Abstract: A method and system for determining the state of a patients brain under anesthesia. The present invention recognizes that anesthesia compounds induce different signatures in physiological characteristics of the patient under anesthesia and aids interpretation of physiological characteristics and signatures therein based on a selected anesthesia compound. The present invention aids the monitoring and/or interpreting of the physiological characteristics to a state of the patient's brain.

Abstract: A system and method for identifying sleep states of a subject are provided. In some aspects, the method includes acquiring physiological data from a subject over a sleep period using sensors positioned about the subject, and assembling the physiological data into time-series datasets. The method also includes selecting a temporal window in which signals associated with the time-series datasets are substantially stationary, computing a time bandwidth product based on a selected spectral resolution and the selected temporal window, and determining a number of tapers using the computed time bandwidth product. The method further includes computing a spectrogram using the determined number of tapers and the time-series datasets, analyzing the spectrogram to identify signatures of sleep in the subject, and generating, using the identified signatures, a report indicative of sleep states of the subject.

Abstract: A system and method is provided for tracking sleep dynamics in a subject. In one aspect, a method includes acquiring physiological data using sensors positioned about the subject, and acquiring behavioral data using input provided by the subject. The method also includes generating a statistical model of wakefulness by combining information obtained from the acquired physiological data and behavior data, and estimating a probability indicative of a degree to which the subject is awake at each point in time during sleep onset using the statistical model. The method further includes generating a report indicative of sleep onset in the subject.

Abstract: A system and method are provided for monitoring subject behavior during sleep onset. In some aspects, a system includes one or more sensors configured to acquire behavioral data from a subject using input provided during sleep onset. The system also includes a processor programmed to at least assemble a time-series of behavioral responses using the behavioral data acquired using the one or more sensors, and estimate an instantaneous probability of response using the time-series of behavioral responses. The processor is also programmed to generate a statistical model of wakefulness using the instantaneous probability of response, and estimate, using the model, a probability indicative of a degree to which the subject is awake at each point in time during the sleep onset process. The processor is further configured to generate a report indicative of sleep onset in the subject. The system also includes an output for displaying the report.

Abstract: Systems and methods for tracking dynamic structure in physiological data are provided. In some aspects, the method includes providing physiological data, including electroencephalogram (“EEG”) data, acquired from a subject and assembling a time-frequency representation of signals from the physiological data. The method also includes generating a dynamic model of at least one non-stationary spectral feature, such as at least one non-stationary spectral peak, using the time-frequency representation and a user indication, and applying a dynamic model of at least one non-stationary spectral feature in a parameter estimation algorithm to compute concurrent estimates of spectral parameters describing the at least one non-stationary spectral feature. The method also includes tracking the spectral parameters of the at least one spectral feature over time.

Abstract: Systems and methods for tracking dynamic structure in physiological data are provided. In some aspects, the method includes providing physiological data, including electroencephalogram (“EEG”) data, acquired from a subject and assembling a time-frequency representation of signals from the physiological data. The method also includes generating a dynamic model of at least one non-stationary spectral feature, such as at least one non-stationary spectral peak, using the time-frequency representation and a user indication, and applying a dynamic model of at least one non-stationary spectral feature in a parameter estimation algorithm to compute concurrent estimates of spectral parameters describing the at least one non-stationary spectral feature. The method also includes tracking the spectral parameters of the at least one spectral feature over time.

Abstract: A method and system for determining the state of a patients brain under anesthesia. The present invention recognizes that anesthesia compounds induce different signatures in physiological characteristics of the patient under anesthesia and aids interpretation of physiological characteristics and signatures therein based on a selected anesthesia compound. The present invention aids the monitoring and/or interpreting of the physiological characteristics to a state of the patient's brain.

Abstract: A system and method for monitoring a subject are provided. In some aspects, a provided electroencephalogram (“EEG”) system includes an electrode patch assembly configured to attach to a subject's skin, the assembly including a flexible circuit layer having electrical leads configured to acquire EEG signals from the subject, the flexible circuit layer having a shielding layer configured to substantially reduce a coupling of the plurality of electrical leads to external sources of noise, and a holder to which the flexible circuit layer is secured. The system also includes an electronics module removably coupled to the holder and configured to engage electrical contacts on the flexible circuit layer, the module including a front-end module configured to perform an active noise cancellation process on the acquired EEG signals and generate digitized data using noise cancelled signals, and a processor configured to transmit the digitized data using a wireless communication module.

Abstract: A system and method for identifying sleep states of a subject are provided. In some aspects, the method includes acquiring physiological data from a subject over a sleep period using sensors positioned about the subject, and assembling the physiological data into time-series datasets. The method also includes selecting a temporal window in which signals associated with the time-series datasets are substantially stationary, computing a time bandwidth product based on a selected spectral resolution and the selected temporal window, and determining a number of tapers using the computed time bandwidth product. The method further includes computing a spectrogram using the determined number of tapers and the time-series datasets, analyzing the spectrogram to identify signatures of sleep in the subject, and generating, using the identified signatures, a report indicative of sleep states of the subject.

Abstract: A system and method are provided for monitoring subject behavior during sleep onset. In some aspects, a system includes one or more sensors configured to acquire behavioral data from a subject using input provided during sleep onset. The system also includes a processor programmed to at least assemble a time-series of behavioral responses using the behavioral data acquired using the one or more sensors, and estimate an instantaneous probability of response using the time-series of behavioral responses. The processor is also programmed to generate a statistical model of wakefulness using the instantaneous probability of response, and estimate, using the model, a probability indicative of a degree to which the subject is awake at each point in time during the sleep onset process. The processor is further configured to generate a report indicative of sleep onset in the subject. The system also includes an output for displaying the report.

Abstract: A system and method is provided for tracking sleep dynamics in a subject. In one aspect, a method includes acquiring physiological data using sensors positioned about the subject, and acquiring behavioral data using input provided by the subject. The method also includes generating a statistical model of wakefulness by combining information obtained from the acquired physiological data and behavior data, and estimating a probability indicative of a degree to which the subject is awake at each point in time during sleep onset using the statistical model. The method further includes generating a report indicative of sleep onset in the subject.

Abstract: Systems and methods for identifying physiological states of a patient are provided. In one aspect, a method includes receiving a time-series of physiological data, and generating a multinomial regression model that includes regression parameters representing signatures of multiple neural states. The method also includes estimating probabilities for each of the neural states by applying the regression model to the time-series of physiological data, and identifying one of a current and future brain state of the patient using the estimated probabilities. The method further includes generating a report indicating a physiological state of the patient.

Abstract: Systems and methods for tracking dynamic structure in physiological data are provided. In some aspects, the method includes providing physiological data, including electroencephalogram (“EEG”) data, acquired from a subject and assembling a time-frequency representation of signals from the physiological data. The method also includes generating a dynamic model of at least one non-stationary spectral feature, such as at least one non-stationary spectral peak, using the time-frequency representation and a user indication, and applying a dynamic model of at least one non-stationary spectral feature in a parameter estimation algorithm to compute concurrent estimates of spectral parameters describing the at least one non-stationary spectral feature. The method also includes tracking the spectral parameters of the at least one spectral feature over time.

Abstract: A system and method for monitoring a patient experiencing an administration of at least one anesthetic drug. In certain embodiments, the method includes arranging sensors configured to acquire physiological data from a patient and reviewing the physiological data from the sensors and an indication received from an input. The method also includes assembling the physiological data into sets of time-series data and determining, from the sets of time-series data, a first set of signals in a first frequency range and a second set of signals in a second frequency range, the first set of signals describing a transient oscillation signature and the second set of signals describing a target wave signature. The method further includes identifying, using the transient oscillation and target wave signatures, a degree of sedation consistent with the administration of the anesthetic drug, and generating a report indicative of the degree of sedation induced by the drug.

Abstract: A method and system for determining the state of a patients brain under anesthesia. The present invention recognizes that anesthesia compounds induce different signatures in physiological characteristics of the patient under anesthesia and aids interpretation of physiological characteristics and signatures therein based on a selected anesthesia compound. The present invention aids the monitoring and/or interpreting of the physiological characteristics to a state of the patient's brain.