PARKINSON_DETECTION

The Parkinson’s Disease Detection System is developed to identify early signs of Parkinson’s disease using machine learning techniques. Patient data such as voice signals, movement patterns, or medical records are processed by a Single Board Computer (SBC). Machine learning models analyze the data to detect abnormalities associated with Parkinson’s disease. This helps support early diagnosis and medical decision-making. This project uses an SBC, ML algorithms, medical datasets, and data analysis techniques, making it suitable for healthcare and neurological research applications.