Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System

Sensors

Che-Chang Yang²  Yeh-Liang Hsu²  Kao-Shang Shih¹ 

[1] Division of Orthopedics, Shin Kong Wu Ho-Su Memorial Hospital, 95 Wen Chang Rd., Shih Lin District, Taipei 111, Taiwan; E-Mail:;Department of Mechanical Engineering, Yuan Ze University, 135 Yuan-Tung Rd., Chung-Li, Tao-Yuan 320, Taiwan; E-Mail:

关键词: accelerometry;    accelerometer;    Parkinson’s disease;    gait;    mobility;   

DOI  :  10.3390/s110807314

来源: mdpi

【 摘 要 】

This paper presents the development of a wearable accelerometry system for real-time gait cycle parameter recognition. Using a tri-axial accelerometer, the wearable motion detector is a single waist-mounted device to measure trunk accelerations during walking. Several gait cycle parameters, including cadence, step regularity, stride regularity and step symmetry can be estimated in real-time by using autocorrelation procedure. For validation purposes, five Parkinson’s disease (PD) patients and five young healthy adults were recruited in an experiment. The gait cycle parameters among the two subject groups of different mobility can be quantified and distinguished by the system. Practical considerations and limitations for implementing the autocorrelation procedure in such a real-time system are also discussed. This study can be extended to the future attempts in real-time detection of disabling gaits, such as festinating or freezing of gait in PD patients. Ambulatory rehabilitation, gait assessment and personal telecare for people with gait disorders are also possible applications.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.