Low-cost intracortical spiking recordings compression with classification abilities for implanted BMI devices.
Within Brain-Machine Interface systems, cortically implanted microelectrode arrays and associated hardware have a low power budget for data sampling, processing and transmission. It is already possible to reduce neural data rates by on-site spike detection; we propose a method to further compress spiking data at a low computational cost, with the objective of maintaining clustering and classification abilities. The method relies on random binary vector projections, and simulations show that it is possible to achieve a compression ratio of 5 at virtually no cost in terms of classification errors.
CEA-LETI, Minatec Campus, Grenoble, France. fbertrand.coppa at cea.fr
Bertrand
B
Coppa
Rodolphe
R
Héliot
Olivier
O
Michel
Eric
E
Moisan
Dominique
D
David
D000200:Action Potentials / Q000502:physiology; D000465:Algorithms; D062207:Brain-Computer Interfaces; D002540:Cerebral Cortex / Q000502:physiology; D006801:Humans; D008839:Microelectrodes; D025341:Principal Component Analysis; D019736:Prostheses and Implants