Automatic Grading of Stroke Symptoms for Rapid Assessment Using Optimized Machine Learning and 4-Limb Kinematics: Clinical Validation Study.

Journal: Journal of medical Internet research
PMID:

Abstract

BACKGROUND: Subtle abnormal motor signs are indications of serious neurological diseases. Although neurological deficits require fast initiation of treatment in a restricted time, it is difficult for nonspecialists to detect and objectively assess the symptoms. In the clinical environment, diagnoses and decisions are based on clinical grading methods, including the National Institutes of Health Stroke Scale (NIHSS) score or the Medical Research Council (MRC) score, which have been used to measure motor weakness. Objective grading in various environments is necessitated for consistent agreement among patients, caregivers, paramedics, and medical staff to facilitate rapid diagnoses and dispatches to appropriate medical centers.

Authors

  • Eunjeong Park
    Cardiovascular Research Institute, Yonsei University College of Medicine, Seoul, Republic Of Korea.
  • Kijeong Lee
    Department of Radiology, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Taehwa Han
    Health-IT Center, Yonsei University College of Medicine, Seoul, Republic of Korea.
  • Hyo Suk Nam
    Department of Neurology, Yonsei University College of Medicine, Seoul, Republic Of Korea.