A Sensor-Based Platform for Early-Stage Parkinson's Disease Monitoring

Biosensing platforms have gained much attention in clinical practice screening thousands of samples simultaneously for the accurate detection of important markers in various diseases for diagnostic and prognostic purposes. Herein, a framework for the design of an innovative methodological approach combined with data processing and appropriate software in order to implement a complete diagnostic system for Parkinson's disease exploitation is presented. The integrated platform consists of biochemical and peripheral sensor platforms for measuring biological and biometric parameters of examinees, a central collection and management unit along with a server for storing data, and a decision support system for patient's state assessment regarding the occurrence of the disease. The suggested perspective is oriented on data processing and experimental implementation and can provide a powerful holistic evaluation of personalized monitoring of patients or individuals at high risk of manifestation of the disease.