Monitoring Post-stroke Motor Rehabilitation Using EEG Analysis

被引：0
|
作者：
Singh, Shatakshi [1 ]
Pradhan, Ashutosh [2 ]
Bakshi, Koushik [3 ]
Tiwari, Bablu [1 ]
Dawar, Dimple [4 ]
Kate, Mahesh [4 ]
Pandian, Jeyaraj [4 ]
Kumar, C. S. [5 ]
Mahadevappa, Manjunatha [1 ]
机构：
[1] Indian Inst Technol Kharagpur, Sch Med Sci & Technol, Kharagpur 721302, W Bengal, India
[2] Indian Inst Technol Kharagpur, Dept Elect Engn, Kharagpur 721302, W Bengal, India
[3] Indian Inst Technol Kharagpur, Adv Technol Dev Ctr, Kharagpur 721302, W Bengal, India
[4] Christian Med Coll & Hosp, Dept Neurol, Ludhiana, Punjab, India
[5] Indian Inst Technol Kharagpur, Mech Engn Dept, Kharagpur 721302, W Bengal, India
来源：
INTELLIGENT HUMAN COMPUTER INTERACTION (IHCI 2019) | 2020年 / 11886卷
关键词：
Stroke rehabilitation; EEG; FMA; STROKE;
D O I：
10.1007/978-3-030-44689-5_2
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
EEG has proved to be a vital tool in diagnosing stroke. Now a days EEG is also used for tracking the rehabilitation process after stroke. Post stroke subjects are guided to do some physical activities to help them in regaining lost motor activity. The study presented here acquires EEG data from patients undergoing rehabilitation process and tracks the improvement in their motor ability. This is done by correlating change in Fugl-Meyer Assessment (FMA) score with some of the features obtained from EEG data. A significant correlation was found between FMA change and mean absolute value (r = 0.6, p < 0.001) of the EEG signal and also between change in mean alpha power ratio (left/right) vs. Delta FMA (r = -0.71, p < 0.001). The high correlation values of these features suggest that they can be used for monitoring rehabilitation after stroke.
引用
收藏
页码：13 / 22
页数：10
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