EEG Classification with a Sequential Decision-Making Method in Motor Imagery BCI.

To develop subject-specific classifier to recognize mental states fast and reliably is an important issue in brain-computer interfaces (BCI), particularly in practical real-time applications such as wheelchair or neuroprosthetic control. In this paper, a sequential decision-making strategy is explored in conjunction with an optimal wavelet analysis for EEG classification. The subject-specific wavelet parameters based on a grid-search method were first developed to determine evidence accumulative curve for the sequential classifier.

Neuroprosthetic limb control with electrocorticography: approaches and challenges.

Advanced upper limb prosthetics, such as the Johns Hopkins Applied Physics Lab Modular Prosthetic Limb (MPL), are now available for research and preliminary clinical applications. Research attention has shifted to developing means of controlling these prostheses. Penetrating microelectrode arrays are often used in animal and human models to decode action potentials for cortical control.

Identifying neuron communities during a reach and grasp task using an unsupervised clustering analysis.

Recent advances in brain-machine interfaces (BMIs) have allowed for high density recordings using microelectrode arrays. However, these large datasets present a challenge in how to practically identify features of interest and discard non-task-related neurons. Thus, we apply a previously reported unsupervised clustering analysis to neural data acquired from a non-human primate as it performed a center-out reach-and-grasp task.

Improved BCI performance with sequential hypothesis testing.

One of the primary challenges in noninvasive brain-computer interface (BCI) control is low information transfer rate (ITR). An approach that employs a power-based sequential hypothesis testing (SHT) technique is presented for real-time detection of motor commands. Electroencephalogram (EEG) recordings obtained during a BCI task were first analyzed with a hypothesis testing (HT) method.