GaitKeep - Biomedical Engineering Competition - 3rd Place

This project focused on decreasing gait variability in Parkinson’s dementia patients through Rhythmic Auditory Simulation (RAS), a method shown to improve cadence in medical research.

Prototype Design

• GaitKeep is a wearable necklace with a built-in speaker that plays calibrated rhythmic audio based on the user’s walking cadence.
• A mobile app was developed to calibrate the necklace by identifying the user’s natural walking cadence through a short 100-step walking test.

Data Collection & Algorithm

• MATLAB was used to collect accelerometer data from the user’s phone to determine their optimal walking cadence.
• A Python BPM algorithm and discrete wavelength transform were applied to match music with the user’s walking cadence, delivering the auditory stimulus needed to stabilize gait.

  Competition Results

• The project was well-received at the University of Toronto CUBE Biomedical Engineering Competition, where it earned 3rd place.

Key Features

• Integration of wearable technology with real-time feedback.
• Use of MATLAB for cadence analysis and Python for audio synchronization.
• Mobile app that personalizes cadence and plays music tailored to individual users.

This project highlights:

• Application of Rhythmic Auditory Simulation in medical devices.
• Prototyping wearable technology.
• Algorithm development for cadence tracking and music synchronization.