Evidence map›Paper›PMID 39127667›Full record

ArticleJournal of neuroengineering and rehabilitation2024

Effectiveness of mixed reality-based rehabilitation on hands and fingers by individual finger-movement tracking in patients with stroke.

Yeajin Ham, Dong-Seok Yang, Younggeun Choi, Joon-Ho Shin

Abstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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.

Yeajin HamDepartment of Rehabilitation Medicine, National Rehabilitation Center, Ministry of Health and Welfare, 58, Samgaksan-ro, Gangbuk-gu, Seoul, 01022, Republic of Korea.
Dong-Seok YangBusiness Growth Support Center, Seongnam, 13449, Korea.
Younggeun ChoiDepartment of Computer Engineering, Dankook University, Yongin-si, 16890, Gyeonggi-do, Korea.
Joon-Ho ShinDepartment of Rehabilitation Medicine, National Rehabilitation Center, Ministry of Health and Welfare, 58, Samgaksan-ro, Gangbuk-gu, Seoul, 01022, Republic of Korea. asfreelyas@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMixed reality (MR) is helpful in hand training for patients with stroke, allowing them to fully submerge in a virtual space while interacting with real objects. The recognition of individual finger movements is required for MR rehabilitation. This study aimed to assess the effectiveness of updated MR-board 2, adding finger training for patients with stroke.

methodsTwenty-one participants with hemiplegic stroke (10 with left hemiplegia and 11 with right hemiplegia; nine female patients; 56.7 ± 14.2 years of age; and onset of stroke 32.7 ± 34.8 months) participated in this study. MR-board 2 comprised a board plate, a depth camera, plastic-shaped objects, a monitor, a palm-worn camera, and seven gamified training programs. All participants performed 20 self-training sessions involving 30-min training using MR-board 2. The outcome measurements for upper extremity function were the Fugl-Meyer assessment (FMA) upper extremity score, repeated number of finger flexion and extension (Repeat-FE), the thumb opposition test (TOT), Box and Block Test score (BBT), Wolf Motor Function Test score (WMFT), and Stroke Impact Scale (SIS). One-way repeated measures analysis of variance and the post hoc test were applied for the measurements. MR-board 2 recorded the fingers' active range of motion (AROM) and Dunnett's test was used for pairwise comparisons.

resultsExcept for the FMA-proximal score (p = 0.617) and TOT (p = 0.005), other FMA scores, BBT score, Repeat-FE, WMFT score, and SIS stroke recovery improved significantly (p < 0.001) during MR-board 2 training and were maintained until follow-up. All AROM values of the finger joints changed significantly during training (p < 0.001).

conclusionsMR-board 2 self-training, which includes natural interactions between humans and computers using a tangible user interface and real-time tracking of the fingers, improved upper limb function across impairment, activity, and participation. MR-board 2 could be used as a self-training tool for patients with stroke, improving their quality of life. TRIAL REGISTRATION NUMBER: This study was registered with the Clinical Research Information Service (CRIS: KCT0004167).

Indexed as

FingersHandStroke RehabilitationAdultAgedFemaleHemiplegiaHumansMaleMiddle AgedMovementRecovery of FunctionStrokeTreatment OutcomeEquipment and suppliesFingersMixed realityRange of motionStroke rehabilitationWearable device

Identifiers

PMID39127667
PMCPMC11316335

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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.