 코드번호 : |
1 |
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| 발표자 : |
고정길 |
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| 소속 : |
아주대 |
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| 부서 : |
소프트웨어학과 |
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| 직위 : |
교수 |
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| 세션시간 : |
16:00~18:00 |
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| 발표자약력 : |
2007 고려대학교 컴퓨터학과 공학사
2012 Johns Hopkins University Computer Science박사
2012-2015 한국전자통신연구원 선임연구원
2015-현재 아주대학교 소프트웨어학과 조교수
2016-현재 아주대학교 의과대학 의료정보학과 겸임교수 |
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| 강연요약 : |
Recent advances in machine learning based data analytics are opening opportunities for designing effective clinical decision support systems (CDSS). However, common patient movements in hospital wards may lead to faulty measurements in physiological sensor readings, and training a CDSS from such noisy data can cause misleading predictions. We present MediSense, a system to sense, classify, and identify noise-causing motions and activities that affect physiological signals when made by patients. MediSense combines wirelessly connected embedded platforms for motion detection with physiological signal data collected from patients to identify and filter faulty physiological signal measurements. We deploy our MediSense in ICUs, and evaluate its performance using real-patient traces collected from a 4-month pilot study at the Ajou University Hospital Trauma Center. |
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