30 results about "Seizure activity" patented technology

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.

Controlled release of pharmaceutical agents using microspheres or other controlled release systems are used to treat disease state characterized by aberrant electrical activity in excitable tissue. For the treatment of epilepsy, agents useful in the treatment of epilepsy may be delivered to the patient at the site of seizure origin to control seizure activity in a time release manner. The inventive system may also be useful in the treatment of cardiac arrhythmias and pre-term labor. Particularly useful pharmaceutical compositions comprising a site 1 sodium channel blocker are also provided.

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. An embodiment of the invention monitors the quality of physiological signals, and may be able to compensate for signals of low signal quality. A further embodiment of the invention includes detection of seizure activity following the delivery of therapy.

The system and method for detecting seizure activity combines signal traces from both an electroencephalogram (EEG) and an electrocardiogram (ECG) in order to detect and predict a seizure event in a patient. Determination of a seizure classification of the combination is based on Dempster-Shafer Theory (DST) to calculate a combined probability belief. Prior to combination, classification of the EEG and ECG data is performed by linear discriminant analysis (LDA) or naïve Bayesian classification to provide a seizure event classification or a non-seizure event classification.

The c-Jun NH₂-terminal kinase (JNK) group of MAP kinases are activated by exposure of cells to environmental stress. The role of JNK in the brain was examined by targeted disruption of the gene that encodes the neuronal isoform JNK3. It was found that JNK3 is required for the normal response to seizure activity. Methods of screening for molecules and compounds that decrease JNK3 expression or activity are described. Such molecules or compounds are useful for treating disorders involving excitotoxicity such as seizure disorders, Alzheimer's disease, Huntington disease, Parkinson's disease, and ischaemia.

Method, apparatus and computer program product for monitoring seizure activity in brain are disclosed. At least one parameter set sequence is derived from brain wave signal data obtained from a subject, wherein each parameter set sequence comprises sequential parameter sets and each parameter set comprises values for at least two signal parameters, the values being derived from the brain wave signal data. A path formed by each of the at least one parameter set sequence in a parameter space is determined, thereby to obtain at least one path. The parameter space is defined by the at least two signal parameters. At least one evolution indicator is calculated, each evolution indicator quantifying the evolution occurred in respective path formed in a given time period in the parameter space. The at least one evolution indicator is then employed to produce an indication of seizure activity in the brain wave signal data.

Deep Brain Stimulation (DBS) is taking off and will be part of the main treatment for brain diseases such as movement disorders, epilepsy, psychiatric diseases and many others. There is a need for more sophisticated devices that can do more in one penetration, not just stimulate. Once there is a probe in the brain, it is used for multiple passive measurements, without harming the brain further. It provides better understanding the brain and real time closed loop improved treatment. An apparatus and method are disclosed, which allow simultaneous monitoring of multiple parameters inside the human brain, such as: pH, temperature, pressure, seizure activity (EEG), degree of metabolism, oxygen tension in the brain, degree of excitotoxicity and others. The ability to measure those parameters during treatment and stimulation procedures makes the difference between success and failure of the patient.

This invention provides compounds, compositions and methods for treating Autism Spectrum Disorders (ASD) using glycyl-2-methylprolyl-glutamic acid (G-2-MePE) and analogs thereof. Autism Spectrum Disorders include Autism, Autistic Disorder, Asperger Syndrome, Childhood Disintegrative Disorder, Pervasive Developmental Disorder-Not Otherwise Specified (PDD-NOS), Fragile X Syndrome, and Rett Syndrome. Compositions containing compounds include water-soluble formulations, water-in-oil micro-emulsions, water-in-oil coarse emulsions, water-in-oil liquid crystals, nanocapsules, tablets, and orally administered gels. The compounds and compositions of this invention can be administered intravenously, intraventricularly, parenterally, or orally, and can be effective in treating neurodegeneration, promoting neurological function, treating seizure activity and other symptoms of ASD, and can prolong life in animals including human beings having Autism Spectrum Disorders.

This invention provides compounds, compositions and methods for treating Autism Spectrum Disorders (ASD) using glycyl-2-methylprolyl-glutamic acid (G-2-MePE) and analogs thereof. Autism Spectrum Disorders include Autism, Autistic Disorder Asperger Syndrome, Childhood Disintegrative Disorder, Pervasive Developmental Disorder—Not Otherwise Specified (PDD-NOS), Fragile X Syndrome, and Rett Syndrome. Compositions containing compounds include water-soluble formulations, water-in-oil micro-emulsions, water-in-oil coarse emulsions, water-in-oil liquid crystals, nanocapsules, tablets, and orally administered gels. The compounds and compositions of this invention can be administered intravenously, intraventricularly, parenterally, or orally, and can be effective in treating neurodegeneration, promoting neurological function, treating seizure activity and other symptoms of ASD, and can prolong life in animals including human beings having Autism Spectrum Disorders.

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. An embodiment of the invention monitors the quality of physiological signals, and may be able to compensate for signals of low signal quality. A further embodiment of the invention includes detection of seizure activity following the delivery of therapy.

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. An embodiment of the invention monitors the quality of physiological signals, and may be able to compensate for signals of low signal quality. A further embodiment of the invention includes detection of seizure activity following the delivery of therapy.

Method, apparatus and computer program product for monitoring seizure activity in brain are disclosed. At least one parameter set time series is derived from brain wave signal data obtained from a subject, wherein each parameter set sequence comprises sequential parameter sets and each parameter set comprises values for at least two signal parameters, the values being derived from the brain wave signal data. In order to reduce susceptibility to inter-subject variations and to enhance adaptability to each recording, past EEG signal data of the subject is used to determine an envelope object that encompasses the parameter points that sequential parameter sets derived from the past signal data form in a parameter space. A reference point is also determined, whose location in the parameter space depends on the past signal data. At least one new parameter point is then obtained from the subject and an evolution indicator set is determined. By examining whether the evolution indicator set fulfills predetermined location and direction criteria in relation to the envelope object and the reference point, seizure activity may be detected. The envelope object and the reference point are conditionally updated for on-line measurement.

A method of estimating the probability of a seizure in a subject, the method comprising: receiving historical data associated with epileptic events experienced by the subject over a first time period,the historical data comprising physiological data associated with each epileptic event and a time at which each epileptic event occurred; generating a temporal probability model of future epileptic events based on the time of each of the epileptic events, the temporal probability model representing a probability of a future seizure occurrence in each of a plurality of time windows; generating a probabilistic model based on the physiological data associated with each epileptic event; weighting the probabilistic model based on the temporal probability model to generate a weighted probabilisticmodel of future seizure activity; and outputting an estimate of seizure probability in the subject using the weighted probabilistic model.

A method for reducing epileptic seizures in a subject includes the steps of providing a vibration motor coupled to a controller configured to control vibratory motion of the vibration motor, positioning at least one vibration motor on a limb of the subject, and generating a vibratory stimulation signal configured to stimulate proprioceptive nerves in the limb to trigger kinesthetic cues that stimulate nerves in cerebellar and pontine areas of the brain to suppress seizure activity.

The method for determining an onset time and an excitability of a brain region that is not observed as recruited or not recruited in a seizure activity of an epileptic patient brain includes: providing a dynamical model of a propagation of an epileptic seizure in the brain networks; providing a statistical model which defines the probability of generating sets of observations of the state of the brain networks by said dynamical model; training the dynamical model of the propagation of an epileptic seizure using the statistical model and the data set of observations of the training cohort; and inverting the trained dynamical model and inferring the onset time and excitability of a third region from the onset time that is observed for the first and second regions using the statistical model.