Date of Award

2024

Document Type

Thesis

Terms of Use

© 2024 Jackie Le. All rights reserved. This work is freely available courtesy of the author. It may only be used for non-commercial, educational, and research purposes. For all other uses, including reproduction and distribution, please contact the copyright holder.

Degree Name

Bachelor of Arts

Department

Engineering Department

First Advisor

Maggie Delano

Second Advisor

Allan R. Moser

Third Advisor

Joseph Towles

Abstract

Parkinson’s Disease and Essential Tremor are two of the most common tremor-related conditions affecting millions of people globally. Various types of tremors, specifically in the hand, arise as symptoms characteristics to these tremor-related conditions. However, the lack of standardization and certainty between clinical tremor assessments motivates the future of medical devices to provide relevant medical diagnostics. Current literature shows promise for the ability of such devices to revolutionize home healthcare and integrate well into currently existing clinical procedures. This engineering design project aims to design a wearable medical device to detect and computationally characterise various types of tremors in Parkinson’s Disease and Essential Tremor according to their severity. In the process of doing so, a hand phantom is designed to simulate tremor severities on a set of defined parameters, while real datasets are gathered to provide validation. MATLAB code is run on an embedded system setup to analyse these tremor signals via standard digital signal processing techniques. Tremors were successfully simulated on the hand apparatus, while the live-tracking script was able to record and analyse tremor signals. Improving the accuracy of the classification portion requires further feature extraction and pipeline development, however this project has demonstrated feasibility in the design of an affordable and potentially reliable tremor sensing medical device.

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