Abstract: A wearable device worn at a head region of a user includes electrodes for measuring a signal evoked by a visual stimulus. The electrodes include a first dry electrode configured to contact the skin around an car of the user. The se electrodes additionally include a second dry electrode configured to provide a reference signal for the measurement of the signal evoked by the visual stimulus.

Abstract: A brain computer interface (BCI) system predicts text based on input and output signals obtained in relation to an individual that are informative for determining an individual's neurobiological activity. The BCI system applies a first predictive model to the input signal and a second predictive model to the output signal. The first predictive model predicts the forward propagation of the input signal through the individual's head whereas the second predictive model predicts the backward propagation of the output signal through the individual's head. Each of the first predictive model and second predictive model predicts characteristics of their respective signal at a common plane such as the cortical surface of the individual's brain. The BCI system predicts text by applying a third predictive model to the predicted signal characteristics at the common plane outputted by the first predictive model and the second predictive model.

Abstract: A brain computer interface system includes a wearable interface, an eye tracking device, and a client device for determining what object a user is looking at on an electronic display. The client device determines a region on the electronic display based on an estimated user gaze direction received from the eye tracking device. For each virtual object in the gaze region, the client device displays a visual stimulus with a unique frequency. The client device receives from the wearable interface an electrical potential signal measured at the user's brain and evoked by a visual stimulus on the electronic display. The client device identifies the object in the gaze region with a stimulus frequency matching a frequency derived from the potential signal, and executes instructions relating to the object.

Abstract: Embodiments relate to a brain computer interface (BCI) including a light source subsystem, an interface transmitting light from the light source subsystem to a body region of a user, and a detector subsystem coupled to the interface and configured to receive light signals from the body region of the user. The light source subsystem, the interface, and the detector subsystem are coupled to other electronics providing power, computing functionality, and/or other functionality. The BCI is designed to be worn at a head region of a user and to generate optical signals that can be used to characterize brain activity of the user, where decoded brain activity can be used as inputs to control other systems and/or electronic content provided to the user.

Abstract: A brain computer interface system includes a wearable interface, an eye tracking device, and a client device for determining what object a user is looking at on an electronic display. The client device determines a region on the electronic display based on an estimated user gaze direction received from the eye tracking device. For each virtual object in the gaze region, the client device displays a visual stimulus with a unique frequency. The client device receives from the wearable interface an electrical potential signal measured at the user's brain and evoked by a visual stimulus on the electronic display. The client device identifies the object in the gaze region with a stimulus frequency matching a frequency derived from the potential signal, and executes instructions relating to the object.

Abstract: A brain computer interface system interprets an individual's neural signals to predict specific phonemes, words, or sentences, thereby enabling the individual to communicate with others through unspoken methods. Specifically, a brain computer interface system captures neural signals from an individual at mesoscopic resolutions using optical neuroimaging techniques. The system applies the captured neural signals to multiple predictive models that have been trained on neural signals captured from previous individuals. The predictive models output predictions as to a phoneme or word that corresponds to the captured neural signals. Therefore, the individual can communicate through the brain computer interface system by only providing neural signals without using verbal, expressive, or physical means.