A Comparative Study of Motion Recognition Methods for Efficacy Assessment of Upper Limb Function
文献类型：期刊论文
| 作者 | Jialing Feng; Jie He; Shaofa Chen; Zhexiao Guo; Sandeep Pirbhulal; Wanqing Wu; Guo Dan |
| 刊名 | International Journal of Adaptive Control and Signal Processing
 |
| 出版日期 | 2018 |
| 文献子类 | 期刊论文 |
| 英文摘要 | Physical disorders are considered to be the most severe disability in patients with hemiplegia after stroke. Currently, most studies have used motion feature extraction methods and machine learning-based methods to evaluate the functional degree of post-stroke in hemiplegic patients. This research collected feature data from patients under diverse experimental conditions and then fed them into different machine learning classifiers. However, few studies have compared which classifiers and experimental condition could achieve more precise assessments in a specific condition. In this paper, we compared the accuracy of four different classifiers in a conservative motion recognition method. A motion sensor was used for monitoring the upper limb action, and four conservative machine learning classifiers, which map the features to Fugl-Meyer scale, were chosen for comparison. Ten post-stroke hemiplegic-simulated subjects performed a group of pre-defined actions, and these motion data were used to generate a group of features reflecting the information of each pre-defined action. We input the features into four classifiers to generate corresponding classifiers. With the support vector machine classifier, prediction accuracy at 97.79% was achieved in the experiment data, which outperformed previous reports. In conclusion, support vector machivnes perform better than the other three classifiers in the assessment of the degree of post-stroke hemiplegics. It is encouraging that results have been generated with the proposed assessment method in this exploratory study. |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/14187]  |
| 专题 | 深圳先进技术研究院_医工所 |
| 推荐引用方式 GB/T 7714 | Jialing Feng,Jie He,Shaofa Chen,et al. A Comparative Study of Motion Recognition Methods for Efficacy Assessment of Upper Limb Function[J]. International Journal of Adaptive Control and Signal Processing,2018. |
| APA | Jialing Feng.,Jie He.,Shaofa Chen.,Zhexiao Guo.,Sandeep Pirbhulal.,...&Guo Dan.(2018).A Comparative Study of Motion Recognition Methods for Efficacy Assessment of Upper Limb Function.International Journal of Adaptive Control and Signal Processing. |
| MLA | Jialing Feng,et al."A Comparative Study of Motion Recognition Methods for Efficacy Assessment of Upper Limb Function".International Journal of Adaptive Control and Signal Processing (2018). |
入库方式： OAI收割
来源：深圳先进技术研究院
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