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Parkinson's disease affects about 1% of the population over 65 years old and even with multiple researches trying to measure or identify the disease, there are still difficulties in finding methods and tools that result in reliable data collection due to unpredictability and variability of their clinical signs. This necessity led to the idea of creating an architecture of an embedded system for monitoring with extended time of an individual with Parkinson's disease. The system must adapt the situations of everyday life collecting inertial and electromyography data with minimal interference as possible, have a high sampling rate and storage capacity of these data in a portable memory for future analysis.

ARQUITETURA DE UM SISTEMA PARA MONITORAMENTO PROLONGADO DE SINAIS CLÍNICOS DA DOENÇA DE PARKINSON