Realtime bioelectrical data acquisition and processing from 128 channels utilizing the wavelet-transformation

We propose a versatile signal processing and analysis framework for bioelectrical data, and in particular for neural recordings and EEG. Within this framework the signal is decomposed into subbands using fast wavelet transform algorithms, executed in real-time on a current digital signal processor hardware platform. The decomposition is used to perform various processing and analysis tasks. Besides fast implementation of high, band, and low pass filters, the decomposition is used for denoising and lossy, as well as lossless compression. Furthermore specific electrophysiologic analysis tasks like spike detection and sorting are performed within this decomposition scheme.