DocumentCode :
149569
Title :
Human gait phase recognition based on thigh movement computed using IMUs
Author :
Abhayasinghe, Nimsiri ; Murray, Iain
Author_Institution :
Dept. of Electr. & Comput. Eng., Curtin Univ. Perth, Perth, WA, Australia
fYear :
2014
fDate :
21-24 April 2014
Firstpage :
1
Lastpage :
4
Abstract :
Human gait analysis is a major topic in pedestrian navigation and geriatric care. Identifying gait phases is important in using human gait for pedestrian navigation and tracking. Most of existing gait phase identification techniques use multiple sensor modules attached to each section of the lower body. This paper discusses the feasibility of recognizing gait phases using a single inertial measurement unit (IMU) placed in a trouser pocket of the subject. The movement of the thigh is computed by fusing accelerometer and the gyroscopic data gathered from the of the IMU. Experimental results indicated that most of the major gait phases such as Initial Contact, Load Response, Mid Stance, Terminal Stance, Pre-Swing and Swing, can be identified by the movement of one thigh tracked by an IMU. It was also noted that the movement of the offside leg can also be estimated from the fused IMU data. This paper presents a method to recognize all major phases of human stride cycle during walking from movement of one thigh.
Keywords :
accelerometers; biomedical measurement; body sensor networks; gait analysis; geriatrics; gyroscopes; inertial navigation; patient care; pattern recognition; pedestrians; units (measurement); accelerometer; gait phase identification techniques; geriatric care; gyroscopic data gathering; human gait analysis; human gait phase recognition; human stride cycle; initial contact; load response; lower body section; mid stance; multiple sensor modules; offside leg movement; pedestrian navigation; pedestrian tracking; preswing; single inertial measurement unit; terminal stance; thigh movement; trouser pocket; walking; Accelerometers; Legged locomotion; Loading; Navigation; Real-time systems; Sensors; Thigh; Human gait analysis; gait phase recognition; inertial sensors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2014 IEEE Ninth International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4799-2842-2
Type :
conf
DOI :
10.1109/ISSNIP.2014.6827604
Filename :
6827604
Link To Document :
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