Abstract: Described is a computer system for establishing an electroencephalogram (EEG) model for discriminating between alert and fatigue states. The computer system comprises a receiver module for receiving an alert state segment illustrative of an alert state of at least one subject, and one or more EEG fatigue data segments illustrative of a fatigue state of the at least one subject. The computer system further comprises a segment selector for selecting one of the one or more fatigue data segments and setting it to be an assumed maximum fatigue segment, an EEG classifier trainer for training an EEG classifier by extracting an EEG feature space from the alert state segment and assumed maximum fatigue segment, and a maximum fatigue identifier module for identifying a segment of maximum fatigue by applying the EEG classifier to each of the fatigue data segments.

Abstract: Disclosed is a process for identifying and extracting pain-related electroencephalogram (EEG) signals. The process comprises receiving, from one or more trials, EEG data for each trial; determining a current density for each signal; estimating the current density for a set of neural activity regions of interest, based on the computed current density; and computing at least one spectrum characteristic for each trial based on the estimated current density. Thus mean and variance of changes in the EEG data between EEG data labeled as being indicative of a pain state and EEG data labeled as being indicative of a non-pain state, for each neural activity region of interest can be calculated, and pain-related EEG signals can be identified based on at least one a region of interest at which the variance is below a predetermined threshold.

Abstract: A method for profiling sleep of an individual is provided. The method includes defining a sleep feature space for the individual, measuring a brain wave for the individual during the individual's sleep, and mapping the sleep feature space in response to a comparison of the brain wave and a previous brain wave measurement used to define the sleep feature space. The brain wave may comprise a brain wave spectrum. The sleep feature space may comprise, or be composed of, spectral power and envelope measures. The method also includes modelling the mapped sleep feature space in response to recognized neural network patterns corresponding to each of a plurality of sleep stages derived from recognizing the neural network patterns from the sleep feature space and deriving a sleep profile for the individual from sleep stages determined in response to the modelled mapped sleep feature space and the brain wave of the individual.

Abstract: Described is a computer system for establishing an electroencephalogram (EEG) model for discriminating between alert and fatigue states. The computer system comprises a receiver module for receiving an alert state segment illustrative of an alert state of at least one subject, and one or more EEG fatigue data segments illustrative of a fatigue state of the at least one subject. The computer system further comprises a segment selector for selecting one of the one or more fatigue data segments and setting it to be an assumed maximum fatigue segment, an EEG classifier trainer for training an EEG classifier by extracting an EEG feature space from the alert state segment and assumed maximum fatigue segment, and a maximum fatigue identifier module for identifying a segment of maximum fatigue by applying the EEG classifier to each of the fatigue data segments.

Abstract: A method for ballistocardiography (BCG) and a BCG system ballistocardiography (BCG) system for heart beat determination are provided. The method includes digitizing a plurality of signals received from a corresponding plurality of sensors, estimating a plurality of smoothed cepstra corresponding to each of the plurality of digitized signals in response to a smoothed cepstrum analysis of a digital signal at a reception time of each of the plurality of digitized signals, and estimating a fused cepstrum for the plurality of digitized signals in response to the plurality of smoothed cepstra. The method further includes determining a heart rate in response to the plurality of smoothed cepstra and the fused cepstrum.

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 for profiling sleep of an individual is provided. The method includes defining a sleep feature space for the individual, measuring a brain wave for the individual during the individual's sleep, and mapping the sleep feature space in response to a comparison of the brain wave and a previous brain wave measurement used to define the sleep feature space. The brain wave may comprise a brain wave spectrum. The sleep feature space may comprise, or be composed of, spectral power and envelope measures. The method also includes modelling the mapped sleep feature space in response to recognized neural network patterns corresponding to each of a plurality of sleep stages derived from recognizing the neural network patterns from the sleep feature space and deriving a sleep profile for the individual from sleep stages determined in response to the modelled mapped sleep feature space and the brain wave of the individual.

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 cloning the file system of a window web operating system by using a bitmap file includes the steps of (i) storing file data from a source partition in a bitmap file, (ii) compressing the data of the source partition into an image file and cloning the image file to an object disk, (iii) decompressing the compressed bitmap file of the source partition in an object partition in the object disk, enabling decompressed data to be restored to the object partition, and (iv) modifying the bitmap file subject to the size of the object partition and the physical parameters of the object disk.