FPGA-Based Implementation of EEG Analyzer

During the last decades, understanding of the brain activity became a topic of major interest. Fast rhythm of life and everyday stress raised significantly the role of mental disorders in our society. Modern methods of brain imaging are applied nowadays to get objective information about changes in brain physiology characteristic for mental diseases and disorders. A new method for detection of depressive disorder based on analysis of the EEG frequency spectrum was proposed in [1]. The method is capable of determining depressive disorders or other mental disorders that are related to similar brain imbalances. The presumption is that the EEG beta band (13-30 Hz) includes useful information for evaluation of depression, whereas the EEG theta band (4-8 Hz) is stable and not affected by a disease. A spectral asymmetry index (SASI) is calculated as a relative differences in power of two EEG special frequency bands selected higher and lower of the EEG spectrum maximum. The EEG central frequency band around the spectrum maximum (alpha band) is excluded from the calculations. The input data for the calculation, stored on SD-card, is the EEG signal recorded for 20 minutes from 2 electrodes. The SASI calculation algorithm has been previously implemented as a MatLab program running on a PC connected to a commercial EEG signal capturing equipment. The main challenge was to develop a portable device with the same functionality. Such dedicated portable device would offer more convenience for obtaining experimental data, real-time analysis and acceleration of the calculation procedure. In addition, the SASI calculation algorithm contains Digital Signal Processing (DSP) modules that can be used also for other analysis tasks. This will allow building an FPGA-based device for health monitoring that is reconfigured depending on the task to be solved. Reconfigurability is beneficial because most of the analysis tasks, like the same EEG analysis, are executed over long time intervals and the space occupied by the modules can be used for other purposes in meantime. The developed prototype consists of three main parts – EEG analyzer, VGA output generator for 8” LCD display and SD-card controller. All modules fit into a Spartan-3S1000 chip.