Assessing Levodopa Effectiveness in Parkison's Disease During Gait Using Electroencephalogram and Machine Learning

Author(s)

Pires, Rafael Goncalves ; Pereira, Clayton Reginaldo ; Penedo, Tiago ; Papa, Joao Paulo ; Roder, Mateus ; Barbieri, Fabio Augusto

• Document type: Journal article
• Source: 2024 31ST INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSING, IWSSIP 2024; v. N/A, p. 5-pg., 2024-01-01.

Abstract

This study aims to investigate the temporal effects of levodopa, a fundamental medication for treating Parkinson's disease, a neurodegenerative condition that causes diverse motor alterations as it progresses. Our goal is to identify, at some specific intervals after the first levodopa intake, whether a machine learning approach can determine the effectiveness of that drug during gait exercises using electroencephalogram signals. The analysis will focus on identifying specific temporal patterns associated with levodopa administration and its impact on brain electrical activities during gait. We observed the proposed approach can accurately identify drug administration 90 minutes after the first levodopa intake, showing machine learning techniques are promising to cope with such a task. (AU)

• FAPESP's process: 18/03448-6 - Challenges encountered during complex walking tasks in people with Parkinson's disease: manipulating obstacle characteristics and configuration
• Grantee: Fabio Augusto Barbieri
• Support Opportunities: Research Grants - Visiting Researcher Grant - International
• FAPESP's process: 17/19516-8 - Effect of medication, dual tasking and asymmetry on the cortical brain activity during gait in older people with Parkinson's disease
• Grantee: Fabio Augusto Barbieri
• Support Opportunities: Regular Research Grants
• FAPESP's process: 22/02971-2 - Unrevealing the gait asymmetry in patients with Parkinson’s Disease: from the neural and motor mechanisms to rehabilitation: AsymmGait-Parkinson study
• Grantee: Fabio Augusto Barbieri
• Support Opportunities: Research Grants - Initial Project
• FAPESP's process: 23/14427-8 - Data Science for Smart Industry (CDII)
• Grantee: José Alberto Cuminato
• Support Opportunities: Research Grants - Research Centers in Engineering Program
• FAPESP's process: 19/07665-4 - Center for Artificial Intelligence
• Grantee: Fabio Gagliardi Cozman
• Support Opportunities: Research Grants - Research Program in eScience and Data Science - Research Centers in Engineering Program
• FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
• Grantee: Francisco Louzada Neto
• Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC