Method and system for analyzing EEG signal based on fpga

Abstract

The invention discloses an FPGA (Field Programmable Gate Array) based electroencephalogram and electro-oculogram signal analysis method and system. The FPGA based electroencephalogram and electro-oculogram signal analysis method comprises collecting electric signals on the surface of the cerebral cortex through a signal collection module and enabling the electric signals to be converted into digital signals and transmitted to an FPGA board in a wireless transmission mode for decoding; obtaining different frequency bands of energy intensities of electroencephalogram signals through a spectrum conversion module; obtaining the blinking intensity of electro-oculogram signals through a blinking signal extraction module; performing data packaging on the electroencephalogram and electro-oculogram signals after processing and transmitting a data package to an upper computer in a wireless mode; performing resolution on the data package through the upper computer and performing real-time display on the useful information. According to the FPGA based electroencephalogram and electro-oculogram signal analysis method and system, the processing speed of data is improved through the multi-channel electroencephalogram signal spectrum conversion and blinking signal extraction; the accuracy and the transmission efficiency of the data are ensured through the data packaging, the low-cost online processing on the large-scale electroencephalogram and electro-oculogram signals is implemented, and the embedded implementation is easy to achieve; the FPGA based electroencephalogram and electro-oculogram signal analysis method and system can be widely applied to the signal analysis field.

Description

technical field [0001] The invention relates to the field of signal analysis, in particular to an FPGA-based electroencephalogram signal analysis method and system. Background technique [0002] In recent years, human-computer interaction technology using bioelectrical signals such as EEG and oculoelectric signals as information carriers is an important research direction in the field of computer applications and information processing. It has important scientific significance and broad application prospects. However, when the number of bioelectrical signal channels is large and the amount of information is large, how to ensure the online analysis and processing of large-scale signals has become an urgent problem to be solved. [0003] The traditional large-scale EEG and OEG signal analysis and processing methods can be divided into two categories: software and hardware methods. The software method has the advantages of low cost and simple operation. The disadvantage is tha...

AI Technical Summary

Problems solved by technology

The disadvantage is that due to the limitation of computing speed, it cannot meet the online processing requirements for large-scale EEG and oculoelectric signals, and is often used in the occasion of offline analysis and processing of signals; the hardware method mostly uses high-performance computers as the main processing unit, and the advantage is that it can Meet the online processing requirements of signals, such as BlueGene, SpiNNaker and SyNAPSE and other systems are based on supercomputers to complete complex calculations

The disadvantage is that its portability is very poor and the configuration is complicated, the price is expensive, and the power consumption is too high, so it is limited to experimental research and difficult to realize as an industrialization

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