TY - CHAP
T1 - On the effect of reduced sampling rate and bitwidth on seizure detection
AU - Kelleher, Daniel
AU - Faul, Stephen
AU - Temko, Andrey
AU - Marnane, William
PY - 2009
Y1 - 2009
N2 - Ambulatory EEG requires signal processing algorithms which are efficient in terms of how much power they use in their computation, while at the same time providing accurate decision-making capabilities. Two methods of achieving this are to downsample the EEG and to perform bitwidth reduction on the data. The effect of performing both of these techniques to varying extents is investigated in this paper. Frequency, time and entropy based features are extracted from the data and used to train a Support Vector Machine (SVM) classification system. The effect of changing the overlap between successive epochs is also investigated.
AB - Ambulatory EEG requires signal processing algorithms which are efficient in terms of how much power they use in their computation, while at the same time providing accurate decision-making capabilities. Two methods of achieving this are to downsample the EEG and to perform bitwidth reduction on the data. The effect of performing both of these techniques to varying extents is investigated in this paper. Frequency, time and entropy based features are extracted from the data and used to train a Support Vector Machine (SVM) classification system. The effect of changing the overlap between successive epochs is also investigated.
UR - https://www.scopus.com/pages/publications/71249101689
U2 - 10.1109/WISP.2009.5286567
DO - 10.1109/WISP.2009.5286567
M3 - Chapter
AN - SCOPUS:71249101689
SN - 9781424450596
T3 - WISP 2009 - 6th IEEE International Symposium on Intelligent Signal Processing - Proceedings
SP - 153
EP - 156
BT - WISP 2009 - 6th IEEE International Symposium on Intelligent Signal Processing - Proceedings
T2 - WISP 2009 - 6th IEEE International Symposium on Intelligent Signal Processing
Y2 - 26 August 2009 through 28 August 2009
ER -