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Physio6: A Sensor-Based Monitoring System for 6-Minute Walking Test in the Era of COVID-19
7th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2021 ; : 133-137, 2021.
Article in English | Scopus | ID: covidwho-1699527
ABSTRACT
Coronavirus disease of 2019 (COVID-19) is still severe nowadays, and plentiful COVID-19 patients need careful rehabilitation. The 6-minute walking test (6MWT) is a common clinical trial that requires the patient to walk as far as possible in a corridor for 6 minutes, significantly indicating patients' cardiopulmonary disease conditions and rehabilitation. A traditional 6MWT provides the 6-minute walking distance (6MWD) as the primary result for clinical analysis. In this paper, we propose Physio6, a sensor-based monitoring system for 6MWT, which monitors one patient's various physiological signals and indicates her/his condition during the test. The system also provides the functions of early warning based on physiological signal monitoring and automatically or manually recording the adverse events, such as hypoxia or dyspnea. Moreover, Physio6 is able to communicate with the existing systems in hospitals, and to generate a comprehensive report that summarizes the performance of the patient in the current 6MWT and even in the past ones. Our system has been deployed in four hospitals. Compared with the conventional distance-based measurement, our preliminary validation reveals that the extracted physiological parameters are promisingly valuable for clinical decision-making. System quality and device comfort are also confirmed by questionnaires. The potential of leveraging this system to perform the remote 6MWT at home/in communities as a solution of COVID-19 patient rehabilitation monitoring is also discussed. © 2021 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 7th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2021 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 7th IEEE International Conference on Network Intelligence and Digital Content, IC-NIDC 2021 Year: 2021 Document Type: Article