Evidence map›Paper›PMID 35062585›Full record

ArticleSensors (Basel, Switzerland)2022

New Internet of Medical Things for Home-Based Treatment of Anorectal Disorders.

Jerry Zhou, Vincent Ho, Bahman Javadi

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. 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 2 institutions in 1 country.

Jerry ZhouTranslational Gastroenterology Laboratory, School of Medicine, Western Sydney University, Campbelltown, NSW 2560, Australia.ORCID 0000-0002-9741-0318
Vincent HoTranslational Gastroenterology Laboratory, School of Medicine, Western Sydney University, Campbelltown, NSW 2560, Australia.ORCID 0000-0003-3127-2933
Bahman JavadiSchool of Computer, Data and Mathematical Sciences, Western Sydney University, Penrith, NSW 2751, Australia.ORCID 0000-0003-2351-9801
Camden and Campbelltown Hospitals · AUWestern Sydney University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Home-based healthcare provides a viable and cost-effective method of delivery for resource- and labour-intensive therapies, such as rehabilitation therapies, including anorectal biofeedback. However, existing systems for home anorectal biofeedback are not able to monitor patient compliance or assess the quality of exercises performed, and as a result have yet to see wide spread clinical adoption. In this paper, we propose a new Internet of Medical Things (IoMT) system to provide home-based biofeedback therapy, facilitating remote monitoring by the physician. We discuss our user-centric design process and the proposed architecture, including a new sensing probe, mobile app, and cloud-based web application. A case study involving biofeedback training exercises was performed. Data from the IoMT was compared against the clinical standard, high-definition anorectal manometry. We demonstrated the feasibility of our proposed IoMT in providing anorectal pressure profiles equivalent to clinical manometry and its application for home-based anorectal biofeedback therapy.

Indexed as

Internet of ThingsRectal DiseasesBiofeedback, PsychologyHumansInternetManometryMonitoring, Physiologicbiofeedback therapyhome healthcareInternet of Medical Things (IoMT)medical sensorsrehabilitation

Identifiers

PMID35062585
PMCPMC8780207
OpenAlexW4206361608

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.