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Record W4416916732 · doi:10.1080/10400435.2025.2586605

Improvement on task performance and satisfaction with the use of dynamic arm support MOMO series on five users with upper limb dysfunction: A case series

2025· article· en· W4416916732 on OpenAlexaboutno aff
Yuichi Yokoyama, Koshi Matsuoka, Shintaro SHIMADA, Kaoru Inoue

Bibliographic record

VenueAssistive Technology · 2025
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsTask (project management)UsabilitySeries (stratigraphy)Psychological interventionQuality of life (healthcare)Activities of daily livingOccupational therapy

Abstract

fetched live from OpenAlex

The dynamic arm support MOMO series by Reharo Corporation, Japan, is an upper limb orthosis that primarily supports the daily lives of people with impaired upper limb function. The MOMO series comprises two types: MOMO and MOMO Prime, which support horizontal movement and antigravity control of the upper limb, respectively. This case series describes occupational therapy interventions using the MOMO series and assistive devices tailored to the individual needs of five participants. Outcomes were assessed using the Canadian Occupational Performance Measure (COPM) and the System Usability Scale (SUS). In all cases, COPM performance and satisfaction scores improved, indicating enhanced ability to engage in meaningful activities such as eating, smartphone use, and leisure. On the SUS score, higher satisfaction was observed when participants could apply the device independently and achieve tasks immediately after introduction. In several cases, the use of the MOMO series contributed to functional recovery, allowing tasks to be continued without the device. These findings suggest that the MOMO series can enhance independence, satisfaction, and quality of life when introduced with appropriate occupational therapy support.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.232
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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