Abstract: Methods, including a method, comprising selecting a plurality of dependent variables relating to each of a plurality of seizures in a patient; selecting a plurality of independent variables, wherein each independent variable comprises a therapy parameter, a therapy delivery parameter, a temporal factor, an environmental factor, or a patient factor; quantifying at least one relationship between each of at least two dependent variables and each of at least two independent variables; and performing an action in response to said quantifying, selected from reporting said at least one relationship, assessing an efficacy of a therapy, assessing an adverse effect of said therapy, providing a therapy modification recommendation, or adjusting said therapy. A medical device system capable of implementing a method. A non-transitory computer readable program storage medium containing instructions that, when executed by a computer, perform a 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 a method of treating an epileptic seizure in a patient, comprising: detecting said epileptic seizure, based on body data from said patient; and reducing a flow of blood to a brain of said patient in response to said detected seizure; wherein said reducing is effected by: increasing the parasympathetic input to said patient's heart, such as by electrically stimulating a parasympathetic nervous structure, applying cooling energy to a sympathetic nervous structure, or administering a cholinergic or a sympatho-blocking agent to said patient. 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, 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: 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: Methods, systems, and apparatus for assessing a state of an epilepsy disease or a comorbidity thereof are provided. The methods comprise receiving at least one autonomic index, neurologic index, stress marker index, psychiatric index, endocrine index, adverse effect of therapy index, physical fitness index, or quality of life index of a patient; comparing the at least one index to at least one reference value; and assessing a state of an epilepsy disease or a body system of the patient based on the comparison. A computer readable program storage device encoded with instructions that, when executed by a computer, perform the method described above is also provided. A medical device system capable of implementing the method described above is also provided.

Abstract: Methods, systems, and apparatus for assessing a state of an epilepsy disease or a comorbidity thereof are provided. The methods comprise receiving at least one autonomic index, neurologic index, stress marker index, psychiatric index, endocrine index, adverse effect of therapy index, physical fitness index, or quality of life index of a patient; comparing the at least one index to at least one reference value; and assessing a state of an epilepsy disease or a body system of the patient based on the comparison. A computer readable program storage device encoded with instructions that, when executed by a computer, perform the method described above is also provided. A medical device system capable of implementing the method described above is also provided.

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 for detecting epileptic or non-epileptic seizures, comprising: receiving a heart rate of a patient; calculating a percentage change of the heart rate in reference to at least one of the patient's maximal heart rate, reserve heart rate, or a resting heart rate; detecting an epileptic seizure if the percentage increase in the heart rate reaches a threshold value; and taking at least one responsive action selected from issuing a warning, delivering a therapy, determining a seizure severity, or logging at least one of a date and time of occurrence of the seizure, its severity, the type of therapy, or its effect, in response to 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: 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: We report a method comprising receiving a first indication to gather a first biological signal or feature thereof from a patient; gathering the first biological signal or feature thereof; receiving a second indication to stop gathering the first biological signal or feature thereof, wherein the second indication relates to a detection of an end of a brain state change; and stopping gathering the first biological signal or feature thereof. 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 for optimizing the therapeutic efficacy of evoked responses elicited by one or more electrical impulses delivered to a neural structure, comprising: comparing a test evoked response to an evoked response elicited by therapeutically efficacious electrical stimulation; adjusting at least one parameter of the electrical impulses in response to a determination that said test evoked response is not similar to the therapeutic evoked response; determining that the test evoked response resembles the therapeutic evoked response after performing at least one of said adjustments; and saving to memory at least one adjusted parameter that increased the similarity between the test evoked response and the therapeutic evoked response. 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 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 determining and responding in real-time to an increased risk of death relating to a patient with epilepsy is provided. The method includes receiving cardiac data and determining a cardiac index based upon the cardiac data. The method includes determining an increased risk of death associated with epilepsy if the indices are extreme, issuing a warning of the increased risk of death and logging information related to the increased risk of death. Also presented is a second method for determining and responding in real-time to an increased risk of death relating to a patient with epilepsy comprising receiving at least one of arousal data, responsiveness data or awareness data and determining an arousal index, a responsiveness index or an awareness index, where the indices are based on arousal data, responsiveness data or awareness data respectively.

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 a method of automatically titrating an electrical therapy administered to a patient by an implanted medical device to a target dosage, comprising programming the medical device with a programmed electrical therapy comprising a first target value for a first therapy parameter; programming at least one titration parameter for automatically adjusting the first therapy parameter from a first value to the first target value over a titration time period initiating the electrical therapy, wherein the first therapy parameter comprises said first value; and automatically titrating the electrical therapy by making a plurality of adjustments to the value of the first therapy parameter, whereby the first electrical therapy parameter is changed from the first value to the first target value according to a titration function. We also report a medical device system configured to implement 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: 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: A method for determining and responding in real-time to an increased risk of death relating to a patient with epilepsy is provided. The method includes receiving cardiac data and determining a cardiac index based upon the cardiac data. The method includes determining an increased risk of death associated with epilepsy if the indices are extreme, issuing a warning of the increased risk of death and logging information related to the increased risk of death. Also presented is a second method for determining and responding in real-time to an increased risk of death relating to a patient with epilepsy comprising receiving at least one of arousal data, responsiveness data or awareness data and determining an arousal index, a responsiveness index or an awareness index, where the indices are based on arousal data, responsiveness data or awareness data respectively.