Improving the power of objective response detection of evoked responses in noise by using average and product of magnitude-squared coherence of two different signals

Objective response detection (ORD) techniques such as the magnitude-squared coherence (MSC) are mathematical methods tailored to detect potentials evoked by an external periodic stimulation. The performance of the MSC is directly proportional to the signal-to-noise ratio (SNR) of the recorded signal and the time spent for collecting data. An alternative to increasing the performance of detection techniques without increasing data recording time is to use the information from more than one signal simultaneously. In this context, this work proposes two new detection techniques based on the average and on the product of MSCs of two different signals. The critical values and detection probabilities were obtained theoretically and using a Monte Carlo simulation. The performances of the new detectors were evaluated using synthetic data and electroencephalogram (EEG) signals during photo and auditory stimulation. For the synthetic signals, the two proposed detectors exhibited a higher detection rate when compared to the rate of the traditional MSC technique. When applied to EEG signals, these detectors resulted in an increase of the mean detection rate in relation to MSC for visual and auditory stimulation of at least 25% and 13.21%, respectively. The proposed detectors may be considered as promising tools for clinical applications.