Quality assessment of EEG signals based on statistics of signal fluctuations

Abstract

Abstract —The quality of the non-invasive EEG signals wasalways affected by the changes in the contact impedances and theartifacts from eye blinking, eye movements and body movements.An effective quality assessment method is needed to assess thequalities of the EEG signals. This paper proposed a novel methodto assess the signal quality of EEG signals based on block-based measurements of the fluctuations of the second-order poweramplitudes of the EEG signals. The initial signal quality scoreswere generated by fusion of the mean power amplitudes and thesignal fluctuations of the motor imagery state with reference tobackground idling state. These scores were subsequently mappedto different quality levels by using fuzzy-c means clustering.Experimental results were conducted on the basis of 3 datasets of 15 healthy subjects performing motor imagery of handmovements and idle, for both gel-based and gel-less electrodes.The results obtained demonstrated that the proposed methodwas capable of evaluating the quality of the EEG signals, assupported by the clear separation of the assigned quality levelsbetween gel-based and gel-less electrodes. This further validatedthe assumption that generally the quality of the EEG signalsacquired based on the gel-based electrodes was better than thatof the gel-less electrodes.