Evidence map›Paper›PMID 41474152›Full record

ArticleNeurorehabilitation and neural repair2026

Beyond the Wrist: Finger-Worn Accelerometers Enhance Assessment of Post-Stroke Motor Performance.

Yunda Liu, Gloria Vergara-Diaz, Benito Lorenzo Pugliese, Randie Black-Schaffer, Grace Kim, Paolo Bonato, Sunghoon Ivan Lee

Abstract read
In one paragraph

Article in Neurorehabilitation and neural repair, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Yunda LiuManning College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, MA, USA.ORCID 0000-0001-6554-3012
Gloria Vergara-DiazDepartment of Physical Medicine and Rehabilitation, Harvard Medical School at Spaulding Rehabilitation Hospital, Boston, MA, USA.
Benito Lorenzo PuglieseDepartment of Physical Medicine and Rehabilitation, Harvard Medical School at Spaulding Rehabilitation Hospital, Boston, MA, USA.
Randie Black-SchafferDepartment of Physical Medicine and Rehabilitation, Harvard Medical School at Spaulding Rehabilitation Hospital, Boston, MA, USA.
Grace KimDepartment of Occupational Therapy, Steinhardt School of Culture, Education, and Human Development, New York University, New York, NY, USA.
Paolo BonatoDepartment of Physical Medicine and Rehabilitation, Harvard Medical School at Spaulding Rehabilitation Hospital, Boston, MA, USA.
Sunghoon Ivan LeeManning College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, MA, USA.ORCID 0000-0001-5935-125X

Funding

Achieving Optimal Motor Function in Stroke Survivors via a Human-Centered Approach to Design an mHealth PlatformR01EB027777 · NIBIB · UNIVERSITY OF MASSACHUSETTS AMHERST · PI LEE, SUNGHOON · 2020 to 2024
$2.4M
NIBIB NIH HHS R01 EB027777
6 · The paper itself

Abstract

BackgroundAccurate and objective assessment of motor performance is critical for effective stroke rehabilitation. While wrist-worn accelerometers are widely accepted as a valid tool for evaluating upper-limb motor performance, they primarily capture arm and forearm movements, overlooking hand and finger activity. This limitation reduces their ability to detect changes in distal function, hindering the broader integration of wearable-based motor performance metrics into clinical practice.ObjectiveTo determine whether finger-worn accelerometers, which capture both proximal and distal movements of the upper limbs, offer a more comprehensive assessment of motor performance by comparing their convergent validity with that of wrist-worn accelerometers.MethodsBilateral accelerometer data were collected from 24 stroke survivors using finger-worn and wrist-worn devices as they performed unscripted daily activities in a simulated home environment. Motor performance metrics from both sensor locations were analyzed for correlations with the Fugl-Meyer Assessment for Upper Extremity (FMA-UE) and sensitivity to differences in motor performance across impairment levels.ResultsFinger-worn accelerometer metrics showed stronger correlations with FMA-UE scores than those from wrist-worn sensors, largely due to their ability to capture fine hand movements. Additionally, finger-worn sensors demonstrated greater sensitivity in detecting performance differences between mildly and moderately impaired individuals.ConclusionsBy capturing both proximal and distal movements, finger-worn accelerometers demonstrate stronger convergent validity with standardized measures of post-stroke motor impairment compared to wrist-worn accelerometers. These findings highlight their potential for providing a more comprehensive assessment of motor performance in stroke survivors.

Indexed as

AccelerometryFingersMotor ActivityStrokeStroke RehabilitationUpper ExtremityWearable Electronic DevicesAdultAgedFemaleHumansMaleMiddle AgedWristfinger-worn accelerometersmotor performancestrokeupper-limb

Identifiers

PMID41474152
PMCPMC12758624

What Socratic holds

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Registered trials

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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 Socratic graph.