Publication | Open Access
FPGA-Based Embedded Cyber-Physical Platform to Assess Gait and Postural Stability in Parkinson’s Disease
38
Citations
28
References
2018
Year
Gait AnalysisWearable TechnologyHardware SystemsMovement AnalysisKinesiologyKinematicsAbnormal GaitRehabilitation EngineeringHealth SciencesAssistive TechnologyAssess GaitComputer EngineeringRehabilitationPostural StabilityCyber-physical PlatformPd PatientsMovement DisordersParkinson DiseaseEeg Signal ProcessingSelective Diagnostic IndexesElectromyographyHealth MonitoringPathological GaitHuman MovementBraincomputer InterfaceMedicineMedical CpsHealth Informatics
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 noninvasive 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 electroencephalography and electromyography allows studying the motor cortex activity through the movement-related potentials, determining a novel set of indexes that could be used for the PD diagnosis and classification. In a future perspective of an application-specific integrated circuit implementation, the real-time data processing has been fully realized on the Altera Cyclone V field-programmable gate array (FPGA), without interactions with embedded processor architecture. Referring to an Altera Cyclone V SE 5CSEMA5F31C6N device, the whole implemented architecture exploits 90% of the available FPGA adaptive logic modules, 74% of the manageable registers, and 10.3% of the total memory, as well as 29.7% wires utilization. Furthermore, the system is able to provide the outputs in about 57 ms with a dynamically power dissipation of 89 mW. The platform has been tested in vivo on two Parkinson's patients and two healthy subjects (control group) covering three typical diagnostic scenarios: PD versus controls, drug treatment evaluation, and involuntary movements detection.
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