Hartley transforms and narrow bessel bandpass filters produce similar power spectra of multiple frequency oscillators and all-night EEG.

Frequency specific power obtained from time and frequency domain analyses are explored in simulated signals and all-night electroencephalogram (EEG). Signals were subjected to a fast Hartley transformation (FHT) and to digital sixth-order Bessel bandpass filters (BDF) of the infinite impulse response type. Numeric values of FHT, BDF and, if suited, authentic frequency specific power were subjected to a Pearson correlation. Frequency bins at 1.6-2.4 Hz (delta), 4.75-5.9 Hz (theta), 9.3-11.5 Hz (alpha), 12.5-14.9 Hz (sigma) and 16.6-19.5 Hz (beta) were investigated. When compared with true power of single frequency oscillators (256-sample windows), frequency specific power of the FHT correlated functionally (1.0) and BDF correlated highly (0.85, delta; 0.99, other bins). For analyses of "white noise", a multiple frequency oscillator and all-night EEG, four rectangular window sizes were applied (256, 512, 1,024 or 2,048 samples). The FHT power correlated better with authentic frequency specific power of "white noise" (256-sample windows) (0.61-0.98) than BDF power (0.67-0.89). With 512-sample windows of "white noise", the estimate of both the FHT (0.69-0.99) and BDF (0.71-0.93) improved. Direct comparison between FHT and BDF frequency specific power obtained from "white noise" or all-night EEG revealed a high degree of compliance between methods for all frequency bins (up to 0.99). For delta, the accord was relatively low for the 256-sample window (EEG, 0.68; "white noise", 0.72), but increased with lengthening window size (2,048-sample: 0.97; 0.99). Averaging of multiple EEG 256-sample windows also increased the agreement between methods.(ABSTRACT TRUNCATED AT 250 WORDS)