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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
Kim, Jong Hyun
Issue Date
2018-01
Citation
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(1), 125-134
Type
Article
Article Type
Article
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 time-consuming 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). © 2001-2011 IEEE.
URI
http://hdl.handle.net/20.500.11750/4625
DOI
10.1109/TNSRE.2017.2755667
Publisher
Institute of Electrical and Electronics Engineers Inc.
Related Researcher
  • Author Kim, Jonghyun REL(Rehabilitation Engineering Laboratory)
  • Research Interests Rehabilitation engineering; Robotics; Nonlinear control
Files:
There are no files associated with this item.
Collection:
Department of Robotics EngineeringREL(Rehabilitation Engineering Laboratory)1. Journal Articles


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