Evidence map›Paper›PMID 36550999›Full record

ArticleBioengineering (Basel, Switzerland)2022

A Novel Smart Belt for Anxiety Detection, Classification, and Reduction Using IIoMT on Students' Cardiac Signal and MSY.

Rishi Pal, Deepak Adhikari, Md Belal Bin Heyat, Bishal Guragai, Vivian Lipari, Julien Brito Ballester, Isabel De la Torre Díez, Zia Abbas, Dakun Lai

Open access · goldAbstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
4.3field-weighted citation impact, top 4% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

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  8. Efficacy and classification ofFrontiers in chemistry · 2024
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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

9 authors at 5 institutions in 3 countries.

Rishi PalSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China.
Deepak AdhikariSchool of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610056, China.
Md Belal Bin HeyatIoT Research Center, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China.ORCID 0000-0001-5307-9582
Bishal GuragaiSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610056, China.
Vivian LipariResearch Group on Foods, Nutritional Biochemistry and Health Universidad Europea Del Atlántico, Isabel Torres, 39011 Santander, Spain.
Julien Brito BallesterResearch Group on Foods, Nutritional Biochemistry and Health Universidad Europea Del Atlántico, Isabel Torres, 39011 Santander, Spain.
Isabel De la Torre DíezDepartment of Signal Theory and Communications and Telematic Engineering, University of Valladolid, Paseo de Belén 15, 47011 Valladolid, Spain.ORCID 0000-0003-3134-7720
Zia AbbasCentre for VLSI and Embedded System Technologies, International Institute of Information Technology, Hyderabad 500032, India.ORCID 0000-0002-3747-3640
Dakun LaiSchool of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610056, China.ORCID 0000-0001-9070-1721
University of Electronic Science and Technology of China · CNUniversidad Europea del Atlántico · ESInternational Institute of Information Technology, Hyderabad · INShenzhen University · CNUniversidad de Valladolid · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prevalence of anxiety among university students is increasing, resulting in the negative impact on their academic and social (behavioral and emotional) development. In order for students to have competitive academic performance, the cognitive function should be strengthened by detecting and handling anxiety. Over a period of 6 weeks, this study examined how to detect anxiety and how Mano Shakti Yoga (MSY) helps reduce anxiety. Relying on cardiac signals, this study follows an integrated detection-estimation-reduction framework for anxiety using the Intelligent Internet of Medical Things (IIoMT) and MSY. IIoMT is the integration of Internet of Medical Things (wearable smart belt) and machine learning algorithms (Decision Tree (DT), Random Forest (RF), and AdaBoost (AB)). Sixty-six eligible students were selected as experiencing anxiety detected based on the results of self-rating anxiety scale (SAS) questionnaire and a smart belt. Then, the students were divided randomly into two groups: experimental and control. The experimental group followed an MSY intervention for one hour twice a week, while the control group followed their own daily routine. Machine learning algorithms are used to analyze the data obtained from the smart belt. MSY is an alternative improvement for the immune system that helps reduce anxiety. All the results illustrate that the experimental group reduced anxiety with a significant (p < 0.05) difference in group × time interaction compared to the control group. The intelligent techniques achieved maximum accuracy of 80% on using RF algorithm. Thus, students can practice MSY and concentrate on their objectives by improving their intelligence, attention, and memory.

Indexed as

anxietyartificial intelligencebrainexercisehealthintegrative medicineinternet of medical thingsmachine learningstudenttherapyyoga

Identifiers

PMID36550999
PMCPMC9774730
OpenAlexW4311364157

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.