Evidence map›Paper›PMID 35782178›Full record

ArticleIEEE internet of things journal2021

Emotion-Aware and Intelligent Internet of Medical Things Toward Emotion Recognition During COVID-19 Pandemic.

Tao Zhang, Minjie Liu, Tian Yuan, Najla Al-Nabhan

Open access · bronzeAbstract read
In one paragraph

Article in IEEE internet of things journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.1field-weighted citation impact, top 6% 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

6 citing papers in PubMed, 55 citations in OpenAlex.

  1. Article
  2. Automated Drone-Delivery Solar-Driven Onsite Wastewater Smart Monitoring and Treatment System.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
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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

4 authors at 3 institutions in 2 countries.

Tao ZhangSchool of artificial intelligence and computer scienceJiangnan University Wuxi 214122 China.ORCID https://orcid.org/0000-0003-3966-4691
Minjie LiuSchool of NursingTaihu University of Wuxi Wuxi 214064 China.ORCID https://orcid.org/0000-0002-8354-2416
Tian YuanSchool of Computer EngineeringNanjing Institute of Technology Nanjing 210000 China.ORCID https://orcid.org/0000-0002-2307-8201
Najla Al-NabhanDepartment of Computer ScienceKing Saud University Riyadh 11682 Saudi Arabia.ORCID https://orcid.org/0000-0002-0805-1721
Jiangnan University · CNKing Saud University · SANanjing Institute of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Internet of Medical Things (IoMT) is a brand new technology of combining medical devices and other wireless devices to access to the healthcare management systems. This article has sought the possibilities of aiding the current Corona Virus Disease 2019 (COVID-19) pandemic by implementing machine learning algorithms while offering emotional treatment suggestion to the doctors and patients. The cognitive model with respect to IoMT is best suited to this pandemic as every person is to be connected and monitored through a cognitive network. However, this COVID-19 pandemic still remain some challenges about emotional solicitude for infants and young children, elderly, and mentally ill persons during pandemic. Confronting these challenges, this article proposes an emotion-aware and intelligent IoMT system, which contains information sharing, information supervision, patients tracking, data gathering and analysis, healthcare, etc. Intelligent IoMT devices are connected to collect multimodal data of patients in a surveillance environments. The latest data and inputs from official websites and reports are tested for further investigation and analysis of the emotion analysis. The proposed novel IoMT platform enables remote health monitoring and decision-making about the emotion, therefore greatly contribute convenient and continuous emotion-aware healthcare services during COVID-19 pandemic. Experimental results on some emotion data indicate that the proposed framework achieves significant advantage when compared with the some mainstream models. The proposed cognition-based dynamic technology is an effective solution way for accommodating a big number of devices and this COVID-19 pandemic application. The controversy and future development trend are also discussed.

Indexed as

Cognitive modelCorona Virus Disease 2019 (COVID-19)emotion-awarehealthcare management systemsinternet of medical things (IoMT)

Identifiers

PMID35782178
PMCPMC8768974
OpenAlexW3102266808

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.