Abstract: An extended Reality (XR) system is provided that monitors neurological signals to determine an engagement of a user with a real-world environment. The XR system continuously monitors neurological signals of a user through a processor operating in a low-power mode. The XR system generates an engagement signal by analyzing endogenous brain patterns in the neurological signals. In response to the engagement signal, the XR system activates environmental sensors to capture real-world environment data. The XR system generates contextual data from the captured environment data and determines XR content to provide to the user based on the contextual data. The XR system selectively activates XR capabilities to display the determined XR content.

Abstract: An adaptive calibration method in a brain-computer interface is disclosed. The method is used to reliably associate a neural signal to an object whose attendance by a user elicited that neural signal. A visual stimulus overlaying one or more objects is provided, at least a portion of the visual stimulus having a characteristic modulation. The brain computer interface measures neural response to objects viewed by a user. The neural response to the visual stimulus is correlated to the modulation, the correlation being stronger when attention is concentrated upon the visual stimulus. Weights are applied to the resulting model of neural responses for the user based on the determined correlations. Both neural signal model weighting and displayed object display modulation are adapted so as to improve the certainty of the association of neural signals with the objects that evoked those signals.

Abstract: An adaptive calibration method in a brain-computer interface is disclosed. The method is used to reliably associate a neural signal to an object whose attendance by a user elicited that neural signal. A visual stimulus overlaying one or more objects is provided, at least a portion of the visual stimulus having a characteristic modulation. The brain computer interface measures neural response to objects viewed by a user. The neural response to the visual stimulus is correlated to the modulation, the correlation being stronger when attention is concentrated upon the visual stimulus. Weights are applied to the resulting model of neural responses for the user based on the determined correlations. Both neural signal model weighting and displayed object display modulation are adapted so as to improve the certainty of the association of neural signals with the objects that evoked those signals.

Abstract: An adaptive calibration method in a brain-computer interface is disclosed. The method is used to reliably associate a neural signal to an object whose attendance by a user elicited that neural signal. A visual stimulus overlaying one or more objects is provided, at least a portion of the visual stimulus having a characteristic modulation. The brain computer interface measures neural response to objects viewed by a user. The neural response to the visual stimulus is correlated to the modulation, the correlation being stronger when attention is concentrated upon the visual stimulus. Weights are applied to the resulting model of neural responses for the user based on the determined correlations. Both neural signal model weighting and displayed object display modulation are adapted so as to improve the certainty of the association of neural signals with the objects that evoked those signals.

Abstract: An adaptive calibration method in a brain-computer interface is disclosed. The method is used to reliably associate a neural signal to an object whose attendance by a user elicited that neural signal. A visual stimulus overlaying one or more objects is provided, at least a portion of the visual stimulus having a characteristic modulation. The brain computer interface measures neural response to objects viewed by a user. The neural response to the visual stimulus is correlated to the modulation, the correlation being stronger when attention is concentrated upon the visual stimulus. Weights are applied to the resulting model of neural responses for the user based on the determined correlations. Both neural signal model weighting and displayed object display modulation are adapted so as to improve the certainty of the association of neural signals with the objects that evoked those signals.

Abstract: An adaptive calibration method in a brain-computer interface is disclosed. The method is used to reliably associate a neural signal to an object whose attendance by a user elicited that neural signal. A visual stimulus overlaying one or more objects is provided, at least a portion of the visual stimulus having a characteristic modulation. The brain computer interface measures neural response to objects viewed by a user. The neural response to the visual stimulus is correlated to the modulation, the correlation being stronger when attention is concentrated upon the visual stimulus. Weights are applied to the resulting model of neural responses for the user based on the determined correlations. Both neural signal model weighting and displayed object display modulation are adapted so as to improve the certainty of the association of neural signals with the objects that evoked those signals.