Abstract: Disclosed is a system for sensor-based training intervention. The system includes one or more electroencephalogram (EEG) sensors for retrieving brain signals of a subject, one or more sensors for retrieving eye tracking data of one or both eyes of the subject, and one or more processors. The one or more processors are configured to model a joint state space of the brain signals and eye tacking data by combining the brain signals and eye tracking data into combined data using sequential Bayesian fusion, and measure a visuospatial attention indicator from combined data.

Abstract: Disclosed is a method for classifying signals for movement control of an autonomous vehicle. The method includes receiving first data comprising concurrently recorded electroencephalogram (EEG) and electromyogram (EMG) signals from a user. The data is used to train a classification model based on the recorded signals. The method further involves receiving second data comprising further EEG and EMG signals recorded from the user, comparing the second data to the classification model to determine a user movement represented by the second data, and determining a control signal for controlling the autonomous vehicle, based on the user movement. This may be used in a further method for identifying an event.

Abstract: A cognitive training method has a step of obtaining sensor data of a subject during a memory exercise which in turn determines whether the sensor data includes predetermined information indicative of cognitive functions used for remembering. The step of advancing the memory exercise is carried out when it is determined that the sensor data includes predetermined information indicative of cognitive functions used for remembering. The step of calculating an objective cognitive assessment of the subject is carried out when the memory exercise is completed and cognitive training is measured at least partially in response to the advancing of the memory exercise. The fact that an objective cognitive assessment is calculated provides a method of using an autodidactic cognitive training device.

Abstract: A method of training a classification algorithm for a Brain Computer Interface (BCI). The method includes the steps of: dividing a Electroencephalography (EEG) signal into a plurality of time segments; for each time segment, dividing a corresponding EEG signal portion into a plurality of frequency bands; for each frequency band, computing a spatial filtering projection matrix based on a Common Spatial Pattern (CSP) algorithm and a corresponding feature, and computing mutual information of each corresponding feature with respect to one or more motor imagery classes; for each time segment, summing the mutual information of all the corresponding features with respect to the respective classes; and selecting the corresponding features of the time segment with a maximum sum of mutual information for one class for training classifiers of the classification algorithm.

Abstract: A method of calibrating a motor imagery detection module and a system for motor rehabilitation are provided. The method comprises acquiring Electroencephalography (EEG) data from a subject; selecting classification features from the EEG data; wherein the feature selection comprises modelling an idle state ?n of the subject by M sub-classes ?j, j=1, . . . , M.

Abstract: A device and method for generating a representation of a subject's attention level. The device measures brain signals from the subject; extracts temporal features from the brain signals; classifies the extracted temporal features using a classifier to give a score X1; extracts spectral-spatial features from the brain signals; selects spectral-spatial features containing discriminative information between concentration and non-concentration states from the set of extracted spectral-spatial features; classifies the selected spectral-spatial features using a classifier to give a score X2; combines the scores X1 and X2 to give a single score; and presents the score to the subject.

Abstract: A cognitive training method has a step of obtaining sensor data of a subject during a memory exercise which in turns determining whether the sensor data includes predetermined information indicative of cognitive functions used for remembering. The step of advancing the memory exercise is carried out when it is determined that the sensor data includes predetermined information indicative of cognitive functions used for remembering. The step of calculating an objective cognitive assessment of the subject when the memory exercise is completed and a cognitive training is measured at least partially in response to the advancing the memory exercise. The fact that an objective cognitive assessment is calculated provides a method of using an autodidactic cognitive training device.

Abstract: A method of calibrating a motor imagery detection module and a system for motor rehabilitation are provided. The method comprises acquiring Electroencephalography (EEG) data from a subject; selecting classification features from the EEG data; wherein the feature selection comprises modelling an idle state ?n of the subject by M sub-classes ?j, j=1, . . . , M.

Abstract: A system and method for brain-computer interface (BCI) based interaction. The method comprising the steps of: acquiring a person's EEG signal; processing the EEG signal to determine a motor imagery of the person; detecting a movement of the person using a detection device; and providing feedback to the person based on the motor imagery, the movement, or both; wherein providing the feedback comprises activating a stimulation element of the detection device for providing a stimulus to the person. The system comprising: means for acquiring a person's EEG signal; means for processing the EEG signal to determine a motor imagery of the person; means for detecting a movement of the person using a detection device; and means for providing feedback to the person based on the motor imagery, the movement, or both; wherein the means for providing the feedback comprises a stimulation element of the detection device for providing a stimulus to the person.

Abstract: A device and method for generating a representation of a subject's attention level. The device comprises means for measuring brain signals from the subject; means for extracting temporal features from the brain signals; means for classifying the extracted temporal features using a classifier to give a score x1; means for extracting spectral-spatial features from the brain signals; means for selecting spectral-spatial features containing discriminative information between concentration and non-concentration states from the set of extracted spectral-spatial features; means for classifying the selected spectral-spatial features using a classifier to give a score x2; means for combining the scores x1 and x2 to give a single score; and means for presenting said score to the subject.