Evidence map›Paper›PMID 41572285›Full record

ArticleJournal of neuroengineering and rehabilitation2026

Short prescribed exercises can quantify upper limb functioning in neurodegenerative disease.

Marcin Straczkiewicz, Katherine M Burke, Narghes Calcagno, Alan Premasiri, Kendall T Carney, Fernando G Vieira, Jukka-Pekka Onnela, James D Berry

Abstract read
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In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2026. 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. Observational
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

8 authors.

Marcin StraczkiewiczDepartment of Measurement and Electronics, AGH University of Krakow, Krakow, Poland. mstr@agh.edu.pl.
Katherine M BurkeNeurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, MA, USA.
Narghes CalcagnoDepartment of Neurology and Laboratory of Neuroscience, IRCCS Istituto Auxologico Italiano, Milan, Italy.
Alan PremasiriALS Therapy Development Institute, Watertown, MA, USA.
Kendall T CarneyNeurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, MA, USA.
Fernando G VieiraALS Therapy Development Institute, Watertown, MA, USA.
Jukka-Pekka OnnelaDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
James D BerryNeurological Clinical Research Institute and Sean M. Healey & AMG Center for ALS, Massachusetts General Hospital, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital health technologies (DHTs) can quantify movements in daily routines but rely heavily on participant adherence over prolonged wear times.

methodsWe analyzed accelerometry data from wrist-worn devices during short at-home episodes of prescribed exercises performed by 329 individuals living with amyotrophic lateral sclerosis (ALS) in a longitudinal study. We developed an automated and interpretable signal processing method to estimate four metrics describing exercise repetitions, i.e., their count, duration, intensity, and similarity. We examined their associations with time elapsed from enrollment and ALS Functional Rating Scale-Revised (ALSFRS-R) using linear mixed effect models. We also compared them with previously validated free-living metrics that require substantial sensor wear-time. Finally, we studied how many repetitions are sufficient to determine participants' upper limb functioning.

resultsThree out of four exercise metrics (all but count) demonstrated significant association with ALSFRS-R outcomes. The duration of exercise repetitions increased, while intensity and similarity of movement decreased over time (all p-value < 0.001), indicating longer but less vigorous and less consistent upper limb movements over time. Exercise intensity was determined as the most robust exercise-based predictor of changes in upper limb function, and it was comparable to free-living metrics, which required at 21 h of sensor wear time (R-squared 0.899 vs. 0.860, respectively). Sensitivity analysis indicated that as few as five exercise repetitions were sufficient to yield statistically significant associations with ALSFRS-R.

conclusionsThese results suggest that prescribed exercise can effectively quantify upper limb function and track longitudinal decline comparably to free-living observation. The proposed method may serve as an alternative that decreases participation burden, increases study adherence, and extends diagnostic accessibility.

Indexed as

Amyotrophic Lateral SclerosisExercise TherapyUpper ExtremityAccelerometryAgedDigital HealthFemaleHumansLongitudinal StudiesMaleMiddle AgedWearable Electronic DevicesAlgorithmAmyotrophic lateral sclerosisDigital healthMotor functionUpper extremityWearable accelerometerWrist-worn

Identifiers

PMID41572285
PMCPMC12825179

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.