Method and systems are disclosed for training state-classifiers for classification of cognitive state. A set of multimodal signals indicating physiological responses of an operator are sampled over a time period. A depiction of operation by the operator during the time period is displayed. In response to user input selecting a cognitive state for a portion of the time period, the one or more state-classifiers are trained. In training the state-classifiers, the set of multimodal signals sampled in the portion of the time period are used as input to the one or more state-classifiers and the selected one of the set of cognitive states is used as a target result to be indicated by the one or more state-classifiers.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method, comprising: sampling a set of multimodal signals indicating physiological responses of an operator over a time period; displaying a depiction of operation in the time period; and in response to user input selecting a cognitive state, from a set of cognitive states, and a portion of the time period, training one or more state-classifiers to map the set of multimodal signals to a set of cognitive states using the set of multimodal signals sampled in the portion of the time period as input to the one or more state-classifiers and the selected one of the set of cognitive states as a target result to be indicated by the one or more state-classifiers. 2. The method of claim 1, further comprising providing a graphical user interface for selecting portions of the time period and selecting respective ones of cognitive states for the selected portions. 3. The method of claim 1, wherein the displaying the depiction of operation in the time period includes displaying a video recording of the operator in the time period. 4. The method of claim 3, wherein the displaying the depiction of operation in the time period further includes displaying respective probabilities that the operator is in each one of the set of cognitive states. 5. The method of claim 1, further comprising, prior to the displaying the depiction of operation in the time period, performing initial training of the one or more state-classifiers to map the set of multimodal signals to the set of cognitive states. 6. The method of claim 5, wherein for each of one or more of the set of cognitive states, the initial training includes: presenting stimuli configured to induce the cognitive state in the operator for a respective portion of the time period; sampling the set of multimodal signals in the portion; and mapping the one or more of the physiological responses indicated by the multimodal signals in the portion to the cognitive state. 7. The method of claim 6, wherein capturing of the set of multimodal signals includes: converting one or more analog signals to digital signals; aligning the digital signals in time; and removing noise artifacts from one or more of the digital signals. 8. The method of claim 6, wherein, presenting stimuli includes simulating an operation scenario in a simulator, presenting a video depicting operation by another operator in the operation scenario, or a combination thereof. 9. The method of claim 1, further comprising: sampling the set of multimodal signals in a second time period; determining respective probabilities of the operator being in the set of cognitive states using the sampled set of multimodal signals as input to the one or more state-classifiers; and in response to the determined respective probabilities satisfying a set of criteria specified in a settings file stored in a data storage, performing an action specified for the set of criteria in the settings file. 10. The method of claim 1, further comprising generating the multimodal signals using a combination of electroencephalogram (EEG), event-related potentials (ERP), functional near infrared spectroscopy (fNIRS), electrocardiogram (EKG), heart rate, blood pressure, respiration rate, skin temperature, galvanic skin response (GSR), electromyogram (EMG), voice stress analysis, and/or facial feature sensors. 11. A system, comprising: a set of sensors configured to provide a set of multimodal signals indicating physiological responses of an operator to stimuli in a first time period; a processing circuit configured to train one or more state-classifiers to map the set of multimodal signals to a set of cognitive states; and a display configured to depict operation by the operator in the first time period; and wherein the processing circuit is further configured to, in response to user input selecting one of the set of cognitive states and a portion of the first time period, perform the training of the one or more state-classifiers using the set of multimodal signals sampled in the portion of the time period as input to the one or more state-classifiers and the selected one of the set of cognitive states as a target result to be mapped to by the one or more state-classifiers. 12. The system of claim 11, further comprising a second display configured to provide the stimuli configured to induce a set of cognitive states in the operator. 13. The system of claim 11, further comprising a circuit coupled to the set of sensors and configured to sample outputs of the set of sensors to produce the set of multimodal signals. 14. The system of claim 11, wherein the display is configured to provide a graphical user interface for selection of the portion of the time period and selection of the one of the set of cognitive states. 15. The system of claim 11, further comprising a data storage circuit coupled to the processing circuit and configured to store the one or more state-classifiers. 16. The system of claim 15, further comprising a second processing circuit coupled to the data storage and configured to determine a cognitive state of an operator using the one or more state-classifiers and the set of multimodal signals as input to the one or more state-classifiers. 17. The system of claim 16, further comprising a third processing circuit configured to perform an action specified in a settings file, stored in the data storage, in response to the determined cognitive state of the operator satisfying a set of criteria specified in the settings file. 18. The system of claim 17, wherein the third processing circuit is configured to: determine a level of confidence in the cognitive state determined by second processing circuit; and in response to the level of confidence being less than a threshold level specified in the set of criteria, cause the first-mentioned processing circuit to retrain the one or more state-classifiers. 19. The system of claim 17, wherein in response to a first user input, the third processing circuit is configured to trigger automated feedback to the operator in further response to the determined cognitive state of the operator being a performance limiting cognitive state; and in response to a second user input, the third processing circuit is configured to disable triggering of the automated feedback to the operator. 20. The system of claim 11, wherein the processing circuit is further configured to perform unsupervised training of the one or more state-classifiers.