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: 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: 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: 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: 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 system and method for finding a Pareto-optimal solution for automated detection, warning, and abatement of a medical condition based on a cost of event intervention in a patient is disclosed. The method includes acquiring at least one biological signal from the patient via at least one sensor of a medical device, detecting an abnormal biological event based on changes in the biological signal, and delivering at least one of a therapy and a warning. The method includes logging a set of parameters including at least one of a detection parameter, a therapy parameter, and a therapy modality. The method includes finding an optimal set of parameters that yield a Pareto-optimal cost of event intervention by iteratively determining at least one metric over a time window, determining the cost of event intervention, and modifying at least one parameter, until the cost of event intervention meets an acceptability criteria.

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: 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: A system and method for finding a Pareto-optimal solution for automated detection, warning, and abatement of a medical condition based on a cost of event intervention in a patient is disclosed. The method includes acquiring at least one biological signal from the patient via at least one sensor of a medical device, detecting an abnormal biological event based on changes in the biological signal, and delivering at least one of a therapy and a warning. The method includes logging a set of parameters including at least one of a detection parameter, a therapy parameter, and a therapy modality. The method includes identifying an optimal set of parameters that yield a Pareto-optimal cost of event intervention by iteratively determining at least one metric over a time window, determining the cost of event intervention, and modifying at least one parameter, until the cost of event intervention meets an acceptability criteria.

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, 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: 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: 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, 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: 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: 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 of distinguishing a non-epileptic seizure from an epileptic seizure in a patient, comprising: detecting a seizure in a patient based on at least one first body signal of the patient selected from an autonomic signal, a neurologic signal, a metabolic signal, an endocrine signal, and a tissue stress marker signal; analyzing at least one second body signal of the patient selected from an autonomic signal, a neurologic signal, a metabolic signal, an endocrine signal, and a tissue stress marker signal; determining, based on the analyzing, at least a first classification index comprising at least one of an epileptic seizure index and a non-epileptic seizure index; and classifying the seizure as one of a non-epileptic seizure or an epileptic seizure based on the at least a first classification index. A medical device system capable of implementing the method. A computer-readable device for storing data that, when executed, perform the method.