MUMBAI, India, May 29 -- Intellectual Property India has published a patent application (202641043635 A) filed by Lalin L Laudis, Kanniyakumari, Tamil Nadu, on April 6, for 'a system and method for early detection of parkinsons disease using speech signal analysis and optimized machine learning.'
Inventor(s) include Lalin L Laudis; and Marsaline Beno M.
The application for the patent was published on May 29, under issue no. 22/2026.
According to the abstract released by the Intellectual Property India: "The present invention relates to a system and method for early detection of Parkinson's disease using speech signal analysis and optimized machine learning techniques. The invention provides a non-invasive computational framework capable of analyzing speech signals to identify acoustic patterns associated with neurological abnormalities. The system comprises a speech acquisition module for capturing voice signals of a subject, a signal preprocessing unit for performing noise reduction, silence removal, normalization, and segmentation of speech signals, and a feature extraction engine configured to derive acoustic parameters including cepstral, spectral, and pitch-based features. The extracted features are processed by a feature optimization module that selects discriminative features using an optimization algorithm to improve classification performance. The optimized features are then supplied to a machine learning prediction module that classifies speech patterns and estimates the likelihood of Parkinson's disease. The prediction results are presented through a diagnostic output interface that provides probability scores and diagnostic indicators to assist clinicians or users in decision making. The proposed system enables automated, scalable, and non-invasive neurological screenmg, facilitating early identification of Parkinson's disease and supporting preventive healthcare monitoring."
Disclaimer: Curated by HT Syndication.
