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Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
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Deep-Learning-Based Stroke Screening Using Skeleton Data from Neurological Examination Videos.

Taeho Lee1, Eun-Tae Jeon2, Jin-Man Jung3,4

  • 1Department of Electrical and Electronic Engineering, Hanyang University, 55 Hanyangdaehak-ro, Sangnok-gu, Ansan 15588, Korea.

Journal of Personalized Medicine
|October 27, 2022
PubMed
Summary

This study introduces an AI system to detect neurological diseases like stroke from videos. It analyzes patient movements and facial features to provide early screening and management for the elderly.

Keywords:
deep learninglandmark extractionrecurrence plotstroke diagnosis

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Area of Science:

  • Gerontology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • The elderly population faces a rising burden of chronic diseases, including stroke.
  • Aging demographics and workforce shortages increase demand for accessible healthcare solutions.
  • Smart healthcare systems are crucial for personalized care and reducing hospitalizations.

Purpose of the Study:

  • To develop an AI system for screening and managing neurological diseases using video analysis.
  • To investigate the feasibility of detecting stroke from video data in elderly patients.
  • To leverage AI for early detection and personalized care in geriatric neurology.

Main Methods:

  • Neurological examination videos were transformed into landmark data, capturing key features like hand, face, and body movements.
  • Sequences of landmark data were converted into recurrence plots, visualized as images.
  • Deep neural networks, specifically convolutional neural networks with feature fusion, were employed to classify stroke risk.

Main Results:

  • The AI system successfully extracted major features from neurological examination videos.
  • Recurrence plots derived from landmark data were utilized for image-based analysis.
  • The proposed deep learning approach demonstrated capability in classifying stroke from video data.

Conclusions:

  • AI-driven video analysis offers a promising approach for early screening of neurological diseases, particularly stroke.
  • This technology can support personalized management and potentially reduce healthcare burdens for the elderly.
  • Further application of this disease screening test is recommended to validate its clinical utility.