Parkinson's Disease Detection Using Machine Learning

Parkinson's disease (PD) is a type of progressive neurological disorder which effect on the human nervous system and its main cause is decrease level of dopamine in forebrain. To develop a web application to detect if a persons have the PD or not having the PD using input voice features and sup...

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Bibliographic Details
Published in2022 International Conference on Smart and Sustainable Technologies in Energy and Power Sectors (SSTEPS) pp. 254 - 258
Main Authors Anthoniraj, S., Kumar, A Naresh, Hemakumar Reddy, Galiveeti, Gope, Sadhan, Raju, More
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2022
Subjects
Dopamine
Feature extraction
KNN
Parkinson's disease
Predictive models
Random Forest
Real-time systems
Support Vector Machine
Support vector machines
Time-frequency analysis
User interfaces
XGBOOST
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Summary:Parkinson's disease (PD) is a type of progressive neurological disorder which effect on the human nervous system and its main cause is decrease level of dopamine in forebrain. To develop a web application to detect if a persons have the PD or not having the PD using input voice features and supervised machine learning models. Linear and time frequency based features are extracted from each input voice samples. These are used to train and are given as input for the machine learning model to predict. Presence of PD or not. We are here using the voice dataset collected from people with and without PD for Machine Learning algorithms: SVM, Random Forest, XGBoost, and KNN.
DOI:10.1109/SSTEPS57475.2022.00070