Title :
A gait recognition system for rehabilitation based on wearable micro inertial measurement unit
Author :
Li, Zhi ; Zhang, Guanglie
Author_Institution :
Coll. of Comput. Sci. & Software Eng., Shenzhen Univ., Shenzhen, China
Abstract :
Gait recognition and analysis is one of the most important biometric methods for medical treatments, virtual reality games and human motion identification. Gait recognition based on wearable MEMS inertial sensors is proposed for medical rehabilitation with Physical Activities Healthcare System (PATHS) in this paper. We use relative wavelet energy as features for support vector machine (SVM) recognition algorithm to discriminate walking pattern from other motion patterns. This method has been proven capable of distinguishing walking gait from other regular physical activities through our experimental validation.
Keywords :
bioMEMS; gait analysis; health care; patient rehabilitation; support vector machines; biometric methods; gait recognition system; medical rehabilitation; physical activities; physical activities healthcare system; support vector machine recognition algorithm; walking gait analysis; wavelet energy; wearable MEMS inertial sensors; wearable microinertial measurement unit; Discrete wavelet transforms; Feature extraction; Humans; Legged locomotion; Sensors; Support vector machines;
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2011 IEEE International Conference on
Conference_Location :
Karon Beach, Phuket
Print_ISBN :
978-1-4577-2136-6
DOI :
10.1109/ROBIO.2011.6181530
