Abstract: Systems and methods for enhancing the accuracy of classifying a measurement by providing an artificial class. Seizure prediction systems may employ a classification system including an artificial class and a user interface for signaling uncertainty in classification when a measurement is classified in the artificial class.

Abstract: Methods and systems for monitoring a subject's brain activity are provided. A method includes receiving EEG signals from the subject using a plurality of EEG electrodes positioned extracranially; and recording EEG signals using a recording circuit coupled to said EEG electrodes and contained in an enclosure implanted beneath the subject's scalp and above the subject's caldarium.

Abstract: Systems and methods for neuromonitoring a subject are described. The system may include a stimulation assembly including a pulse generator that generates one or more stimulus waveforms; an electrode array coupled to the stimulation assembly and configured to deliver a stimulation signal to nervous system of the subject; a sensing assembly adapted to acquire a signal from a subject indicative of the subject's brain activity; a power supply configured to supply power to the stimulation assembly and the sensing assembly; and a timing controller programmed to control the use of the power supply by the stimulation assembly and the sensing assembly, said timing controller being programmed to control the time the sensing assembly is powered to acquire the signal to be substantially different than the time the stimulation assembly is powered to stimulate the subject.

Abstract: Methods of classifying a subject's condition are described. The method includes: receiving measured signals from the subject; processing the measured signals using a computing device to identify a class associated with an identified condition of the subject; introducing an artificial class, the artificial class being associated with an unknown condition of the subject; classifying a feature vector from the subject into the identified class or the artificial class; and generating a signal in response to classifying the feature vector. The measured signals from the subject may include at least one signal extracted from brain activity of the subject.

Abstract: The present invention relates to neurological systems and methods of use which acquire physiological signals from a subject and stimulate the subject. The system is adapted to control the timing at which the system acquires the physiological signals from the subject and the timing of the stimulation signal to reduce the amount of stimulation induced artifact that is acquired by the system.

Abstract: Methods of classifying a subject's condition are described. The method includes: receiving measured signals from the subject; processing the measured signals using a computing device to identify a class associated with an identified condition of the subject; introducing an artificial class, the artificial class being associated with an unknown condition of the subject; classifying a feature vector from the subject into the identified class or the artificial class; and generating a signal in response to classifying the feature vector. The measured signals from the subject may include at least one signal extracted from brain activity of the subject.

Abstract: Systems and methods for enhancing the accuracy of classifying a measurement by providing an artificial class. Seizure prediction systems may employ a classification system including an artificial class and a user interface for signaling uncertainty in classification when a measurement is classified in the artificial class.

Abstract: A neurological control system for modulating activity of any component or structure comprising the entirety or portion of the nervous system, or any structure interfaced thereto, generally referred to herein as a “nervous system component.” The neurological control system generates neural modulation signals delivered to a nervous system component through one or more neuromodulators to control neurological state and prevent neurological signs and symptoms. Such treatment parameters may be derived from a neural response to previously delivered neural modulation signals sensed by one or more sensors, each configured to sense a particular characteristic indicative of a neurological or psychiatric condition.

Abstract: Systems and methods for enhancing the accuracy of classifying a measurement by providing an artificial class. Seizure prediction systems may employ a classification system including an artificial class and a user interface for signaling uncertainty in classification when a measurement is classified in the artificial class.

Abstract: A neurological control system for modulating activity of any component or structure comprising the entirety or portion of the nervous system, or any structure interfaced thereto, generally referred to herein as a “nervous system component.” The neurological control system generates neural modulation signals delivered to a nervous system component through one or more neuromodulators to control neurological state and prevent neurological signs and symptoms. Such treatment parameters may be derived from a neural response to previously delivered neural modulation signals sensed by one or more sensors, each configured to sense a particular characteristic indicative of a neurological or psychiatric condition.

Abstract: Systems and methods for enhancing the accuracy of classifying a measurement by providing an artificial class. Seizure prediction systems may employ a classification system including an artificial class and a user interface for signaling uncertainty in classification when a measurement is classified in the artificial class.

Abstract: The present invention provides methods and systems for modulating a patient's neurological disease state. In one embodiment, the system comprises one or more sensors that sense at least one signal that comprise a characteristic that is indicative of a neurological disease state. A signal processing assembly is in communication with the one or more sensors and processes the at least one signal to estimate the neurological disease state and to generate a therapy to the patient that is based at least in part on the estimated neurological disease state. A treatment assembly is in communication with the signal processing assembly and delivers the therapy to a nervous system component of the patient.

Abstract: Systems and methods for enhancing the accuracy of classifying a measurement by providing an artificial class. Seizure prediction systems may employ a classification system including an artificial class and a user interface for signaling uncertainty in classification when a measurement is classified in the artificial class.

Abstract: The present invention provides methods and systems for modulating a patient's neurological disease state. In one embodiment, the system comprises one or more sensors that sense at least one signal that comprise a characteristic that is indicative of a neurological disease state. A signal processing assembly is in communication with the one or more sensors and processes the at least one signal to estimate the neurological disease state and to generate a therapy to the patient that is based at least in part on the estimated neurological disease state. A treatment assembly is in communication with the signal processing assembly and delivers the therapy to a nervous system component of the patient.

Abstract: Systems and methods for enhancing the accuracy of classifying a measurement by providing an artificial class. Seizure prediction systems may employ a classification system including an artificial class and a user interface for signaling uncertainty in classification when a measurement is classified in the artificial class.

Abstract: The present invention provides systems and methods for ambulatory, long term monitoring of a physiological signal from a patient. At least a portion of the systems of the present invention may be implanted within the patient in a minimally invasive manner. In preferred embodiments, brain activity signals are sampled from the patient and are transmitted to a handheld patient communication device for further processing.

Abstract: A neurological control system for modulating activity of any component or structure comprising the entirety or portion of the nervous system, or any structure interfaced thereto, generally referred to herein as a “nervous system component.” The neurological control system generates neural modulation signals delivered to a nervous system component through one or more neuromodulators to control neurological state and prevent neurological signs and symptoms. Such treatment parameters may be derived from a neural response to previously delivered neural modulation signals sensed by one or more sensors, each configured to sense a particular characteristic indicative of a neurological or psychiatric condition.

Abstract: A neurological control system for modulating activity of any component or structure comprising the entirety or portion of the nervous system, or any structure interfaced thereto, generally referred to herein as a “nervous system component.” The neurological control system generates neural modulation signals delivered to a nervous system component through one or more neuromodulators, comprising intracranial (IC) stimulating electrodes and other actuators, in accordance with treatment parameters. Such treatment parameters may be derived from a neural response to previously delivered neural modulation signals sensed by one or more sensors, each configured to sense a particular characteristic indicative of a neurological or psychiatric condition.

Abstract: A neurological control system for modulating activity of any component or structure comprising the entirety or portion of the nervous system, or any structure interfaced thereto, generally referred to herein as a ?nervous system component.? The neurological control system generates neural modulation signals delivered to a nervous system component through one or more neuromodulators, comprising intracranial (IC) stimulating electrodes and other actuators, in accordance with treatment parameters. Such treatment parameters may be derived from a neural response to previously delivered neural modulation signals sensed by one or more sensors, each configured to sense a particular characteristic indicative of a neurological or psychiatric condition.