@inproceedings{ef3080786691412ab10a081837d4a379,
title = "An automatic recognition system for patients with movement disorders based on wearable sensors",
abstract = "Movement disorder in lower extremity has been a major concern for the elder worldwide. Early diagnosis and effective therapy monitoring is an important prerequisite to treat patients and reduce health care costs. Objective and non-invasive assessment strategies are an urgent need in order to achieve this goal. In this study, we apply a wearable, lightweight and easy applicable sensor based gait analysis system to measure gait cycle. We analyse the features of different kinds of patients with movement disorder. An automatic pattern recognition system by machine learning and statistical approaches is proposed to support the classification of different neuro-degenerative diseases. The results demonstrate that it is feasible to apply computational classification techniques in characterise these three diseases with the features extracted from gait cycles.",
keywords = "data mining, gait recognition, movement disorders, wearable sensors",
author = "Zhouheng Li and Weihai Chen and Jianhua Wang and Jingmeng Liu",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 9th IEEE Conference on Industrial Electronics and Applications, ICIEA 2014 ; Conference date: 09-06-2014 Through 11-06-2014",
year = "2014",
month = oct,
day = "20",
doi = "10.1109/ICIEA.2014.6931487",
language = "英语",
series = "Proceedings of the 2014 9th IEEE Conference on Industrial Electronics and Applications, ICIEA 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1948--1953",
booktitle = "Proceedings of the 2014 9th IEEE Conference on Industrial Electronics and Applications, ICIEA 2014",
address = "美国",
}