Dynamic, location-based channel selection for power consumption reduction in EEG analysis

Authors:
Stephen Faul;William Marnane
Affiliations:
Dept. of Electrical and Electronic Engineering, University College Cork, Ireland;Dept. of Electrical and Electronic Engineering, University College Cork, Ireland
Venue:
Computer Methods and Programs in Biomedicine
Year:
2012

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Abstract

The objective of this study is to develop methods to dynamically select EEG channels to reduce power consumption in seizure detection while maintaining detection accuracy. A method is proposed whereby a number of primary screening channels are predefined. Depending on the classification results of those channels, further channels are selected for analysis. This method provides savings in computational complexity of 43%. A further method called idling is then proposed which increases the computational saving to 75%. The performance of a location-independent, decision-based method is used for comparison. The proposed method achieves better computational savings for the same performance than the decision-based method. The decision-based method was capable of higher overall computational savings, but with a reduction in seizure detection performance. Each method was also implemented with the REACT algorithm on a Blackfin microprocessor and the average power measured. The proposed methods gave a power saving of up to 47% with no reduction in detection performance.