Research on Abnormal Gait Recognition Algorithms for Stroke Patients Based on Array Pressure Sensing System

被引：0

作者：

Wang, Mo ^{[1
]}

Yong, Shanshan ^{[1
]}

He, Chunjiu ^{[1
]}

Chen, Hongying ^{[1
]}

Zhang, Sixu ^{[1
]}

Peng, Chen ^{[1
]}

Wang, Xin'an ^{[1
]}

机构：

[1] Peking Univ, Shenzhen Grad Sch, Key Lab Integrated Microsyst, Shenzhen, Peoples R China

来源：

PROCEEDINGS OF 2019 IEEE 3RD INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2019) | 2019年

关键词：

plantar pressure; pressure image; stroke; gait analysis; cluster analysis; CROSS-VALIDATION; DBSCAN;

D O I：

10.1109/itnec.2019.8729511

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Plantar pressure image is an important tool for gait analysis. In the gait rehabilitation training of stroke patients, it can provide effective quantitative data reference for doctors to accurately assess the recovery status of patients and formulate targeted treatment programs. In this paper, a gait recognition algorithm for pressure sensing image is proposed. Through DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm and minimum circumscribed rectangular algorithm, footprints can be accurately located in the pressure image for feature extraction. Three different degrees of abnormal gait and healthy gait are trained based on SVM (Support Vector Machine) algorithm. The training results can accurately identify the above abnormal gait, with an average accuracy of 91.4%.

引用

页码：1560 / 1563

页数：4

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