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i-Sheet: A Low-Cost Bedsheet Sensor for Remote Diagnosis of Isolated Individuals.
Tapwal, Riya; Misra, Sudip; Deb, Pallav Kumar.
  • Tapwal R; Department of Computer Science and EngineeringIndian Institute of Technology Kharagpur Kharagpur 721302 India.
  • Misra S; Department of Computer Science and EngineeringIndian Institute of Technology Kharagpur Kharagpur 721302 India.
  • Deb PK; Department of Computer Science and EngineeringIndian Institute of Technology Kharagpur Kharagpur 721302 India.
IEEE Sens J ; 23(2): 906-913, 2023 Jan.
Article in English | MEDLINE | ID: covidwho-2245667
ABSTRACT
In this article, we propose a smart bedsheet-i-Sheet-for remotely monitoring the health of COVID-19 patients. Typically, real-time health monitoring is very crucial for COVID-19 patients to prevent their health from deteriorating. Conventional healthcare monitoring systems are manual and require patient input to start monitoring health. However, it is difficult for the patients to give input in critical conditions as well as at night. For instance, if the oxygen saturation level decreases during sleep, then it is difficult to monitor. Furthermore, there is a need for a system that monitors post-COVID effects as various vitals get affected, and there are chances of their failure even after the recovery. i-Sheet exploits these features and provides the health monitoring of COVID-19 patients based on their pressure on the bedsheet. It works in three phases 1) sensing the pressure exerted by the patient on the bedsheet; 2) categorizing the data into groups (comfortable and uncomfortable) based on the fluctuations in the data; and 3) alerting the caregiver about the condition of the patient. Experimental results demonstrate the effectiveness of i-Sheet in monitoring the health of the patient. i-Sheet effectively categorizes the condition of the patient with an accuracy of 99.3% and utilizes 17.5 W of the power. Furthermore, the delay involved in monitoring the health of patients using i-Sheet is 2 s which is very diminutive and is acceptable.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Randomized controlled trials Topics: Long Covid Language: English Journal: IEEE Sens J Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Randomized controlled trials Topics: Long Covid Language: English Journal: IEEE Sens J Year: 2023 Document Type: Article