Realtime Parkinson Detection Using AI

EasyChair Preprint no. 13045

Abstract

This project aims to develop a real-time Parkinson detection system utilizing artificial intelligence techniques. The system focuses on analyzing voice recordings to determine the presence of Parkinson's disease. By employing advanced AI algorithms, including machine learning and signal processing, the system can accurately detect subtle variations in vocal characteristics associated with Parkinson's. Real-time processing allows for immediate feedback, enabling timely intervention and support for individuals potentially affected by the disease. This innovative approach showcases the potential of AI in healthcare, particularly in early disease detection and management, ultimately improving patient outcomes and quality of life. Through machine learning techniques, the system distinguishes between healthy and Parkinson's affected voices with high accuracy. Real-time implementation enables early detection and intervention, potentially improving the quality of life for individuals with Parkinson's disease.

Keyphrases: Artificial Intelligence Techniques, detection, Machine Learning Techniques, real-time processing

@Booklet{EasyChair:13045,
  author = {Jakkula Nikil and Bommera Kavyasri and Edubilli Tarunkumar and Bejawada Gopinadh},
  title = {Realtime Parkinson Detection Using AI},
  howpublished = {EasyChair Preprint no. 13045},

  year = {EasyChair, 2024}}