Neural Spike Compression Based on Random Sampling and IMATI Techniques

A new spike compression approach for implantable intra-cortical neural recording microsystems is proposed. This approach is based on random sampling and Iterative Method and Adaptive Thresholding with Interpolation (IMATI) techniques to compress and reconstruct the neural spikes respectively. The proposed method presents a compression ratio of 10 along with SNDR of 12 and normalized RMS of error equal to 5.5%. The superiority of this work is lower computation complexity with same compression performance in comparison with similar works.