학술논문
Real-time adaptive discrimination threshold estimation for embedded neural signals detection
Document Type
Conference
Author
Source
2009 4th International IEEE/EMBS Conference on Neural Engineering Neural Engineering, 2009. NER '09. 4th International IEEE/EMBS Conference on. :597-600 Apr, 2009
Subject
Language
ISSN
1948-3546
1948-3554
1948-3554
Abstract
Multi-electrode array systems used in neurological applications produce large amount of data because of the simultaneous continuous high-rate sampling on a large number of channels. This data flow must be reduced to envision compact data acquisition systems with wireless transmission for body implantation. In spike-related applications, the useful data is sparse due to the relative low neurons firing rate combined to the high sampling rate. High compression ratio can be achieved by detecting, extracting and storing only the relevant spike occurrences. The first step is to provide a simple yet robust discrimination threshold based on the characteristics of the noise distribution. This article presents both a method and its hardware implementation for adaptive spike detection.