Abstract
Brain computer interfaces (BCIs) offer a broad class of neurologically impaired individuals an alternative means to interact with the environment. Many BCIs are “synchronous” systems, in which the system sets the timing of the interaction and tries to infer what control command the subject is issuing at each prompting. In contrast, in “asynchronous” BCIs subjects pace the interaction and the system must determine when the subject’s control command occurs. In this paper we propose a new idea for BCI which draws upon the strengths of both approaches. The subjects are externally paced and the BCI is able to determine when control commands are issued by decoding the subject’s intention for initiating control in dedicated time slots. A single task with randomly interleaved trials was designed to test whether it can be used as stimulus for inducing initiation and non-initiation states when the sensory and motor requirements for the two types of trials are very nearly identical. Further, the essential problem on the discrimination between initiation state and non-initiation state was studied. We tested the ability of EEG spectral power to distinguish between these two states. Among the four standard EEG frequency bands, beta band power recorded over parietal-occipital cortices provided the best performance, achieving an average accuracy of 86% for the correct classification of initiation and non-initiation states. Moreover, delta band power recorded over parietal and motor areas yielded a good performance and thus could also be used as an alternative feature to discriminate these two mental states. The results demonstrate the viability of our proposed idea for a BCI design based on conventional EEG features. Our proposal offers the potential to mitigate the signal detection challenges of fully asynchronous BCIs, while providing greater flexibility to the subject than traditional synchronous BCIs.
Highlights
Brain computer interfaces (BCIs), more generally known as brain-machine interfaces (BMIs), offer an alternative means to interact with the environment, which is important for patients whose normal means of interaction are compromised by central nervous system damage, such as caused by brainstem strokes, upper spinal cord injury, and amyotrophic lateral sclerosis (ALS) [1,2,3,4]
We investigated the fundamental problem of separating initiation states from non-initiation states, demonstrating the viability of a new approach for BCI design in which subjects are externally paced but allowed to determine on which prompting cycles control commands are issued
Using Support vector machine (SVM) classification and EEG spectral features, we could distinguish between the initiation state, when subjects were preparing to make choices, and non-initiation states during which subjects were engaged in otherwise similar task contingencies but not required to make a choice
Summary
Brain computer interfaces (BCIs), more generally known as brain-machine interfaces (BMIs), offer an alternative means to interact with the environment, which is important for patients whose normal means of interaction are compromised by central nervous system damage, such as caused by brainstem strokes, upper spinal cord injury, and amyotrophic lateral sclerosis (ALS) [1,2,3,4] They may provide an assistive mechanism to healthy individuals in demanding tasks [5,6,7]. Most laboratory-based BCIs are designed to determine what the subject’s intentions are, in the form of commands (or communication) signals, in a protocol where subjects are constantly prompted to make choices. The BCI must solve the signal detection problem, trying to maximize true positives while minimizing false positives, a tradeoff usually optimized by adopting extra layers of design complexity such as error correction schemes [17] and/or dwell times and refractory periods [10]
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