Multichannel evoked neural signal compression using advanced video compression algorithm
Journal
2009 4th International IEEE/EMBS Conference on Neural Engineering
Pages
697-701
Date Issued
2009
Author(s)
Abstract
Multichannel neural recording is one of the most important topics in the field of biomedical engineering. This is because there is a need to considerably reduce large amounts of data without degrading the data quality for easy transfer through wireless transmission. Video compression technology is of considerable importance in the field of signal processing. There are many similarities between multichannel neural signals and video signals. In this study, we propose a signal compression method that employs motion vectors (MVs) to reduce the redundancy between successive video frames and between successive channels. The method shows a signal-to-noise (error) ratio (SNR) of 25 db and data are compressed to 5% of their original size.
Type
conference paper
