Date of Award

2021

Degree Type

Thesis

Degree Name

Master of Science in Electrical Engineering (MSEE)

Specialization

Biomedical Engineering

Department

Electrical, Computer, and Biomedical Engineering

First Advisor

Kunal Mankodiya

Abstract

Parkinson's disease (PD) is a progressive neurodegenerative disorder that is caused by loss of dopaminergic neurons to cause a variety of motor symptoms like bradykinesia, movement rigidity, freezing of gait and resting tremors. It is necessary to detect symptom progression to alter medication plan. Present methods for evaluating the longitudinal progression of this ailment relies on visual evaluation by a trained rater, vastly limiting frequency of assessment and increasing burden on individuals with PD. In this work, we present the Wear-IoTex kit, that is composed of wearables (bands and gloves) and a study tablet that provides motor task prompts enabling in-home longitudinal upper body assessment of Parkinson's Disease and remote logging. In this thesis we detail the development of multiple components of the system from IoTex band firmware, IoTex glove and tablet web application development. Our design enables sensing of inertial signals and finger flexion (middle, index, ring) using bands and gloves. To assess feasibility of the proposed system, we conduct a longitudinal study with two participants with PD using bands and three participants with PD using gloves. Using the data collected, we perform system level analysis of data acquisition system and extract features from the device data. The preliminary validation results shows promise in assessing variations induced by medication usage.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

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