Lower-limb motion classification for hemiparetic patients through IMU and EMG signal processing

Hsin Ta Li, Shao Li Han, Min Chun Pan

研究成果: 書貢獻/報告類型會議論文篇章同行評審

10 引文 斯高帕斯(Scopus)

摘要

This study is to develop an automatic classification system for lower limb Brunnstrom stage of hemiparetic patients. The measurement system is employed both IMU and sEMG to acquire the lower limb motion signals from patients. Afterward, this study extracted some useful features for the proposed rule-based classification system and compared different classification algorithms such as k-nearest neighbor, artificial neural network and support vector machine. Instead of leave one out cross validation, the leave subjects out cross validation was used to calculate the successful rate of classification. The results of the experiment on seventeen men and seven women at mean age: 60.6 ± 12.4 years after stroke for more than 6 months show that SVM (95.2%) has the highest accuracy to classify Brunnstrom stage than k-NN (89.2%) and ANN (92.3%). The robustness of this classification system was verified by training different number of subject data. According to the classification result, it can be concluded that the proposed classification system has the potential to predict the lower limb Brunnstrom stage for hemiparetic patients.

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主出版物標題BME-HUST 2016 - 3rd International Conference on Biomedical Engineering
發行者Institute of Electrical and Electronics Engineers Inc.
頁面113-118
頁數6
ISBN(電子)9781509010974
DOIs
出版狀態已出版 - 12 12月 2016
事件3rd International Conference on Biomedical Engineering, BME-HUST 2016 - Hanoi, Viet Nam
持續時間: 5 10月 20166 10月 2016

出版系列

名字BME-HUST 2016 - 3rd International Conference on Biomedical Engineering

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???event.eventtypes.event.conference???3rd International Conference on Biomedical Engineering, BME-HUST 2016
國家/地區Viet Nam
城市Hanoi
期間5/10/166/10/16

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