Research on Recognition of Basic Rehabilitation Actions for Stroke Patients
XIN Zaihai1, XING Mengmeng2, CAO Hui1, YANG Feng3, WEI Sumeng2
1. College of Intelligence and Information Engineering, Shandong University of Traditional Chinese Medicine, Jinan Shangdong
250355, China; 2. China Rehabilitation Research Center, Beijing 100071, China; 3. Department of Equipment, Affiliated Hospital of
Shandong University of Traditional Chinese Medicine, Jinan Shandong 250000, China
Abstract：Objective To explore a recognition method of basic action units of upper limb rehabilitation based on inertial sensor
signals, which can realize unsupervised exercise for stroke patients. Methods Data collection and recognition were carried out for
six basic action units in upper limb rehabilitation exercise. Firstly, inertial sensors were used to collect upper limb motion data.
Secondly, feature extraction was carried out to extract the statistical features in the data. Finally, machine learning model was used
for classification. Results Using extreme learning machine, support vector machine, random forest and k-nearest neighbor, the
average recognition rate of six basic action units collected in the experiment can reach about 99% and the error is no more than 1%.
Conclusion In this study, the proposed method based on inertial sensor for basic rehabilitation of upper limb after stroke has certain
effectiveness and robustness.
辛在海1，邢蒙蒙2，曹慧1，杨锋3，魏稣濛2. 脑卒中患者的基本康复动作识别研究[J]. 中国医疗设备, 2022, 37(5): 33-36.
XIN Zaihai1, XING Mengmeng2, CAO Hui1, YANG Feng3, WEI Sumeng2. Research on Recognition of Basic Rehabilitation Actions for Stroke Patients. China Medical Devices, 2022, 37(5): 33-36.
