李一宽
（重庆交通大学机电与车辆工程学院，重庆 400074）
摘要：帕金森病是一种常见的神经退行性疾病，目前尚无可治愈的手段，只有通过药物治疗来缓解发病周期。因此，针对早期帕金森病的研究具有重要意义。针对早期帕金森病步态数据较少、识别准确率较低的问题，提出一种基于多特征融合的早期帕金森病步态特征识别方法。该方法对比传统的单一特征识别方法，识别准确率更高，可为早期帕金森病临床诊断提供一种辅助手段。
关键词：早期帕金森病；步态数据；特征融合；分类识别
中图分类号：TP391.41 文献标志码：A 文章编号：1674-2605(2024)01-0009-06
DOI：10.3969/j.issn.1674-2605.2024.01.009
Gait Feature Recognition Method for Early Parkinson's Disease Based on Multi Feature Fusion
LI Yikuan
(School of Mechanical and Vehicle Engineering, Chongqing Jiaotong University, Chongqing 400074, China)
Abstract: Parkinson's disease is a common neurodegenerative disease, and there is currently no cure available. Only drug treatment can alleviate the onset cycle. Therefore, research on early Parkinson's disease is of great significance. Aiming at the problem of limited gait data and low recognition accuracy in early Parkinson's disease, a multi feature fusion based gait feature recognition method for early Parkinson's disease is proposed. Compared with traditional single feature recognition methods, this method has higher recognition accuracy and can provide an auxiliary method for early clinical diagnosis of Parkinson's disease.
Keywords: early Parkinson's disease; gait data; feature fusion; classification recognition
