@inproceedings{dc9fe5cfff964bd38762902b6285a5dc,
title = "Compression of neural signals using discriminative coding for wireless applications",
abstract = "One of the most critical tasks when designing a portable wireless neural recording system is to limit power consumption. This paper proposes a new compression technique applied to neuronal recordings in real-time. The signal is compressed before transmission using a discriminative vector quantization algorithm and then it is reconstructed on the receiver side. Results show that power consumption is decreased while more efficiently using the limited bandwidth. A discriminative Linde-Buzo-Gray algorithm (DLBG) preserves action potential regions of the neuronal signal where information is contained while efficiently filtering background activity. The compression algorithm has been tested in real time on a hardware platform (PICO DSP [3]) that has a Digital Signal Processor (DSP) which performs the algorithm before sending the compressed data to a wireless transmitter. The compression ratios obtained range between 20:1 and 70:1 depending on the embedding size of the signal and the number of code-vectors used.",
author = "Stefan Craciun and David Cheney and Karl Gugel and Sanchez, {Justin C.} and Principe, {Jose C.}",
year = "2009",
month = oct
day = "27",
doi = "10.1109/NER.2009.5109375",
language = "English (US)",
isbn = "9781424420735",
series = "2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09",
pages = "629--632",
booktitle = "2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09",
note = "2009 4th International IEEE/EMBS Conference on Neural Engineering, NER '09 ; Conference date: 29-04-2009 Through 02-05-2009",
}