Abstract: A system and method for analyzing and logging changes in brain state of a subject for administering therapy to the subject based on the at least one cardiac signal wherein the system and method comprises the steps of receiving at least one cardiac signal of the subject into a processor, analyzing the cardiac signal to detect at least one cardiac signal change indicative of a brain state change, and logging at least one characteristic of the detected signal change or brain state change.

Abstract: Disclosed are methods and systems for treating epilepsy by stimulating a main trunk of a vagus nerve, or a left vagus nerve, when the patient has had no seizure or a seizure that is not characterized by cardiac changes such as an increase in heart rate, and stimulating a cardiac branch of a vagus nerve, or a right vagus nerve, when the patient has had a seizure characterized by cardiac changes such as a heart rate increase.

Abstract: Disclosed are methods and systems for treating epilepsy by stimulating a main trunk of a vagus nerve, or a left vagus nerve, when the patient has had no seizure or a seizure that is not characterized by cardiac changes such as an increase in heart rate, and stimulating a cardiac branch of a vagus nerve, or a right vagus nerve, when the patient has had a seizure characterized by cardiac changes such as a heart rate increase.

Abstract: Methods, systems, and apparatus for detecting and/or validating a detection of a state change by matching the shape of one or more of an cardiac data series, a heart rate variability data series, or at least a portion of a heart beat complex, derived from cardiac data, to an appropriate template.

Abstract: A method, comprising receiving a time series of patient body signal, determining first and second sliding time windows for the time series; applying an autoregression algorithm, comprising: applying an autoregression analysis to each of the first and second windows, yielding autoregression coefficients and a residual variance for each window; estimating a parameter vector for each window based on the autoregression coefficients and residual variances; and determining a difference between the parameter vectors; and determining seizure onset and seizure termination based on the difference between the parameter vectors. A non-transitory computer readable program storage unit encoded with instructions that, when executed by a computer, perform the method.

Abstract: A method for identifying changes in an epilepsy patient's disease state, comprising: receiving at least one body data stream; determining at least one body index from the at least one body data stream; detecting a plurality of seizure events from the at least one body index; determining at least one seizure metric value for each seizure event; performing a first classification analysis of the plurality of seizure events from the at least one seizure metric value; detecting at least one additional seizure event from the at least one determined index; determining at least one seizure metric value for each additional seizure event, performing a second classification analysis of the plurality of seizure events and the at least one additional seizure event based upon the at least one seizure metric value; comparing the results of the first classification analysis and the second classification analysis; and performing a further action.

Abstract: We report method of detecting a pathological body state of a patient, comprising receiving a body signal of the patient; determining a body index from said body signal; determining an activity level of said patient; determining a value range for said body index for said patient, based at least in part on said activity level; comparing said body index to said value range; and detecting a pathological state when said body index is outside said value range. We also report a medical device system configured to implement the method. We also report a non-transitory computer readable program storage unit encoded with instructions that, when executed by a computer, perform the method.

Abstract: A system and method for detecting seizures in a patient are disclosed. The method includes measuring at least one signal associated with the patient over a first time period, and calculating a first slope having a rate of change in a first signal of the at least one signal over the first time period. The first signal is a heart rate. The method also includes determining a difference between the first slope and a reference slope, as well as detecting an epileptic seizure based at least upon the difference between the first slope and the reference slope. Furthermore, the method includes quantifying the epileptic seizure by calculating a severity of the seizure. The severity is the product of a seizure duration and a seizure intensity.

Abstract: A system and method for analyzing and logging changes in brain state of a subject for administering therapy to the subject based on the at least one cardiac signal wherein the system and method comprises the steps of receiving at least one cardiac signal of the subject into a processor, analyzing the cardiac signal to detect at least one cardiac signal change indicative of a brain state change, and logging at least one characteristic of the detected signal change or the brain state change.

Abstract: Methods, systems, and apparatus for detecting and/or validating a detection of a state change by matching the shape of one or more of an cardiac data series, a heart rate variability data series, or at least a portion of a heart beat complex, derived from cardiac data, to an appropriate template.

Abstract: Disclosed are methods and medical device systems for automated delivery of therapies for pain and determination of need for and safety of treatment. In one embodiment, such a medical device system may comprise a sensor configured to sense at least one body signal from a patient; and a medical device configured to receive a first sensed body signal from the sensor determine a patient pain index based at least in part on said first sensed body signal; determine whether said patient pain index is above at least a first pain index threshold; determine a safety index based at least in part on a second sensed body signal; select a pain treatment regimen based on at least one of said safety index and or a determination that said pain index is above said first pain index threshold; and deliver said pain treatment regimen.

Abstract: A method, comprising receiving at least one of a signal relating to a first cardiac activity and a signal relating to a first body movement from a patient; triggering at least one of a test of the patient's responsiveness, awareness, a second cardiac activity, a second body movement, a spectral analysis test of the second cardiac activity, and a spectral analysis test of the second body movement, based on at least one of the signal relating to the first cardiac activity and the signal relating to the first body movement; determining an occurrence of an epileptic event based at least in part on said one or more triggered tests; and performing a further action in response to said determination of said occurrence of said epileptic event. Further methods allow classification of epileptic events. Apparatus and systems capable of implementing the method.

Abstract: A method for assessment, optimization and logging of the effects of a therapy for a medical condition, including (a) receiving into a signal processor input signals indicative of the subject's brain activity; (b) characterizing the spatio-temporal behavior of the brain activity using the signals; (c) delivering a therapy to a target tissue of the subject; (d) characterizing the spatio-temporal effect of the therapy on the brain activity; (e) in response to the characterizing, optimizing at least one parameter of the therapy if the brain activity has not been satisfactorily modified and/or has been adversely modified by the therapy; (f) characterizing the spatio-temporal effect of the at least one optimized parameter; and (g) logging to memory the at least one optimized parameter. A computer readable program storage unit encoded with instructions that, when executed by a computer, performs the method.

Abstract: We report a method of determining an occurrence of an epileptic convulsive seizure in a patient, comprising: receiving body data from a patient during a first time period, determining a work level relating to said first time period at least based partially upon said body data; determining whether said work level exceeds an extreme work level threshold; performing a responsive action, in response to a determination that said work level exceeds said extreme work level threshold. We also report a medical device system configured to implement the method. We also report a non-transitory computer readable program storage unit encoded with instructions that, when executed by a computer, perform the method.

Abstract: We report a method of a method for detecting an epileptic seizure, comprising providing a first body signal reference value; determining a current body signal value from a time series of body signals; comparing the current body signal value and the first reference value; determining a work level of the patient; determining whether the current body signal value comprises an ictal component, based on the work level and the comparing; issuing a detection of an epileptic seizure in response to the determination that the current body signal value comprises the ictal component; and taking at least one further action (e.g. warning, delivering a therapy, etc.), based on the detection. We also report a medical device system configured to implement the method. We also report a non-transitory computer readable program storage unit encoded with instructions that, when executed by a computer, perform the method.

Abstract: We report method of detecting a pathological body state of a patient, comprising receiving a body signal of the patient; determining a body index from said body signal; determining an activity level of said patient; determining a value range for said body index for said patient, based at least in part on said activity level; comparing said body index to said value range; and detecting a pathological state when said body index is outside said value range. We also report a medical device system configured to implement the method. We also report a non-transitory computer readable program storage unit encoded with instructions that, when executed by a computer, perform the method.

Abstract: A method for identifying changes in an epilepsy patient's disease state, comprising: receiving at least one body data stream; determining at least one body index from the at least one body data stream; detecting a plurality of seizure events from the at least one body index; determining at least one seizure metric value for each seizure event; performing a first classification analysis of the plurality of seizure events from the at least one seizure metric value; detecting at least one additional seizure event from the at least one determined index; determining at least one seizure metric value for each additional seizure event, performing a second classification analysis of the plurality of seizure events and the at least one additional seizure event based upon the at least one seizure metric value; comparing the results of the first classification analysis and the second classification analysis; and performing a further action.

Abstract: A method, comprising detecting, in at least a first brain region of a patient, an electrical activity relating to an epileptic activity; determining a first regularity index of said electrical activity; and applying at least one first electrical stimulation to at least one neural target of said patient for treating said epileptic event, in response to said first regularity index being within a first range. A non-transitive, computer-readable storage device for storing instructions that, when executed by a processor, perform the method. A medical device system suitable for use in the method.

Abstract: Methods, systems, and apparatus for detecting and/or validating a detection of a state change by matching the shape of one or more of an cardiac data series, a heart rate variability data series, or at least a portion of a heart beat complex, derived from cardiac data, to an appropriate template.

Abstract: We report a method of determining an occurrence of an epileptic convulsive seizure in a patient, comprising: receiving body data from a patient during a first time period, determining a work level relating to said first time period at least based partially upon said body data; determining whether said work level exceeds an extreme work level threshold; performing a responsive action, in response to a determination that said work level exceeds said extreme work level threshold. We also report a medical device system configured to implement the method. We also report a non-transitory computer readable program storage unit encoded with instructions that, when executed by a computer, perform the method.