Abstract: A customizable recognition system with at least one processor to process the audio/video input to determine a control command for accessibility functions of a computer or gaming application. The customized recognition engine has a classifier for each different input type for the different types of speech or gestures. The classifier stored with a link or indication of a user identifier. The interface is configured to provide the control commands to a computer application, gaming application, or a laptop, or an access technology device.

Abstract: A system for a brain-computer interface (BCI) is provided. The system comprises an output unit configured to trigger a series of mental tasks for the patient, a device having a plurality of electrodes to continuously capture real-time raw electroencephalography (EEG) data from a patient, a server, and a display device to display and update an interface with visual elements based on issued control commands from the server. The server has an acquisition unit configured to receive the electrode data, a processor configured to detect real-time changes in brain-state of the patient in response to the series of mental tasks for the patient, a presentation unit configured to generate visual elements for an interface in real-time, and a display controller configured to issue control commands to update the interface using the generated visual elements. The processor detects the real-time changes in brain-state using the electrode data.

Abstract: A customizable recognition system with at least one processor to process the audio/video input to determine a control command for accessibility functions of a computer or gaming application. The customized recognition engine has a classifier for each different input type for the different types of speech or gestures. The classifier stored with a link or indication of a user identifier. The interface is configured to provide the control commands to a computer application, gaming application, or a laptop, or an access technology device.

Abstract: A device and method are provided for real-time classification of covert speech. The device comprises a plurality of sensors for capturing real-time bio-signal data for brain monitoring in response to mental tasks delivered to a user, and a brain computer interface with memory storing instructions to configure a processor to perform a method of real-time classification of covert speech. The method comprises capturing real-time bio-signal data for brain monitoring in response to mental tasks delivered to a user, pre-processing the raw bio-signal data, extracting a vector of features from the raw bio-signal data, selecting features from the vector of features, building classification model to generate classified covert speech data using the selected features, and controlling a display device with visual elements based on the classified covert speech data.

Abstract: A system for a brain-computer interface (BCI) is provided. The system comprises an output unit configured to trigger a series of mental tasks for the patient, a device having a plurality of electrodes to continuously capture real-time raw electroencephalography (EEG) data from a patient, a server, and a display device to display and update an interface with visual elements based on issued control commands from the server. The server has an acquisition unit configured to receive the electrode data, a processor configured to detect real-time changes in brain-state of the patient in response to the series of mental tasks for the patient, a presentation unit configured to generate visual elements for an interface in real-time, and a display controller configured to issue control commands to update the interface using the generated visual elements. The processor detects the real-time changes in brain-state using the electrode data.

Abstract: An in-ear EEG device is provided. The in-ear EEG device comprises an over-ear support arm coupled to an enclosure, and an earpiece coupled to the enclosure. The enclosure has a power switch, an analog output, a power input, and a processor. The processor is configured to receive EEG data and generate output data for the analog output. The earpiece collects the EEG data and transmits the EEG data to the processor.

Abstract: A device and method are provided for real-time classification of covert speech. The device comprises a plurality of sensors for capturing real-time bio-signal data for brain monitoring in response to mental tasks delivered to a user, and a brain computer interface with memory storing instructions to configure a processor to perform a method of real-time classification of covert speech. The method comprises capturing real-time bio-signal data for brain monitoring in response to mental tasks delivered to a user, pre-processing the raw bio-signal data, extracting a vector of features from the raw bio-signal data, selecting features from the vector of features, building classification model to generate classified covert speech data using the selected features, and controlling a display device with visual elements based on the classified covert speech data.

Abstract: A method of associating handwriting with an individual, or authenticating a document or transaction based on handwriting of one or more individuals is provided, the method including (a) collecting by operation of a handwriting instrument, biometric data from a plurality of instances of handwriting of at least one individual, such biometric data including grip pressure and optionally including axial pressure, so as to create a set of handwriting biometric data elements; (b) modeling the handwriting biometric data elements to create, or facilitate the creation of, a functional characteristic model for the handwriting of each of the at least one individual; and (c) associating each of one or more target instances of handwriting with an individual associated with such handwriting based on the functional characteristic model, and optionally based on such association(s) authenticating a document or transaction.