Brain signal reference concept using cross correlation based for brain computer interface

On the characterization of cognitive tasks using activity-specific short-lived synchronization between electroencephalography channels

“…• Our analysis extended the premise that the brain synchronization emerges at similar time lags for similar cognitive activities (Bandt et al, 2019;Feige et al, 2017;Hermanto et al, 2013;Mitra et al, 2015). Here, we showed that the brain exhibits synchronization patterns not only on specific time lags but also at specific latency and duration parameters as well.…”

“…They also suggested that the synchronization lag among the oscillatory activities becomes smaller for faster and more accurate inter-regional communication and that the inter-regional synchronization lag reorganizes to adapt to the requirements of cognitive activities (Wang et al, 2019). Hermanto et al stated that the brain should generate similar synchronization patterns at similar timings among its regions for each trial of a particular cognitive task to meet the task-specific demands (Hermanto et al, 2013). These findings suggest that an accurate characterization of cognitive tasks can be achieved by capturing and using activity-specific timings at which the systematic and characteristic inter-regional short-lived synchronization occurs (Bassett et al, 2006;Jin et al, 2012).…”

Motor imagery EEG signal classification on DWT and crosscorrelated signal features

“…Those which are darkened depict the most informative regions corresponding to MI data. After choosing the reference signal, cross-correlation is done between the reference signal and all the other non-reference signals, according to the equation Hence if the first column i.e., the first training example, is cross-correlated with all the other 235 training examples, it would result in 235 new signals [11]. In order to handle the cross-correlogram sequence comfortably, the dimension of the data has to be reduced.…”

Evaluation of synchronization measures for capturing the lagged synchronization between EEG channels: A cognitive task recognition approach

“…In Ref. [67], using cross-correlation, Hermanto et al try to recognize motor imagery brain activity by finding the time lags between electrophysiological signal pairs across periods. In here, the main assumption is that the brain generates similar motor imagery related oscillatory activity within same time interval.…”