FPGA-based Embedded Cyber-Physical Platform to Assess Gait and Postural Stability in Parkinson Disease

Abnormal gait and postural instability are common disorders in people affected by Parkinson’s disease (PD). This paper proposes an embedded cyber-physical system for the identification and the real-time extraction of highly selective diagnostic indexes for PD patients. A non-invasive wearable and wireless architecture for both gait analysis and postural instability detection has been proposed and implemented on a programmable hardware. The combined analysis of EEG and EMG allows studying the motor cortex activity through the Movement Related Potentials (MRPs), determining a novel set of indexes that could be used for the PD diagnosis and classification. In a future perspective of an ASIC implementation, the real-time data processing has been fully realized on the Altera Cyclone V FPGA, without interactions with embedded processor architecture. Referring to an Altera Cyclone V SE 5CSEMA5F31C6N device, the whole implemented architecture exploits the 90% of the available FPGA ALMs, the 74% of the manageable registers and the 10.3% of the total memory, as well as the 29.7% wires utilization. Furthermore, the system is able to provide the outputs in about 57ms with a dynamically power dissipation of 89mW. The platform has been tested in-vivo on 2 Parkinson’s patients and 2 healthy subjects (control group) covering three typical diagnostic scenarios: PD vs. Controls, Drug Treatment Evaluation and Involuntary Movements detection.