@inproceedings{69bb0b2dacd340a1a2b0fe92bdfc5302,
title = "A Gait Recognition System for Rehabilitation Based on Wearable Micro Inertial Measurement Unit",
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. {\textcopyright} 2011 IEEE.",
author = "Zhi Li and Guanglie Zhang",
year = "2011",
month = dec,
doi = "10.1109/ROBIO.2011.6181530",
language = "English",
isbn = "978-1-4577-2136-6",
series = "IEEE International Conference on Robotics and Biomimetics, ROBIO",
publisher = "IEEE",
pages = "1678--1682",
booktitle = "Proceedings of the 2011 IEEE International Conference on Robotics and Biomimetics",
address = "United States",
note = "2011 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2011 ; Conference date: 07-12-2011 Through 11-12-2011",
}