PARKINSON’S DISEASE PREDICTION SYSTEM

Abstract

ABSTRACT A Parkinson’s disease prediction system (100) comprising: a plurality of wearable devices configured to collect physiological and behavioral data from a user; a machine learning module configured to analyze the collected data and detect early-stage patterns indicative of Parkinson’s disease; a processor configured to manage and optimize the prediction process, ensuring precision and efficiency; a communication module for transmitting the analyzed data to a healthcare platform for real-time monitoring and prediction. <>

Specification

Description:FIELD OF THE DISCLOSURE
[0001] This invention generally relates to a field of healthcare and, in particular, to a system for predicting Parkinson's disease using machine learning algorithms, enhancing the accuracy and timeliness of diagnosis, and improving patient care by providing early detection of Parkinson's disease.
BACKGROUND

[0002] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
[0003] Parkinson's disease is a progressive neurodegenerative disorder that primarily affects movement control. It is the second most common neurodegen , Claims:WE CLAIM:
1. A Parkinson's disease prediction system (100) comprising:
a plurality of wearable devices configured to collect physiological and behavioral data from a user;
a machine learning module configured to analyze the collected data and detect early-stage patterns indicative of Parkinson's disease;
a processor configured to manage and optimize the prediction process, ensuring precision and efficiency;
a communication module for transmitting the analyzed data to a healthcare platform for real-time monitoring and prediction.

2. The system (100) as claimed in claim 1, wherein the wearable devices include accelerometers, gyroscopes, and microphones for collecting movement and speech data.

3. The system (100) as claimed in claim 1, wherein the machine learning module uses classification algorithms to detect early-stage Parkinson's disease patterns.

4. The system (100) as claimed in claim 1, further comprising a user interface for displaying real-time feedback and predictions to the user.

5. The system (1

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