Footstep Induced Floor Vibration
Raphael Voda
School of Engineering
Faculty Supervisor: Zhaoshuo Jiang
This project investigates a non-invasive, privacy-preserving approach to monitoring human gait using floor-based vibration sensors. As the elderly population grows, there is an increasing need for reliable systems that can detect mobility changes and potential fall risks without relying on wearable devices or camera systems. The study explores whether vibration signals generated by footsteps can be used to accurately estimate gait parameters such as walking speed, step frequency, and stride patterns.
A sensor network consisting of floor-mounted accelerometers is used to capture vibration data, which is then analyzed using signal processing techniques, including Fast Fourier Transform (FFT) and phase delay analysis. Phase-based localization is emphasized due to its higher spatial resolution compared to traditional time-of-flight methods. Video labeling is initially used to establish ground truth data for validation.
The results demonstrate that vibration-based monitoring can provide accurate gait insights while maintaining user privacy. This approach shows strong potential for applications in healthcare monitoring, smart buildings, and assisted living environments.