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Automated Evaluation of Upper-limb Motor Function Impairment using Fugl-Meyer Assessment

Title
Automated Evaluation of Upper-limb Motor Function Impairment using Fugl-Meyer Assessment
Authors
Lee, Seung-HeeLee, Yang-SooKim, Jong-Hyun
DGIST Authors
Lee, Seung-Hee
Issue Date
2017
Citation
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Type
Article
Article Type
Article in Press
Keywords
AutomationBinsClassification (of information)Computer circuitsFunction evaluationLearning algorithmsLearning systemsROMShoulders (road)Binary logicElbowFugl-meyer assessmentsSensor systemsStrokeThumbUpper limbsWristWearable sensors
ISSN
1534-4320
Abstract
The Fugl-Meyer assessment (FMA) is the most popular instrument for evaluating upper extremity motor function in stroke patients. However, it is a labor-intensive and timeconsuming method. This paper proposes a novel automated FMA system to overcome these limitations of the FMA. For automation, we used Kinect v2 and force sensing resistor sensors owing to their convenient installation as compared with body-worn sensors. Based on the linguistic guideline of the FMA, a rule-based binary logic classification algorithm was developed to assign FMA scores using the extracted features obtained from the sensors. The algorithm is appropriate for clinical use because it is not based on machine learning, which requires additional learning processes with a large amount of clinical data. The proposed system was able to automate 79% of the FMA tests because of optimized sensor selection and the classification algorithm. In clinical trials conducted with nine stroke patients, the proposed system exhibited high scoring accuracy (92%) and time efficiency (85% reduction in clinicians’ required time). IEEE
URI
http://hdl.handle.net/20.500.11750/4625
DOI
10.1109/TNSRE.2017.2755667
Publisher
Institute of Electrical and Electronics Engineers Inc.
Files:
There are no files associated with this item.
Collection:
Robotics EngineeringETC1. Journal Articles


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