Evidence map›Paper›PMID 36913205›Full record

ArticleIEEE sensors journal2023

i-Sheet: A Low-Cost Bedsheet Sensor for Remote Diagnosis of Isolated Individuals.

Riya Tapwal, Sudip Misra, Pallav Kumar Deb

Open access · bronzeAbstract read
In one paragraph

Article in IEEE sensors journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Riya TapwalDepartment of Computer Science and EngineeringIndian Institute of Technology Kharagpur Kharagpur 721302 India.ORCID https://orcid.org/0000-0002-1801-2734
Sudip MisraDepartment of Computer Science and EngineeringIndian Institute of Technology Kharagpur Kharagpur 721302 India.ORCID https://orcid.org/0000-0002-2467-6414
Pallav Kumar DebDepartment of Computer Science and EngineeringIndian Institute of Technology Kharagpur Kharagpur 721302 India.ORCID https://orcid.org/0000-0002-4605-9046
Indian Institute of Technology Kharagpur · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Artificial intelligenceCOVID-19remote monitoringsensorssmart bedsheet

Identifiers

PMID36913205
PMCPMC9983696
OpenAlexW4292264516

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.