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Related Experiment Video

Updated: Jul 6, 2026

Simultaneous Scalp Electroencephalography EEG, Electromyography EMG, and Whole-body Segmental Inertial Recording for Multi-modal Neural Decoding

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Optimizing the Interaction System for Treadmill Video Games Using a Smartphone's Front Camera.

Micaela Yanet Martin¹, Carlos Marín-Lora², María Beatriz Villar-López¹

¹Institute of New Imaging Technologies, Universitat Jaume I, Av. Vicent Sos Baynat s/n, 12071 Castellón de la Plana, Spain.

Sensors (Basel, Switzerland)

|January 10, 2026

Summary

This summary is machine-generated.

This study presents a smartphone-based system for treadmill video games, using facial tracking for hands-free control and running cadence estimation. The FFT-based method offers accurate, real-time feedback for enhanced exergaming experiences.

Keywords:

active video games face tracking mobile technology treadmill interaction

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Area of Science:

Human-Computer Interaction
Exergaming Technology
Biomedical Signal Processing

Background:

Treadmill-based video games require intuitive control methods.
Existing systems often lack accessibility or require dedicated hardware.
Hands-free interaction enhances immersion and user engagement in exergames.

Purpose of the Study:

To develop a lightweight and accessible interaction system for treadmill video games.
To enable real-time estimation of running cadence and directional control using facial tracking.
To provide an immersive and hands-free gaming experience through smartphone integration.

Main Methods:

Utilized smartphone front camera for facial tracking.
Implemented a Fast Fourier Transform (FFT)-based method for cadence estimation.
Incorporated natural head movements for directional game control.

Main Results:

Achieved cadence estimation accuracy errors below 5% with only 128 frames.
Demonstrated superior accuracy and robustness compared to traditional peak detection methods.
Facilitated real-time feedback for an immersive gaming experience.

Conclusions:

The FFT-based facial tracking system offers a practical, efficient, and scalable solution for fitness-oriented human-computer interaction.
The system has promising implications for digital health and the exergaming industry.
Facial tracking provides a viable hands-free control mechanism for interactive fitness applications.