Research progress on intelligent assessment system for upper limb function of stroke patients.
10.7507/1001-5515.202112046
- Author:
Sujiao LI
1
;
Kun WU
1
;
Qiaoling MENG
1
;
Hongliu YU
1
Author Information
1. Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai 200093, P. R. China.
- Publication Type:Review
- Keywords:
Function assessment;
Intelligent evaluation;
Machine learning;
Stroke;
Upper limb
- MeSH:
Algorithms;
Humans;
Physical Therapy Modalities;
Stroke/diagnosis*;
Stroke Rehabilitation;
Upper Extremity
- From:
Journal of Biomedical Engineering
2022;39(3):620-626
- CountryChina
- Language:Chinese
-
Abstract:
At present, the upper limb function of stroke patients is often assessed clinically using a scale method, but this method has problems such as time-consuming, poor consistency of assessment results, and high participation of rehabilitation physicians. To overcome the shortcomings of the scale method, intelligent upper limb function assessment systems combining sensors and machine learning algorithms have become one of the hot research topics in recent years. Firstly, the commonly used clinical upper limb functional assessment methods are analyzed and summarized. Then the researches on intelligent assessment systems in recent years are reviewed, focusing on the technologies used in the data acquisition and data processing parts of intelligent assessment systems and their advantages and disadvantages. Lastly, the current challenges and future development directions of intelligent assessment systems are discussed. This review is hoped to provide valuable reference information for researchers in related fields.
