The present invention relates to a system and method of emotion recognition. An emotion recognition system may utilize a Valence-Arousal factor along with training data. The training data may exist as emotions assigned to actual measurements of user inputs. The actual measurements of user inputs may be assigned to a plurality of points on the Valence-Arousal model. A user input acquisition device may be used to collect actual measurements of user inputs. A processor may utilize an algorithm to assign user emotions based on the training data. A user may provide feedback on the assigned user emotions, and the training data may be updated based on the user feedback, depending on whether the user feedback is considered an outlier to the training data.

The invention relates to a novel method for scoring sleep stages of a mammal subject, comprising extracting features from polysomnography data using the continuous wavelet transform; grouping the extracted features into clusters that are assigned to different sleep stages; and scoring the sleep stages based on the clusters. The method does not require prior visual knowledge of sleep stages nor supervised training.

One embodiment of the user authentication method using brainwave signal according to imagined speech includes extracting and storing characteristic information of a first brainwave signal generated by an imagined speech of a first user based on preset imagined speech induction information provided to the first user by the user authentication apparatus, and determining whether a second user matches the first user by extracting characteristic information of a second brainwave signal generated by an imagined speech of the second user, based on preset imagined speech induction information provided to the second user, comparing the characteristic information of the first brainwave signal with the characteristic information of the second brainwave signal stored according to the extracting and storing, and analyzing a result of the comparing by the user authentication apparatus.

One embodiment of the user authentication method using brainwave signal according to imagined speech includes extracting and storing characteristic information of a first brainwave signal generated by an imagined speech of a first user based on preset imagined speech induction information provided to the first user by the user authentication apparatus, and determining whether a second user matches the first user by extracting characteristic information of a second brainwave signal generated by an imagined speech of the second user, based on preset imagined speech induction information provided to the second user, comparing the characteristic information of the first brainwave signal with the characteristic information of the second brainwave signal stored according to the extracting and storing, and analyzing a result of the comparing by the user authentication apparatus.

Embodiments of a system for controlling an object using brainwaves are disclosed. The system includes a set of EEG electrodes configured to be positioned on a head of a user and to collect EEG signals. The system further includes one or more computer readable storage mediums storing a framework configured to execute an extensible architecture through which EEG signals are interpreted for control of the object. The framework includes an EEG device plugin associated with the set of EEG electrodes and configured to extract the EEG signals from the set of EEG electrodes. The framework also includes an interpreter plugin configured to convert the EEG signals extracted by the EEG device plugin into a command. Further, the framework includes an object control plugin configured to access the command through an extension point of the interpreter plugin and to execute the command to control the object.

A method for estimating neural activation arising from stimulation by a stimulation system includes identifying different neural elements stimulated by the stimulation; obtaining a neural response signal resulting from the stimulation by the stimulation system; and decomposing the neural response signal to estimate neural activation of each of the different neural elements.

A method for estimating neural activation arising from stimulation by a stimulation system includes identifying different neural elements stimulated by the stimulation; obtaining a neural response signal resulting from the stimulation by the stimulation system; and decomposing the neural response signal to estimate neural activation of each of the different neural elements.

A system and method for automatically assessing pilot readiness via a plurality of biometric sensors includes continuously receiving biometric data including vision-based data; the biometric vision-based data is compared to a task specific set of movements and facial expressions as defined by known anchor points. A deviation is calculated based on the vision-based data and task specific set of movements and expressions, and the deviation is compared to an acceptable threshold for pilot readiness. Other biometric data may be included to refine the readiness assessment.

Apparatus and methods for monitoring electrical activity within the brain of a person (“brainwaves”) employing electrodes or other sensors placed proximate to portions of the body below the head to develop raw signals without physically touching the body and penetrating hair and clothing. Additionally, apparatus and methods for monitoring electrical activity within the brain of a person (“brainwaves”) employing non-contacting sensors placed proximate to portions of the head to develop raw signals. The raw signals are filtered to produce analysis signals including frequency components relevant to brain electrical activity while attenuating unrelated frequency components. The apparatus and methods can be used for biofeedback-based attention training, human performance training, gaming, biometrics, cognitive state detection, and relaxation training. Either wired or wireless signal connections are made to electronic circuitry, typically including a digital computer, for performing signal processing and analysis functions.

Apparatus and methods for monitoring electrical activity within the brain of a person (“brainwaves”) employing electrodes or other sensors placed proximate to portions of the body below the head to develop raw signals without physically touching the body and penetrating hair and clothing. Additionally, apparatus and methods for monitoring electrical activity within the brain of a person (“brainwaves”) employing non-contacting sensors placed proximate to portions of the head to develop raw signals. The raw signals are filtered to produce analysis signals including frequency components relevant to brain electrical activity while attenuating unrelated frequency components. The apparatus and methods can be used for biofeedback-based attention training, human performance training, gaming, biometrics, cognitive state detection, and relaxation training. Either wired or wireless signal connections are made to electronic circuitry, typically including a digital computer, for performing signal processing and analysis functions.