MétaCan
Menu
Back to cohort
Record W2763731607 · doi:10.2196/games.7969

Usability Test of Exercise Games Designed for Rehabilitation of Elderly Patients After Hip Replacement Surgery: Pilot Study

2017· article· en· W2763731607 on OpenAlexvenueno aff
Yun Ling, Louis P Ter Meer, Zerrin Yumak, Remco C. Veltkamp

Bibliographic record

VenueJMIR Serious Games · 2017
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationPhysical therapyMuscle strengthMedicineTest (biology)Hip replacementHip surgeryPhysical medicine and rehabilitationUsabilityTotal hip replacementSurgeryArthroplastyComputer scienceHuman–computer interaction

Abstract

fetched live from OpenAlex

BACKGROUND: Patients who receive rehabilitation after hip replacement surgery are shown to have increased muscle strength and better functional performance. However, traditional physiotherapy is often tedious and leads to poor adherence. Exercise games, provide ways for increasing the engagement of elderly patients and increase the uptake of rehabilitation exercises. OBJECTIVE: The objective of this study was to evaluate Fietsgame (Dutch for cycling game), which translates existing rehabilitation exercises into fun exercise games. The system connects exercise games with a patient's personal record and a therapist interface by an Internet of Things server. Thus, both the patient and physiotherapist can monitor the patient's medical status. METHODS: This paper describes a pilot study that evaluates the usability of the Fietsgame. The study was conducted in a rehabilitation center with 9 participants, including 2 physiotherapists and 7 patients. The patients were asked to play 6 exercise games, each lasting about 5 min, under the guidance of a physiotherapist. The mean age of the patients was 74.57 years (standard deviation [SD] 8.28); all the patients were in the recovery process after hip surgery. Surveys were developed to quantitatively measure the usability factors, including presence, enjoyment, pain, exertion, and technology acceptance. Comments on advantages and suggested improvements of our game system provided by the physiotherapists and patients were summarized and their implications were discussed. RESULTS: The results showed that after successfully playing the games, 75% to 100% of the patients experienced high levels of enjoyment in all the games except the squats game. Patients reported the highest level of exertion in squats when compared with other exercise games. Lunges resulted in the highest dropout rate (43%) due to interference with the Kinect v2 from support chairs. All the patients (100%) found the game system useful and easy to use, felt that it would be a useful tool in their further rehabilitation, and expressed that they would like to use the game in the future. The therapists indicated that the exercise games highly meet the criteria of motor rehabilitation, and they intend to continue using the game as part of their rehabilitation treatment of patients. Comments from the patients and physiotherapists suggest that real-time corrective feedback when patients perform the exercises wrongly and a more personalized user interface with options for increasing or decreasing cognitive load are needed. CONCLUSIONS: The results suggest that Fietsgame can be used as an alternative tool to traditional motor rehabilitation for patients with hip surgery. Lunges and squats are found to be more beneficial for patients who have relatively better balance skills. A follow-up randomized controlled study will be conducted to test the effectiveness of the Fietsgame to investigate how motivating it is over a longer period of time.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.298
Teacher spread0.277 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations46
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Serious GamesSame topicTotal Knee Arthroplasty OutcomesFrench-language works237,207