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mFAST: Automatic Stoke Evaluation System for Time-Critical Treatment with Multimodal Feature Collection and Machine Learning Classification

Authors
 Eunjeong Park  ;  Taehwa Han  ;  Hyo Suk Nam 
Citation
 PROCEEDINGS OF 2020 12TH INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING (ICCAE 2020), : 38-41, 2020-02 
Journal Title
 PROCEEDINGS OF 2020 12TH INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING (ICCAE 2020) 
Issue Date
2020-02
Keywords
Mobile Healthcare ; Automatic Evaluation ; Decision Support ; Stroke
Abstract
In this paper, we introduce an automatic evaluation system, mFAST, for the examination of neurological deficits and personalized stroke prediction. The proposed system enables mobile monitoring of stroke patients utilizing sensors and machine learning techniques. This research is composed of objective and rapid measurement of neurological deficits of stroke patients; development of stroke-triage prediction; and data collection of monitored neurological deficits and personalized stroke prediction system to rapidly recognize the symptoms and enhance the treatment in hospitals. The research proposes to implement the mobile services for FAST (Face, Arm, Speech, Time) stroke activation to measure face palsy, arm weakness, speech disturbance and to analyze the automatically collected data. The measured FAST features can be used in the prediction of stroke scores including NIHSS (National Institute of Health for Stroke Scale), CPSS (Cincinnati Pre-hospital Stroke Scale), MRC (Medial Research Council) to enable stroke patients to be treated in a restricted time frame.
Full Text
https://dl.acm.org/doi/abs/10.1145/3384613.3384653
DOI
10.1145/3384613.3384653
Appears in Collections:
1. College of Medicine (의과대학) > Research Institute (부설연구소) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Neurology (신경과학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Yonsei Biomedical Research Center (연세의생명연구원) > 1. Journal Papers
Yonsei Authors
Nam, Hyo Suk(남효석) ORCID logo https://orcid.org/0000-0002-4415-3995
Park, Eunjeong(박은정)
Han, Taehwa(한태화)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/190256
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