Dynamic channel selection to reduce computational burden in seizure detection.

Ambulatory physiological monitoring devices benefit patients, medical staff and hospitals by allowing patients to return home with the devices for monitoring. The main problem associated with designing such devices is that of power consumption. Wireless communications and complex processing are generally part of such devices and are power hungry components. These problems are magnified when dealing with EEG signals, with relatively high data rates, multiple channels, and advanced signal processing techniques required. This paper proposes a method to dynamically select EEG channels in the REACT seizure detection system based on information already available in the system, hence keeping any added computational complexity very low. Using the techniques computational effort can be reduced by up to 65% with no effect on the REACT seizure detection performance.