Spindle Filter Optimisation with Receiver Operating Characteristics-Curves
The automatic detection of sleep spindles can be accomplished with filter methods. The optimisation of filter characteristics is necessary to improve the performance of the detection. Raw EEG data were filtered with varying basebands in the frequency range of sleep spindles. The outputs were taken to calculate Receiver Operating Characteristics-Curves (ROC-Curves). The area under the ROC-curve (AUC) served as the only optimisation parameter. The maximum AUC had 0.962 square units. This result corresponded to a filter-function with edge-frequencies of 12Hz and 16.8Hz. The shown optimisation procedure is not limited to any number of free parameters. Solely data marked by an expert is needed. The ROCcurves can be further used to find a suitable detection-threshold for sleep spindles.