The cerebral hemodynamic response is inherently slower than the corresponding electrical response measured using EEG. The majority of systems have used electroencephalography (EEG) ( Wolpaw et al., 2002), while hemodynamic-based monitoring modalities such as near-infrared spectroscopy (NIRS) ( Sitaram et al., 2009 Falk et al., 2011), and transcranial Doppler (TCD) ultrasonography systems ( Myrden et al., 2011) are emerging BCI alternatives. Many portable brain monitoring modalities have been explored for BCI development. BCI systems enable users to generate a control command through mental activity alone ( Tai et al., 2008). Brain-computer interface (BCI) systems offer an alternative means of communication for these individuals ( Tai et al., 2008). Individuals who are cognitively aware but living with severe motor disabilities such as muscular dystrophy, multiple sclerosis, high-level spinal cord injuries or locked-in syndrome may not be able to use conventional means of expression such as speech and gestures for communication. Future interface and signal classification enhancements are required to improve communication rate. These findings suggest that an online TCD-BCI can achieve reasonable accuracies with an intuitive language task, but with modest throughput. The average information transfer rate was 0.87 bits/min with an average throughput of 0.31 ± 0.12 character/min. The level of agreement between the intended and machine-predicted selections was moderate (κ = 0.60). The system achieved an average specificity and sensitivity of 81.44 ± 8.35 and 82.30 ± 7.39%, respectively. With 10 able-bodied right-handed young adults, the two mental tasks were differentiated online using a Naïve Bayes classification algorithm and a set of time-domain, user-dependent features. Undesired letters or words were bypassed by performing visual tracking, a non-lateralized task. Target letters or words were selected by repetitively rehearsing the spelling while imagining the writing of the intended word, a left-lateralized task. In this paper, an online TCD-BCI system was implemented, bilaterally tracking blood flow velocities in the middle cerebral arteries for system-paced control of a scanning keyboard. The feasibility of a TCD-based BCI system hinges on its online performance. However, TCD-BCI studies to date have exclusively been offline. An emerging brain monitoring modality for BCI development is transcranial Doppler ultrasonography (TCD), which facilitates the tracking of cerebral blood flow velocities associated with mental tasks.
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