Development of an Automated Motor-Based Biomarker for Preclinical Alzheimer’s Disease

Biomedical Engineering

Jake McColm

Abstract

This project presents a low-cost system designed to measure task time and motor behavior using an interactive, sensor-based task. The system captures precise timing data during user interactions to assess motor–cognitive performance in a controlled yet accessible format.

While not diagnostic, it demonstrates the potential for scalable behavioral tools to contribute to early screening of conditions such as Alzheimer’s disease.

Video

Research poster

Faculty mentor

Portrait of Sydney Schaefer

Sydney Schaefer

Associate Professor

School of Biological and Health Systems Engineering

[email protected]