Evidence map›Paper›PMID 42464320›Full record

Trial reportJournal of neuroengineering and rehabilitation2026

Smartphone-based real-time feedback to suppress trunk compensation for unsupervised upper limb rehabilitation in patients with brain disorders.

Su Hyeon Kim, Doo Na Cho, Won Hyuk Chang, Hyo-Chang Seo

Abstract readRandomized Controlled Trial
In one paragraph

Trial report 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. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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.

Su Hyeon KimDigital Therapeutics Research Center, Smart Healthcare Research Institute, Samsung Medical Center, Seoul, 06351, South Korea.
Doo Na ChoDepartment of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul, 06355, Korea.
Won Hyuk Chang *Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul, 06355, Korea. wh.chang@samsung.com.
Hyo-Chang Seo *Digital Therapeutics Research Center, Smart Healthcare Research Institute, Samsung Medical Center, Seoul, 06351, South Korea. shc0513@gmail.com.ORCID https://orcid.org/0000-0002-8046-6374

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo ensure continuous rehabilitation for patients with hemiparesis due to brain disorders, there is a growing need for simple, accessible systems that enable unsupervised self-training. The occurrence of compensatory trunk movements during the unsupervised exercise may prevent true functional recovery. This study proposes a smartphone-based visual-auditory feedback system designed to detect and suppress compensatory trunk movements in real-time without wearable sensors.

methodsA pilot cohort (n = 16) was first used to calibrate detection thresholds for compensatory trunk movements. Subsequently, a total of 55 hemiparetic patients were enrolled in a randomized controlled trial and allocated to a Feedback (FB) group (n = 27) or a Non-Feedback (NFB) group (n = 28). Participants performed standardised upper limb rehabilitation tasks using the Rapael Smart Board™, a planar upper limb rehabilitation device. The proposed system utilised a smartphone camera with MediaPipe-based pose estimation to track trunk movements and provided real-time traffic-light feedback based on calibrated thresholds. Outcome measures included trunk path length, trunk deviation, task efficiency, and spatial occupancy, which were evaluated using 3D coordinates reconstructed from depth camera data.

resultsThe FB group demonstrated significantly improved postural stability compared to the NFB group, with a 37.9% reduction in trunk path length (p = 0.014) and a 35.3% decrease in spatial occupancy (p = 0.003). Kinematic analysis revealed that the NFB group's shorter hand path lengths were achieved through kinematic redundancy-specifically, the recruitment of trunk degrees of freedom-rather than through selective upper limb motor control. In contrast, the FB group maintained a stable posture near the neutral position, ensuring true upper limb engagement. The usability assessment demonstrated that the system was well received by users and was reliable (Cronbach's α= 0.775).

conclusionThe proposed system, which integrates mobile technology, effectively suppresses compensatory trunk movements and promotes selective motor control, and ensures that rehabilitation outcomes reflect true upper limb joint engagement rather than kinematic redundancy through compensatory trunk recruitment. While certain design considerations remain, particularly related to dynamic recalibration and the use of a fixed auditory feedback window, the system retains strong potential as an automated feedback solution, offering a scalable and accessible pathway for high-quality unsupervised home rehabilitation.

Indexed as

Feedback, SensoryParesisSmartphoneStroke RehabilitationTorsoUpper ExtremityAdultAgedFemaleHumansMaleMiddle AgedPilot ProjectsCompensatory trunk movementReal-time feedbackSmartphone-based systemTrunk controlUnsupervised upper limb rehabilitation

Identifiers

PMID42464320
PMCPMC13682079

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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 OpenQuestion graph.