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Record W4400856790 · doi:10.2196/58411

Effect of Elastic Resistance on Exercise Intensity and User Satisfaction While Playing the Active Video Game BoxVR in Immersive Virtual Reality: Empirical Study

2024· article· en· W4400856790 on OpenAlexvenueno aff
Jacek Polechoński, Alan Przepiórzyński, Piotr Polechoński, Rajmund Tomik

Bibliographic record

VenueJMIR Serious Games · 2024
Typearticle
Languageen
FieldComputer Science
TopicVirtual Reality Applications and Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsImmersion (mathematics)Virtual realityIntensity (physics)Exercise intensityRepeated measures designVideo gamePhysical therapyPsychologySimulationComputer scienceMultimediaHuman–computer interactionMedicineHeart rateMathematicsStatistics

Abstract

fetched live from OpenAlex

Background: One of the main contemporary forms of physical activity (PA) involves exercises and games in an immersive virtual reality (VR) environment, which allows the user to practice various forms of PA in a small space. Unfortunately, most of the currently available VR games and workout applications are mostly based on upper body movements, especially the arms, which do not guarantee sufficiently high exercise intensity and health benefits. Therefore, it is worth seeking solutions to help increase the exercise load during PA in VR. Objective: The main aim of this study was to evaluate the effect of elastic arm resistance in the form of latex resistance bands of different elasticity levels on the intensity of students' PA while playing the BoxVR game. We further assessed the satisfaction of this form of exercise and its associations with PA intensity. Methods: A total of 21 healthy and physically fit men (mean age 22.5, SD 2.0 years) were included in the study. The tests consisted of 3 10-minute games. One game was run with no load and the other two were run with 1.5-meter latex resistance bands (low and high resistance). The order of the tests was randomized and the participants rested for 20 minutes after each exercise. Exercise intensity was estimated using objective (heart rate monitoring) and subjective (Borg scale) methods. The Physical Activity Enjoyment Scale was used to assess satisfaction with the PA. The effect of elastic resistance on exercise intensity and user enjoyment was estimated using ANOVA for repeated measures. Results: The ANOVA results indicated that incorporation of elastic resistance caused a significant change (F2,40=20.235, P<.001; η²p=0.503) in the intensity of PA in VR, which was low while playing without resistance and then increased to a moderate level with additional resistance. The use of elastic bands also changed participants' perceptions of the enjoyment of exercise in VR (F2,40=9.259, P<.001; η²p=0.316). The students rated their satisfaction with PA in VR on a 7-point scale highly and similarly when exercising without an upper limb load (mean 6.19, SD 0.61) and with slight elastic resistance (mean 6.17, SD 0.66), whereas their satisfaction declined significantly (mean 5.66, SD 0.94) when incorporating a higher load. Conclusions: The intensity of PA among students playing the BoxVR game is at a relatively low level. With the added resistance of elastic bands attached to the upper limbs, the intensity of the exercise increased to a moderate level, as recommended for obtaining health benefits. Participants rated the enjoyment of PA in VR highly. The use of slight elastic resistance did not negatively affect satisfaction with the BoxVR game, although user satisfaction declined with a higher load. Further research should be undertaken to increase the effectiveness of exercise in VR so that regular users can enjoy the health benefits.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.957
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.018
GPT teacher head0.318
Teacher spread0.301 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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