Low-Cost Intracortical Spiking Recordings Compression with Classification Abilities for Implanted BMI Devices

International audienceCortically implanted microelectrode array systems have a low power budget for data processing and transmission. It is already possible to reduce data rates by spike detection but we propose a method to further compress the data with a low computational cost, with the objective of maintaining clustering and classification ability. The method relies on random binary vector projections, and simulations show that it is possible to achieve a compression rate of 5 at the cost of a few errors on classification