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Multi-modal Analysis for Stroke Severity Monitoring and AF Detection

This project aims to develop a real-time and continuous monitoring system for stroke severity and atrial fibrillation detection based on multi-modal analysis of physiological signals. The goal is to improve patient outcomes by providing timely interventions. The first year focuses on algorithm development and validation using ICU bio-signals, while the second year involves implementation and trial on the MTK bio-platform.

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Multi-modal Analysis for Stroke Severity Monitoring and AF Detection

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  1. Progressive Acute Stroke Severity Monitoring and Atrial Fibrillation Detection Based on Multi-modal Analysis of Physiological Signals以多項性生理訊號分析應用於長期監控急性中風病患嚴重度與偵測心房顫動Future Working Item Meeting計畫期間：105/10/01~107/09/30PI:湯頌君醫師、吳安宇教授、賴達明醫師Sep 30, 2016

  2. Project Goal • Stroke is the leading cause of mortality and morbidity • Atrial fibrillation (AF) is a risk factor for ischemic stroke • Aim of the study: • Stroke severity monitoring and • AF detection based on bio-signals in hospital • Advantage: • Real-time • Continuous • Inexpensive

  3. Goal of First Year First half of the year • Involve bio-signals of ICU for enhanced algorithm development & validation • Utilize medical-grade sensors for recording and analyzing bio-signals • PPG-based AF detection • Test with non-stroke patients (test set) • Refine the algorithm • Stroke severity monitoring • Outcome prediction => Progressive monitoring Second half of the year

  4. Goal of Second Year • Implementation and trial on MTK bio-platform • Multi-modal analysis for progressive stroke severity monitoring • PPG for AF detection EEG EKG PPG ABP

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