A 10-item Fugl-Meyer Motor Scale Based on Machine Learning.

Journal: Physical therapy
PMID: 33513236

Abstract

OBJECTIVE: The Fugl-Meyer motor scale (FM) is a well-validated measure for assessing upper extremity and lower extremity motor functions in people with stroke. The FM contains numerous items (50), which reduces its clinical usability. The purpose of this study was to develop a short form of the FM for people with stroke using a machine-learning methodology (FM-ML) and compare the efficiency (ie, number of items) and psychometric properties of the FM-ML with those of other FM versions, including the original FM, the 37-item FM, and the 12-item FM.

Authors

  • Gong-Hong Lin
    Master Program in Long-term Care, College of Nursing, Taipei Medical University, Taipei, Taiwan.
  • Chien-Yu Huang
    Department of Occupational Therapy, I-Shou University, Kaohsiung, Taiwan.
  • Shih-Chieh Lee
    Department of BioIndustry Technology, Da-Yeh University, No. 168, University Rd., Dacun, Changhua, Taiwan, Republic of China.
  • Kuan-Lin Chen
    Department of Occupational Therapy, College of Medicine, National Cheng Kung University, Tainan, Taiwan.
  • Jenn-Jier James Lien
    Department of Computer Science and Information Engineering, National Cheng Kung University.
  • Mei-Hsiang Chen
    Department of Occupational Therapy, Chung Shan Medical University, Taichung, Taiwan.
  • Yu-Hui Huang
    School of Medicine, Chung Shan Medical University; and Department of Physical Medicine & Rehabilitation, Chung Shan Medical University Hospital.
  • Ching-Lin Hsieh
    School of Occupational Therapy, College of Medicine, National Taiwan University, School of Occupational Therapy, Taipei, Taiwan.

Keywords

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