Using AI to predict Energy Expenditure in Lower Limb Prosthesis Users

Authors

• Nelly Diaz, St. Mary's University
• Siem Hadish, St. Mary's University

Files

Contributor

Ramirez, Ricardo (Faculty Mentor)

Digital Publisher

Digital Commons at St. Mary's University

Publication Date

Spring 2026

Keywords

Artificial Intelligence, Energy expenditure, Computer vision, Biomechanics, Human motion

Description

• Computer vision has evolved from simple image classification and object detection to analyzing human motion and biomechanics (1). • CNN’s are usually focused on image classification, but, in this case, we are not asking the model if a person is walking. • Many real-world problems require regression: Predicting a continuous number like energy expenditure of walking is a complex task. • It is essential for Prosthetists to understand energy expenditure of their prosthetic patients (2). • An amputee may use 20-30% more energy to walk. • In this project, we developed an AI model to analyze human motion and predict energy expenditure to improve prosthetic design.

Format

PDF

Size

1 poster

City

San Antonio, Texas

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.