal with ubiquitous orthoronal error and magnetic disturbance. Proportional integral controller based complementary filter and error correction of gait parameters have been defined with a multi-sensor data fusion algorithm. The purpose of the current work is to investigate the effectiveness of obtained gait data in differentiating healthy subjects and patients with gait impairments. Preliminary clinical gait experiments results showed that the proposed system can be effective in auxiliary diagnosis and rehabilitation plan formulation compared to existing methods, which indicated that the proposed method has great potential as an auxiliary for medical rehabilitation assessment. View Full-Text
Keywords: MEMS sensors; gait analysis; rehabilitation assessment; body sensor network MEMS sensors; gait analysis; rehabilitation assessment; body sensor network
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Qiu, S.; Liu, L.; Zhao, H.; Wang, Z.; Jiang, Y. MEMS Inertial Sensors Based Gait Analysis for Rehabilitation Assessment via Multi-Sensor Fusion. Micromachines 2018, 9, 442.

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