Evidence map›Paper›PMID 42147756›Full record

ArticleFrontiers in electronics2025

Quantitative musculoskeletal monitoring and analysis in aquatic rehabilitation.

Abu Bony Amin, Ebenezer Asabre, Sina Razaghi, Yeonsik Noh

Abstract read
In one paragraph

Article in Frontiers in electronics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

4 authors.

Abu Bony AminDepartment of Electrical and Computer Engineering, University of Massachusetts Amherst, Amherst, MA, United States.
Ebenezer AsabreDepartment of Electrical and Computer Engineering, University of Massachusetts Amherst, Amherst, MA, United States.
Sina RazaghiDepartment of Electrical and Computer Engineering, University of Massachusetts Amherst, Amherst, MA, United States.
Yeonsik NohDepartment of Electrical and Computer Engineering, University of Massachusetts Amherst, Amherst, MA, United States.

Funding

Technology Development ComponentP2CHD101899 · NICHD · REHABILITATION INSTITUTE OF CHICAGO D/B/A SHIRLEY RYAN ABILITYLAB · PI DEWALD, JULIUS P · 2020 to 2024
$5.6M
NICHD NIH HHS P2C HD101899
6 · The paper itself

Abstract

The benefits of aquatic rehabilitation have been demonstrated to promote wellbeing and facilitate motor recovery in middle-aged adults and geriatrics. Individualized patient-centered treatment is essential to accelerate and improve the rehabilitation process of neurological and orthopedic patients. Although aquatic therapy and rehabilitation are well known to be beneficial to these populations, it can be challenging for therapists to visualize and monitor patient progress and provide individualized feedback to ensure correct movement as planned. To establish the suitability of the developed wearable device in an aquatic environment, this study compared the extracted features of the sEMG and IMU data in on-land and aquatic environments for the bicep curls (BC) and tricep kickback (TK) protocols. We conducted a systematic analysis of the reproducibility and precision of the sEMG-IMU characteristics to assess the feasibility of the device for practical applications. While time and frequency domain features of sEMG were higher in aquatic environments compared to on-land, the Intraclass Correlation Coefficient (ICC) for these features ranged from 0.81 to 0.98, and the Coefficient of Variation (

Indexed as

aquatic rehabilitationbicep curlsmusculoskeletal monitoringquantitative analysistricep kickbackswaterproof wearable device

Identifiers

PMID42147756
PMCPMC13175757

What OpenQuestion holds

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LicenceCC BY
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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.