TremorTrack: A Privacy-Aware Solution for Monitoring Parkinsonian and Essential Tremors

This paper discusses the TremorTrack application and studies its functionality as a home-based monitoring tool to periodically analyze and demonstrate observable differences in tremor severity. Using the application, an individual can record Parkinsonian and essential tremors, devoid of the location and time-sensitivity constraints linked to clinical settings. Tremor-Track combines the accelerometer sensor built into an Android handheld device, a Fast Fourier Transform (FFT) algorithm, and Amazon Web Services (AWS) for high-level analysis and data visualization. In contrast to existing work that typically focuses on diagnosis and management, our novel contribution extends this with the monitoring of the tremor's progression. It also includes comparing over multiple timepoints or averaging several readings as opposed to a single point in time. The usability and interactivity of TremorTrack through simple navigation with minimal input, making it accessible to those with impaired hand dexterity. We also report on our validation results that suggest a reliable simulation of a hand tremor that has increased in severity over time, clearly represented by comparing or averaging the associated timepoints.