Abstract
Brain-computer interfaces (BCI) can detect specific EEG patterns and translate them into control signals for external devices by providing people suffering from severe motor disabilities with an alternative/additional channel to communicate and interact with the outer world. Many EEG-based BCIs rely on the P300 event-related potentials, mainly because they require training times for the user relatively short and provide higher selection speed. This paper proposes a P300-based portable embedded BCI system realized through an embedded hardware platform based on FPGA (field-programmable gate array), ensuring flexibility, reliability, and high-performance features. The system acquires EEG data during user visual stimulation and processes them in a real-time way to correctly detect and recognize the EEG features. The BCI system is designed to allow to user to perform communication and domotic controls.
Highlights
The purpose of the Brain-computer interfaces (BCI) research is the realization of a new assistive communication and control technology for people with severe neuromuscular disabilities [1,2,3], such as amyotrophic lateral sclerosis (ALS), spinal cord injury, stroke, multiple sclerosis, and muscular dystrophies [4,5,6,7,8,9,10,11,12,13]
The embedded platform used for developing the BCI system is an integrated acquisition and processing system based on field-programmable gate array (FPGA) technology
Since applications are implemented in hardware without an operating system, FPGA will run them reliably
Summary
The purpose of the BCI research is the realization of a new assistive communication and control technology for people with severe neuromuscular disabilities [1,2,3], such as amyotrophic lateral sclerosis (ALS), spinal cord injury, stroke, multiple sclerosis, and muscular dystrophies [4,5,6,7,8,9,10,11,12,13]. Several groups have perfected this system through the use of alternative EEG registration sites, signal-processing methods, and stimulus presentation parameters and formats to improve the speed, accuracy, capacity, and clinical practicality of the P300-based BCI systems, to make them a valid option of communication and control for people with severe motor disabilities [27,28,29,30,31,32,33,34]. These BCI systems are based on the use of personal computers. FFiinnaallllyy,, SSeeccttiioonn 44 ccoonncclluuddeess tthhee ppaappeerr,, hhiigghhlliigghhttiinngg the innovative features of our system
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