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Record W4409687883 · doi:10.2196/60607

Usability Evaluation of an Electrically Powered Orthopedic Exerciser: Focus Group Interview and Satisfaction Survey Study

2025· article· en· W4409687883 on OpenAlexvenueno aff
Seojin Hong, Hyun Choi, Hyosun Kweon

Bibliographic record

VenueJMIR Human Factors · 2025
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintUsabilityFocus groupPsychologyEngineeringComputer scienceHuman–computer interactionBusinessWorld Wide WebMarketing

Abstract

fetched live from OpenAlex

Background: Musculoskeletal disorders significantly impair physical function and quality of life, necessitating systematic rehabilitation. Electrically powered orthopedic exercisers, such as continuous passive motion devices, are widely used to enhance joint mobility and muscle recovery. However, existing devices often lack advanced functionalities and user-specific adaptability, limiting their effectiveness. To address these shortcomings, the Rebless Pro was developed as a novel device supporting active and passive exercises with personalized treatment programs. Objective: This study aimed to conduct a formative usability evaluation of the Rebless Pro prototype using focus group interviews (FGIs) and satisfaction surveys with health care professionals specializing in rehabilitation medicine. The goal was to identify areas for improvement to enhance the safety, usability, and information clarity of the device. Unlabelled: Usability evaluation was performed at the National Rehabilitation Center with 10 participants (5 physiatrists and 5 physical therapists) who had prior experience using similar devices. FGIs were conducted to collect qualitative insights into user experiences, while satisfaction surveys provided quantitative data on ease of use of the user interface and identifiability and understanding of information. Data collection focused on identifying risk factors and usability challenges. Results: Three key areas for improvement were identified: (1) product upgrades to ensure patient safety, including adjustments to exercise speed and resistance; (2) hardware and software improvements to improve usability, including adjustments to the location of the emergency button and improvements to the graphical user interface elements; and (3) improvements to the user manual, including detailed contraindications, patient criteria, and clearer operating instructions. Although the mean score of physiatrists (mean 4.463, SD 0.298) was higher than that of physical therapists (mean 4.114, SD 0.829) in terms of the ease of use of the user interface, the difference was not statistically significant (P=.69). Similarly, in the category of identifiability and understanding of information, higher scores were again reported by physiatrists (mean score 4.467, SD 0.506) than by physical therapists (mean 3.733, SD 0.894), but this difference was also not statistically significant (P=.22). Conclusions: Usability evaluation provided actionable insights into improving the Rebless Pro's safety, usability, and information clarity. To further refine the device, iterative usability evaluations involving both health care professionals and patients are recommended. These efforts are expected to contribute to the development of a safe, effective, and user-friendly electrically powered orthopedic exerciser suitable for commercialization.

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)0.025
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.027
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.319
Teacher spread0.279 · 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 designQualitative
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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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