Evidence map›Paper›PMID 38809596›Full record

ArticleJMIR formative research2024

Highlighting Unseen Activity Through 48-Hour Continuous Measurement in Subacute Stroke Rehabilitation: Preliminary Cohort Study.

Emi Mizuno, Takayuki Ogasawara, Masahiko Mukaino, Masumi Yamaguchi, Shingo Tsukada, Shigeru Sonoda, Yohei Otaka

Abstract read
In one paragraph

Article in JMIR formative research, 2024. 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. Review
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

7 authors.

Emi MizunoDepartment of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Japan.ORCID https://orcid.org/0009-0000-6806-8456
Takayuki OgasawaraNTT Basic Research Laboratories and Bio-medical Informatics Research Center, NTT Corporation, Atsugi, Japan.ORCID https://orcid.org/0000-0002-1657-6907
Masahiko MukainoDepartment of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Japan.ORCID https://orcid.org/0000-0003-4348-8715
Masumi YamaguchiNTT Basic Research Laboratories and Bio-medical Informatics Research Center, NTT Corporation, Atsugi, Japan.ORCID https://orcid.org/0000-0001-8315-0140
Shingo TsukadaNTT Basic Research Laboratories and Bio-medical Informatics Research Center, NTT Corporation, Atsugi, Japan.ORCID https://orcid.org/0009-0003-6660-3744
Shigeru SonodaDepartment of Rehabilitation Medicine II, School of Medicine, Fujita Health University, Toyoake, Japan.ORCID https://orcid.org/0000-0001-7491-5308
Yohei OtakaDepartment of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Japan.ORCID https://orcid.org/0000-0002-6797-2782

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMotor impairments not only lead to a significant reduction in patient activity levels but also trigger a further deterioration in motor function due to deconditioning, which is an issue that is particularly pronounced during hospitalization. This deconditioning can be countered by sustaining appropriate activity levels. Activities that occur outside of scheduled programs, often overlooked, are critical in this context. Wearable technology, such as smart clothing, provides a means to monitor these activities.

objectiveThis study aimed to observe activity levels in patients who had strokes during the subacute phase, focusing on both scheduled training sessions and other nontraining times in an inpatient rehabilitation environment. A smart clothing system is used to simultaneously measure heart rate and acceleration, offering insights into both the amount and intensity of the physical activity.

methodsIn this preliminary cohort study, 11 individuals undergoing subacute stroke rehabilitation were enrolled. The 48-hour continuous measurement system, deployed at admission and reassessed 4 weeks later, monitored accelerometry data for physical activity (quantified with a moving SD of acceleration [MSDA]) and heart rate for intensity (quantified with percent heart rate reserve). The measurements were performed using a wearable activity monitoring system, the hitoe (NTT Corporation and Toray Industries, Inc) system comprising a measuring garment (wear or strap) with integrated electrodes, a data transmitter, and a smartphone. The Functional Independence Measure was used to assess the patients' daily activity levels. This study explored factors such as differences in activity during training and nontraining periods, correlations with activities of daily living (ADLs) and age, and changes observed after 4 weeks.

resultsA significant increase was found in the daily total MSDA after the 4-week program, with the average percent heart rate reserve remaining consistent. Physical activity during training positively correlated with ADL levels both at admission (ρ=0.86, P<.001) and 4 weeks post admission (ρ=0.96, P<.001), whereas the correlation between age and MSDA was not significant during training periods at admission (ρ=-0.41, P=.21) or 4 weeks post admission (ρ=-0.25, P=.45). Conversely, nontraining activity showed a negative correlation with age, with significant negative correlations with age at admission (ρ=-0.82, P=.002) and 4 weeks post admission (ρ=-0.73, P=.01).

conclusionsInpatient rehabilitation activity levels were positively correlated with ADL levels. Further analysis revealed a strong positive correlation between scheduled training activities and ADL levels, whereas nontraining activities showed no such correlation. Instead, a negative correlation between nontraining activities and age was observed. These observations suggest the importance of providing activity opportunities for older patients, while it may also suggest the need for adjusting the activity amount to accommodate the potentially limited fitness levels of this demographic. Future studies with larger patient groups are warranted to validate and further elucidate these findings.

Indexed as

activities of daily livingactivity levelactivity monitoringADLdeconditioningheart ratemobile phonemonitoringmuscle wastingolder peoplephysical conditionphysical therapyrecoveryrehabilitationsmart clothing systemstroketrainingunseenwearablewearable technology

Identifiers

PMID38809596
PMCPMC11170042

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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.