Wearable in an Embedded System for Assistance in the Treatment of Individuals with Parkinson's Disease: A Machine Learning Approach.

• Grant number: 24/07082-7
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2024
• End date: September 30, 2025
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Clayton Reginaldo Pereira
• Grantee: Manuele Sabatini Christófalo
• Host Institution: Faculdade de Ciências (FC). Universidade Estadual Paulista (UNESP). Campus de Bauru. Bauru , SP, Brazil

Abstract

Parkinson's Disease (PD) is the most prevalent neuromotor condition worldwide, affecting approximately 9 million individuals globally. It is characterized by the degeneration of cells located in the midbrain, a region of the brain responsible for the production of dopamine-an essential neurotransmitter for motor control. PD leads to impaired bodily functions, presenting symptoms such as bradykinesia and involuntary tremors, among others. Although there is no cure, therapeutic and pharmacological treatments have been employed to provide a better quality of life for PD patients.In this context, the present proposal involves the development of a wearable bracelet integrated with the Internet of Things (IoT) through an Arduino board and sensors. The device aims to measure the tremors associated with PD, allowing for the assessment of the disease's progression and the effectiveness of treatment, with a particular focus on the impact of medication. Through temporal analyses and Machine Learning (ML) techniques, the instrument will be capable of collecting precise and relevant data for therapy, enabling its optimization in a non-invasive and cost-effective manner.