Description
This paper serves to report the research performed towards detecting PD and the effects of medication through the use of machine learning and finger tapping data collected through mobile devices. The primary objective for this research is to prototype a PD classification model and a medication classification model that predict the following: the individual’s disease status and the medication intake time relative to performing the finger-tapping activity, respectively.
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Details
Title
- Prediction at the Tip of Your Fingers: A Machine Learning Approach to Predict Parkinson's Disease and the Effects of Medication
Contributors
- Gin, Taylor (Author)
- McCarthy, Alexandra (Co-author)
- Berisha, Visar (Thesis director)
- Baumann, Alicia (Committee member)
- Barrett, The Honors College (Contributor)
- Electrical Engineering Program (Contributor)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2022-05
Resource Type
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