Abstract: A method, computer program, and system for real-time signal analysis providing characterization of temporally-evolving densities and distributions of signal features of arbitrary-type signals in a moving time window by tracking output of order statistic filters (also known as percentile, quantile, or rank-order filters). Given a raw input signal of arbitrary type, origin, or scale, the present invention enables automated quantification and detection of changes in the distribution of any set of quantifiable features of that signal as they occur in time. Furthermore, the present invention's ability to rapidly and accurately detect changes in certain features of an input signal can also enable prediction in cases where the detected changes associated with an increased likelihood of future signal changes.

Abstract: Systems and methods for detecting and/or treating nervous system disorders, such as seizures, are disclosed. Certain embodiments of the invention relate generally to implantable medical devices (IMDs) adapted to detect and treat nervous system disorders in patients with an IMD. Certain embodiments of the invention include detection of seizures based upon comparisons of long-term and short-term representations of physiological signals. Other embodiments include prediction of seizure activity based upon analysis of physiological signal levels. A further embodiment of the invention includes detection of seizure activity following the delivery of therapy.

Abstract: Disclosed are probabilistic approaches to patient evaluation, warning and treatment of a neurological disorder. Disclosed techniques estimate probability distribution functions or cumulative distribution functions, determined by relying on representative historical profiles, comprising information in short and/or long timescales obtained at times that may be intermittent or temporally discontinuous from each other or from other events of interest. The patient may thereby be treated based on the determined probability information.

Abstract: Method and apparatus for detecting possible interference in a neurological signal received from a monitoring element of a medical device system. The monitoring element monitors a condition or a symptom of a nervous system disorder being treated and provides a neurological signal to the medical device system for purposes of providing closed-loop feedback control. The system analyzes various parameters of the received signal by taking instantaneous measurements of data points in moving window and thereby determining whether the signal is of poor quality. If the signal is of determined poor quality, it is removed from consideration in the closed-loop feedback control system until it is determined that the signal quality has sufficiently been restored.

Abstract: Method and apparatus for phase shifting neurological signals received from monitoring elements of a medical device. The medical device comprises a plurality of monitoring elements each receiving a neurological signal. The device processes the neurological signals and identifies a time shift of the neurological signal relative to each other. The neurological signals are then time shifted according to the time shift upon which the signals are utilized to provide closed-loop feedback control of a treatment therapy.

Abstract: A cerebral interface system including a housing mechanism spaced at least partially in a cavity formed in the subject's skull; an attaching mechanism; a fluid-tight sealing mechanism; a control mechanism; a communication mechanism with one or more sensors embedded in the subject's brain connecting the control mechanism to the subject's brain; a power source; an inner wall substantially aligned with an inner surface of the subject's skull; an outer wall which may include an auxiliary portion extending tangentially outwardly from the cavity formed in the subject's skull; a communication link connecting the control mechanism to external apparatus for transmitting or receiving information related to detecting, predicting, controlling, or aborting abnormal brain activity of the subject; and an output mechanism which is activatable by the control mechanism.

Abstract: A method and system for intrinsic timescale decomposition, filtering, and automated analysis of signals of arbitrary origin or timescale including receiving an input signal, determining a baseline segment and a monotonic residual segment with strictly negative minimum and strictly positive maximum between two successive extrema of the input signal, and producing a baseline output signal and a residual output signal. The method and system also includes determining at least one instantaneous frequency estimate from a proper rotation signal, determining a zero-crossing and a local extremum of the proper rotation signal, and applying interpolation thereto to determine an instantaneous frequency estimate thereof.

Abstract: Apparatus and method support the synchronization and calibration of a plurality of clocks in a medical device system that may provide treatment to a patient with a nervous system disorder. The plurality of clocks, which may be located at different components of the medical device system, comprises a first clock and a second clock. The second clock may be synchronized to a first clock by disabling a run mode operation and setting the second clock to a selected time. When a reference time of the first clock approximately equals the selected time, the second clock enables the run mode operation. Additionally, a drift time that is indicative of a time difference between the first clock and the second clock is determined. If the drift time is greater than a predetermined amount, an indication to resynchronize the first and second clocks is provided.

Abstract: Apparatus and method support the synchronization and calibration of a plurality of clocks in a medical device system that may provide treatment to a patient with a nervous system disorder. The plurality of clocks, which may be located at different components of the medical device system, comprises a first clock and a second clock. The second clock may be synchronized to a first clock by disabling a run mode operation and setting the second clock to a selected time. When a reference time of the first clock approximately equals the selected time, the second clock enables the run mode operation. Additionally, a drift time that is indicative of a time difference between the first clock and the second clock is determined. If the drift time is greater than a predetermined amount, an indication to resynchronize the first and second clocks is provided.

Abstract: A system (10) analyzes signals representative of a subject's brain activity in a signal processor (12) for information indicating the subject's current activity state and for predicting a change in the activity state. One preferred embodiment uses a combination of nonlinear filtering methods to perform real-time analysis of the electro-encephalogram (EEG) or electro-corticogram (ECoG) signals from a subject patient for information indicative of or predictive of a seizure, and to complete the needed analysis at least before clinical seizure onset. The preferred system then performs an output task for prevention or abatement of the seizure, or for recording pertinent data.

Abstract: A method, computer program, and system for real-time signal analysis providing characterization of temporally-evolving densities and distributions of signal features of arbitrary-type signals in a moving time window by tracking output of order statistic filters (also known as percentile, quantile, or rank-order filters). Given a raw input signal of arbitrary type, origin, or scale, the present invention enables automated quantification and detection of changes in the distribution of any set of quantifiable features of that signal as they occur in time. Furthermore, the present invention's ability to rapidly and accurately detect changes in certain features of an input signal can also enable prediction in cases where the detected changes associated with an increased likelihood of future signal changes.

Abstract: A cerebral interface system has a housing mechanism configured to be at least partially spaced in a cavity formed in the subject's skull; an attaching mechanism for attaching the housing mechanism to the subject's skull; a sealing mechanism for providing a fluid-tight seal between the housing mechanism and the subject's skull; a control mechanism spaced within the housing mechanism; a communication mechanism with one or more sensors embedded in the subject's brain connecting the control mechanism to the subject's brain; and a power source spaced within the housing mechanism.

Abstract: A system (10) analyzes signals representative of a subject's brain activity in a signal processor (12) for information indicating the subject's current activity state and for predicting a change in the activity state. One preferred embodiment uses a combination of nonlinear filtering methods to perform real-time analysis of the electro-encephalogram (EEG) or electro-corticogram (ECoG) signals from a subject patient for information indicative of or predictive of a seizure, and to complete the needed analysis at least before clinical seizure onset. The preferred system then performs an output task for prevention or abatement of the seizure, or for recording pertinent data.

Abstract: A system (10) analyzes signals representative of a subject's brain activity in a signal processor (12) for information indicating the subject's current activity state and for predicting a change in the activity state. One preferred embodiment uses a combination of nonlinear filtering methods to perform real-time analysis of the electro-encephalogram (EEG) or electro-corticogram (ECoG) signals from a subject patient for information indicative of or predictive of a seizure, and to complete the needed analysis at least before clinical seizure onset. The preferred system then performs an output task for prevention or abatement of the seizure, or for recording pertinent data.