ArticleSensors (Basel, Switzerland)2025
Gamifying Resistance Training with Wearable Sensors.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Machine Learning in Adapted Physical Activity: Clinical Applications, Monitoring, and Implementation Pathways for Personalized Exercise in Chronic Conditions: A Narrative Review.Journal of functional morphology and kinesiology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Gamification has been extensively applied to aerobic and cardiovascular training, but its adoption in resistance training remains limited. Unlike traditional strength training, which often relies on intrinsic motivation and discipline, gamification introduces extrinsic incentives and real-time feedback that improves engagement and adherence, affecting overall training outcomes. In this work, we develop a gamified resistance training program using wearable sensors to explore the potential benefits of interactive and data-driven exercise experiences. By leveraging real-time feedback and performance tracking, our system provides participants feedback to properly control key training variables such as form and tempo, essential factors for muscle hypertrophy and strength development. To evaluate the effectiveness of our approach, we conducted a short-term comparative study in which participants were assigned to either a gamified training group or a conventional resistance training control group. Over a four-week period, we assessed volitional adherence to prescribed tempo and repetition schemes, along with strength adaptations in the biceps and triceps. Our findings indicate that gamified resistance training significantly enhances adherence to tempo and repetition targets while fostering better adaptation to the workout regime. Participants in the gamified group exhibited measurable improvements in upper body strength compared to the control group. These results suggest that gamification when integrated with wearable sensor technology, can be a powerful tool for optimising resistance training effectiveness and motivation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.