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스마트워치의 생리 데이터 기반 질병 모니터링 체계를 활용한 COVID-19 이상탐지
김진현(Jin Hyun Kim),한용섭(Yong Seop Han),조형래(Hyeongrae Cho),윤혜린(Hyerin Yoon),김현수(Hyeonsu Kim),구다예(Daye Gu),강태신(Taeseen Kang) 대한전기학회 2021 전기학회논문지 Vol.70 No.8
Real-Time vital-sign from patients are important information that implies the current health status and behavior of patients. Recently, Mishra et al. have shown that COVID-19 can be detected by analyzing the patient’s vital signs and behaviors, i.e., heart rates and steps, using anomaly detection techniques. This paper presents a medical IoT platform, called MiT Eco-platform, which is designed to gather patient’s physiological data through a smartwatch and to increase the efficiency of data labeling for building an AI model for medical diagnosis and treatment. Furthermore, we present a real-time COVID-19 detection approach advanced from the approach of using anomaly detection Mishra et al. that will be run on MiT Eco-platform. As a result, we show performance evaluation results of preemptively detecting the COVID-19 infection for the same samples of the COVID-19 infected ones of Mishra et al., comparing with the anomaly detection approach of Mishra et al.. We expect that physiological data through smartwatches on daily life can be continuously gathered and effectively labeled by the MiT Eco-platform for various studies in medical area.