Deep Learning Based Estimation of Ground Reaction Forces Using Wearable Smart Insoles

Biomedical Engineering

Noah Kettner

Abstract

This project develops a smart insole system that uses an array of pressure sensors to capture plantar pressure during walking. A machine learning model is trained to estimate ground reaction forces and center of pressure from this wearable data, reducing the need for traditional lab-based equipment.

The system aims to enable portable, real-world biomechanical analysis for applications in sports performance and rehabilitation.

Video

Research poster

Faculty mentor

Portrait of Hyunglae Lee

Hyunglae Lee

Associate Professor

School for Engineering of Matter, Transport and Energy

[email protected]