Reducing the number of channels for an ambulatory patient-specific EEG-based epileptic seizure detector by applying recursive feature elimination.
We are building an ambulatory version of a patient-specific epileptic seizure detector based on scalp EEG signals. Since patients have to wear the electrodes all the time, it is desirable to use the minimum number of electrodes needed to achieve good performance. In this paper, we describe a method that uses recursive feature elimination (RFE) to design detectors that use small numbers of electrodes. We also present results that indicate that the appropriate number of electrodes varies across patients. It is frequently the case that a surprisingly small number of electrodes, sometimes as few as two, suffices to construct a detector with expected performance comparable to that of detectors that use a full twenty-one-channel montage.
Glassman
Elena L
EL
CSAIL, MIT, Massachusetts.
Guttag
John V
JV
D000465:Algorithms; D001185:Artificial Intelligence; D001931:Brain Mapping / Q000295:instrumentation / Q000379:methods; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D004566:Electrodes; D004569:Electroencephalography / Q000295:instrumentation* / Q000379:methods*; D004827:Epilepsy / Q000175:diagnosis*; D006801:Humans; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted