The General Hospital Corporation

Massachusetts Institute of Technology

Patrick L Purdon

Emery Neal Brown

Michael J Prerau

Pavitra Krishnaswamy

Brandon M Westover

ShiNung Ching

Eran A Mukamel

Laura D Lewis

Uri Tzvi Eden

Giorgio Bonmassar

Oluwaseun Johnson-Akeju

Matti Hamalainen

Gabriel Obregon-Henao

Behtash Babadi

Jacob A Donoghue

Kathleen J Koenigs

Aylin Cimenser

Oluwaseun Akeju

Systems and methods are provided for monitoring a subject, and particularly, for inferring an underlying brain state present in absence of current conditions. In some aspects, a method for monitoring the subject is provided including steps of receiving physiological feedback from at least one sensor configured to acquire physiological information from locations associated with a subject's brain, assembling a set of time-series data using the received physiological feedback, and identifying portions of the set of time-series data that indicate a burst suppression state. The method also includes identifying a burst characteristic profile associated with a burst pattern determined from the identified portions, and comparing the burst characteristic against a reference set of burst profiles. The method further includes determining, based on the comparison, a likelihood of a brain state of the subject underlying the burst suppression state, and generating a report indicative of the likelihood of the determined brain state.

Systems and methods to infer brain state during burst suppression

Systems and methods for monitoring a subject under, or suspected to be under, the influence of one or more drugs are provided. In one aspect, a method comprises controlling one or more sensors of a monitoring device to acquire physiological signals from a subject suspected to be under the influence of one or more drugs, and assembling a set of physiological data using the acquired physiological signals. The method also includes generating, using a processor of the monitoring device, physiological markers characteristic of the influence of the one or more drugs by analyzing the set of physiological data, and correlating the physiological markers with a drug profile characterizing the one or more drugs affecting the subject. The method further includes proving to a user a report indicating the drug profile characterizing the one or more drugs affecting the subject.

Systems and methods for monitoring a subject under the influence of drugs

A system and method for monitoring a patient suspected of experiencing a state of unconsciousness are provided. In certain aspects, the method includes assembling physiological data, obtained from a plurality of sensors placed on a subject, into sets of time-series data, separating, from the sets of time-series data, a plurality of electroencephalogram signals, and determining, from the plurality of electroencephalogram signals, at least one of frequency information and amplitude information. The method can also include identifying, using the at least one of the frequency information and the amplitude information, spatiotemporal signatures indicative of a likelihood of arousing the patient to consciousness by applying an external stimulus and generating a report indicating the likelihood of arousing the patient to consciousness by applying the external stimulus.

Systems and methods for predicting arousal to consciousness during general anesthesia and sedation

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.

System and method for tracking brain states during administration of anesthesia

The present invention generally relates to compositions comprising anesthesia-reversing agents which facilitate or increase the time of awakening or reverse the effects of general anesthesia-induced unconsciousness. In some embodiments, the anesthesia reversing agent can be selected from any or a combination of methylphenidate (MPH), amphetamine, modafinil, amantadine, caffeine, or analogues or derivatives thereof. In some embodiments, compositions comprising at least one or more anesthesia-reversing agents can be used to facilitate awakening from anesthesia without or decreasing occurrence of delirium, and can be used in methods to treat or prevent the symptoms associated with emergence delirium, as well as treat a subject oversedated with general an esthesia. The invention also relates to methods for administering these compositions comprising anesthesia-reversing agents to subjects and for use.

Reversal of general anesthesia by administration of methylphenidate, amphetamine, modafinil, amantadine, and/or caffeine

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.

System and method for spectral characterization of sleep

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.

System and method for tracking sleep dynamics using behavioral and physiological information

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.

System and method for monitoring behavior during sleep onset

A method for non-invasively resolving electrophysiological activity in sub-cortical structures located deep in the brain by comparing amplitude-insensitive M/EEG field patterns arising from activity in subcortical and cortical sources under physiologically relevant sparse constraints is disclosed. The method includes a sparse inverse solution for M/EEG subcortical source modeling. Specifically, the method employs a subspace-pursuit algorithm rooted in compressive sampling theory, performs a hierarchical search for sparse subcortical and cortical sources underlying the measurement, and estimates millisecond-scale currents in these sources to explain the data. The method can be used to recover thalamic and brainstem contributions to non-invasive M/EEG data, and to enable non-invasive study of fast timescale dynamical and network phenomena involving widespread regions across the human brain.

Deep brain source imaging with M/EEG and anatomical MRI

A system and method for monitoring and/or controlling a state of consciousness of a subject experiencing anesthesia are provided. In some aspects, the system includes a plurality of sensors placed about the subject and configured to acquire electroencephalogram ('EEG'} data therefrom while the subject is receiving anesthesia, and at least one processor configured to receive the EEG data from the plurality of sensors, and perform a phase-amplitude coupling analysis using the received EEG data to determine a phase-amplitude frequency distribution. The at least one processor is also configured to identify a state of consciousness of the subject using the determined phase-amplitude frequency distribution, and generate a report indicative of the state of consciousness of the subject.

System and method for characterizing brain states during general anesthesia and sedation using phase-amplitude modulation

Systems and a method for reducing periodic artifacts in an electrophysiologic signal are provided. The method includes receiving a time-series electrophysiologic signal acquired from a subject and providing a regression model that defines an interference signal caused by periodic artifacts using a harmonic representation. The method also includes applying the regression model using the time-series electrophysiologic signal to define a cost function and performing an iterative optimization process to estimate regression parameters that minimize the cost function. The method further includes determining, using the regression parameters, the interference signal, and generating a corrected time-series electrophysiologic signal by reducing the interference signal.

Removing eletrophysicologic artifacts from a magnetic resonance imaging system

Systems and method for age-compensated monitoring of a patient experiencing administration of at least one drug having anesthetic properties are provided. In one embodiment, a system includes a plurality of sensors configured to acquire physiological data from the patient and at least one processor configured to receive the physiological data from the plurality of sensors, and determine, from the physiological data, signal markers indicative of an apparent or likely patient age. The at least one processor is also configured to at least one of scale and regulate the physiological data using at least the apparent patient age to create age-compensated data, and generate a report including the age-compensated data.

Systems and methods for improved brain monitoring during general anesthesia and sedation

Methods, systems and arrangements are provided for obtaining electroencephalograph ('EEG') EEG signals from a patient e.g., during a concurrent EEG/MRI examination of the patient. The methods, systems and arrangements include a cap made of conductive inks with sensor positions for attaching a plurality of sensors to the patient's head. The sensors can include electrodes as well as motion sensors for improving EEG signal quality and MRI image quality in the presence of motion noise and other artifacts within the MRI environment. The electrodes may be composed of conductive inks, and can be used in high magnetic fields due to a weak interaction with the RF fields generated by the MRI scanner. The exemplary methods, systems and arrangements can achieve lower SAR and lower temperature increase, as compared to conventional electrodes.

Apparatuses and methods for electrophysiological signal delivery and recording during MRI

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.

Growing community of inventors

Cambridge, MA, United States of America

Patrick L Purdon