Automatic Detection and Correction of Blink Artifacts in Single Channel EEG Signals

Abstract

Ocular Artifacts (OAs) are inevitable during EEG acquisition and make the signal analysis critical. Detection and correction of these artifacts is a major problem now a day's. In this paper an energy detection method is used to detect the artifacts and performed wavelet thresholding within the researched zones to protect neural data at non blink regions. Various sets of Wavelet Transform (WT) techniques and threshold functions are collated and identification of the optimum combination for OA's separation is indicated in many research areas including Technology & Management. The output of these methods at blink regions is compared interns of various standard metrics using established techniques of Supply Chains. Results of this study demonstrate that the SWT+HT has better in rejecting the artifacts than other methods in this paradigm.

Source separation on single channel EEG: A pilot study on effect of transcranial alternating current stimulation on scalp meridian

“…One major problem with single-channel EEG is that the signal-to-noise ratio is rather low when compared to those of multiple-channel systems used in clinics and academia [14,15]. Theoretically, data with a mono source is more difficult to be analyzed with ICA, which needs multi-channel to be performed.…”

Eye Blink Identification and Removal From Single-Channel Eeg Using Emd With Energy Threshold and Adaptive Filter

“…As such, most eye blink detection methods use amplitude-based quantification as means for non-eye blink and eye blink region segregation. This may be in terms of windowed amplitude mean as proposed by authors of [9], highest amplitude as reference for eye blink temporal span approximation as posited in [7], amplitude power, as demonstrated in [10], and amplitude energy as being presented in [11].…”