An apparatus for providing information about a user's brain resources, the apparatus comprising a user interface, at least sensor interface circuitry and processing circuitry coupled to the sensor interface circuitry, wherein, in a calibration mode, the sensor interface circuitry is configured to: receive first sensor data from an electroencephalography sensor, the first sensor data being indicative of an electroencephalogram of the user; and receive second sensor data from a physiological sensor, the second sensor data being indicative of a physiological property of the user, wherein, in the calibration mode, the processing circuitry is configured to train a brain-physiological model for the user based on the first sensor data and the second sensor data, wherein the sensor interface circuitry is further configured to receive the second sensor data in an operation mode, wherein, in the operation mode, the processing circuitry is configured to determine the information about the user's brain resources by processing the second sensor data with the trained brain-physiological model, wherein, for determining the information about the user's brain resources, the processing circuitry is configured to not process data of the electroencephalography sensor with the trained brain-physiological model, characterized in that in the operation mode: the user interface is further configured to: output a questionnaire regarding a physiological and/or cognitive status of the user as subjectively perceived by the user; and receive a user feedback to the questionnaire, and the processing circuitry is further configured to: train the brain-physiological model based on the user feedback to the questionnaire; determine a divergence between the user feedback to the questionnaire and the determined information about the user's brain resources; and if the divergence is above a threshold level, initiate a re-calibration process for the brain-physiological model. wherein, in a calibration mode, the sensor interface circuitry is configured to: receive first sensor data from an electroencephalography sensor, the first sensor data being indicative of an electroencephalogram of the user; and receive second sensor data from a physiological sensor, the second sensor data being indicative of a physiological property of the user, receive first sensor data from an electroencephalography sensor, the first sensor data being indicative of an electroencephalogram of the user; and receive second sensor data from a physiological sensor, the second sensor data being indicative of a physiological property of the user, wherein, in the calibration mode, the processing circuitry is configured to train a brain-physiological model for the user based on the first sensor data and the second sensor data, wherein the sensor interface circuitry is further configured to receive the second sensor data in an operation mode, wherein, in the operation mode, the processing circuitry is configured to determine the information about the user's brain resources by processing the second sensor data with the trained brain-physiological model, wherein, for determining the information about the user's brain resources, the processing circuitry is configured to not process data of the electroencephalography sensor with the trained brain-physiological model, characterized in that in the operation mode: the user interface is further configured to: output a questionnaire regarding a physiological and/or cognitive status of the user as subjectively perceived by the user; and receive a user feedback to the questionnaire, and output a questionnaire regarding a physiological and/or cognitive status of the user as subjectively perceived by the user; and receive a user feedback to the questionnaire, and the processing circuitry is further configured to: train the brain-physiological model based on the user feedback to the questionnaire; determine a divergence between the user feedback to the questionnaire and the determined information about the user's brain resources; and if the divergence is above a threshold level, initiate a re-calibration process for the brain-physiological model. train the brain-physiological model based on the user feedback to the questionnaire; determine a divergence between the user feedback to the questionnaire and the determined information about the user's brain resources; and if the divergence is above a threshold level, initiate a re-calibration process for the brain-physiological model.