FPGA-based online-learning using parallel genetic algorithm and neural network for ECG signal classification

This paper presents FPGA-based ECG signal classification based-on a parallel genetic algorithm and block-based neural network. The proposed parallel genetic algorithm has cellular-like structure which is suitable for hardware implementation. With online learning using hardware parallel genetic algorithm to block-based neural network, the complete ECG signal classification can be implemented in hardware. The proposed hardware can be implemented in FPGA or ASIC for a portable personalized ECG signal classifications for long term patient monitoring.