ArticleSensors (Basel, Switzerland)2025
Optimizing the Interaction System for Treadmill Video Games Using a Smartphone's Front Camera.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
4 authors.
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Abstract
This paper introduces a lightweight and accessible interaction system for treadmill-based video games, relying solely on facial tracking via a smartphone's front camera. The system enables real-time estimation of running cadence and directional control through natural head movements, providing an immersive and hands-free gaming experience. A key contribution is the implementation of a FFT-based cadence estimation method that achieves accuracy errors below 5% using only 128 frames, enabling real-time feedback. Preliminary evaluations with 11 participants demonstrate that the FFT-based approach outperforms traditional peak detection in both accuracy and robustness across multiple running speeds. These results position the system as a practical, efficient, and scalable solution for fitness-oriented human-computer interaction, with promising implications for digital health and exergaming.
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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.