Development of a Novel Home-Based Exergame With On-Body Feedback: Usability Study
Notice bibliographique
Résumé
BACKGROUND: With more than 1.4 billion adults worldwide classified as physically inactive, physical inactivity is a public health crisis leading to an increased risk of cardiometabolic diseases. Motivating and engaging training strategies are needed to tackle this public health crisis. Studies have shown that exergames, games controlled by active body movements, are potentially usable, attractive, and effective tools for home-based training. The ExerCube (by Sphery Ltd) has been developed as a physically immersive and adaptive functional fitness game. The development of a home-based version of the ExerCube could increase accessibility, reduce barriers to exercise, and provide an attractive solution to improve physical and cognitive health. OBJECTIVE: The aim was threefold: (1) to develop a usable home-based exergame system, (2) to evaluate the usability and training experience of the home-based exergame and its early-stage on-body feedback system, and (3) to identify avenues for further user-centered design iterations of the system. METHODS: A total of 15 healthy participants (mean age 25, SD 3 years) completed 2 laboratory visits consisting of four 5-minute exergame sessions. In each session, the on-body feedback system provided a different feedback modality (auditory, haptic, and visual feedback) to the participant. Following the second visit, participants completed a range of assessments, including the System Usability Scale (SUS), the Physical Activity Enjoyment Scale (PACES), the Flow Short Scale (FSS), the Immersive Experience Questionnaire (IEQ), and a rating of perceived exertions (RPEs) both physically and cognitively. Participants answered questions regarding the on-body feedback system and completed a semistructured interview. RESULTS: Usability was rated as acceptable, with a SUS score of 70.5 (SD 12). The questionnaires revealed medium-to-high values for the training experience (FSS: 5.3, SD 1; PACES: 5.3, SD 1.1; IEQ: 4.7, SD 0.9. Physical (mean 4.8, SD 1.6) and cognitive (mean 3.9, SD 1.4) RPEs were moderate. Interviews about the on-body feedback system revealed that the majority of participants liked the haptic feedback and the combination of haptic and auditory feedback the best. Participants enjoyed the distinct perceptibility, processing, and integration of the exergame and its supportive and motivating effect. The visual feedback was perceived less positively by participants but was still classified as "potentially" helpful. The auditory feedback was rated well but highlighted an area for further improvement. Participants enjoyed the training experience and described it as motivating, interactive, immersive, something new, interesting, self-explanatory, as well as physically and cognitively challenging. Moreover, 67% (n=10) of the participants could imagine exercising at home and continuing to play the exergame in the future. CONCLUSIONS: The home-based exergame and its early-stage on-body feedback system were rated as usable and an enjoyable training experience by a young healthy population. Promising avenues emerged for future design iterations.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».