41 results about "Seizure disorder" patented technology

Treatment of hyperinsulinemic hypoglycemia comprises administration of an effective amount of a glucagon-like peptide-1 receptor antagonist (GLP1RA) alone or in combination with an amylinomimetic agent or any anti-gastric emptying agent. Patients suffering from hyperinsulinemic hypoglycemia after bariatric surgery experience particular benefit, as there is no current method effective for their treatment. Prevention or reduction of acute adverse effects of postprandial hypoglycemia, such as palpitations, tremor, weakness, sweating, confusion, fatigue, blurred vision, seizures, or loss of consciousness, and prevention of chronic adverse effects of hyperinsulinemic hypoglycemia, such as cognitive impairment, can be achieved by treatment with GLP1RA.

A system including one or more electronic devices calculates the likelihood of the user of the system experiencing a health event, such as a seizure. In some examples, the system collects data including environmental data and / or physiological data and uses the data to calculate the likelihood of the user of the system experiencing the health event. In some examples, in response to calculating that the likelihood of the user experiencing the health event exceeds a predetermined threshold, the system generates an alert.

The present invention concerns a pharmaceutical composition, advantageously a ready-to-use liquid composition or dry powder for reconstitution, comprising: Cenobamate or a salt, hydrate or solvate thereof, wherein the pharmaceutical composition for administration is preferably a suspension for oral administration, a kit of parts for the accurate dosing and administration of the pharmaceutical composition. Further the present composition having at least one surface modifying agent controlling the solid state of Cenobamate in suspension; and a method for the treatment of partial seizures in a human patient comprising administration of a therapeutically effective amount of the pharmaceutical composition.

The invention discloses an epileptic seizure detection system based on a multi-dimensional hypergraph fusion network, which comprises a multi-modal data collector, a signal preprocessor, a feature extractor, a multi-dimensional hypergraph builder, a hypergraph feature extractor, a feature fusion device, a classifier and a time sequence prediction corrector, the multi-dimensional hypergraph constructor constructs three hypergraph structures, namely an intra-modal hypergraph, an inter-modal hypergraph and a time sequence hypergraph; the feature fusion device integrates the features extracted by the three hypergraphs to generate a comprehensive feature vector; the classifier classifies the fusion features through a two-layer feedforward neural network, and outputs probability prediction of epileptic seizure; the time sequence prediction corrector applies a majority voting smoothing filter to carry out post-processing on a classification result, isolated misclassification is eliminated, and the time sequence consistency of prediction is enhanced. The invention provides an innovative multi-dimensional hypergraph fusion network, and the robustness and accuracy of epileptic seizure detection are remarkably improved by simultaneously modeling high-order relationships in modals, between modals and time sequence dimensions.

Implementations described and claimed herein provide systems and methods for a cloud-based seizure management platform for personalized management of seizures while providing assured connectedness across multiple stakeholders. The systems and methods address the needs of a patient in the area of seizure management, through such functionalities as seizure detection, seizure histories and other health-related data management, stakeholder connectedness, tachyphylaxis detection, drug titration guidance, and / or treatment aggressiveness management. The system provides for access for multiple parties, including allowing neurologists and / or caregivers to monitor progression of neurological conditions on a continuous basis while at home or otherwise remote from the patient. The unique methodology of the seizure management system includes wearable technologies coupled with artificial intelligence, machine-learning algorithms, and data modeling techniques to enable personalization of care.

Methods, system and apparatus for identifying an extreme epileptic state / event in a patient are provided. In one aspect, at least two seizure events are identified. At least one inter-seizure interval (ISI) value related to the at least two seizure events are determined. The ISI value is compared to at least one reference value. An occurrence of an extreme seizure event is determined based upon the comparison of the determined ISI value to the at least one reference value. In another aspect, a first seizure event is detected. At least one body index affected by the first seizure event is determined. A second seizure event is detected. An occurrence of an extreme seizure event is determined based at least in part in response to a determination that the second seizure event occurred prior to the body index value returning to a reference value.

To provide methods of correlating a brain signal to intentional and unintentional changes in a brain state.SOLUTION: Disclosed herein are methods of analysis to extract and assess brain data collected from subject animals, including humans, to detect intentional and unintentional brain activity and other unexpected signals. These signals are correlated with higher cognitive brain functions or unintended, potentially adverse events, such as a stroke or seizure, and with translation of those signals into defined trigger events or tasks.SELECTED DRAWING: Figure 6

The present application provides a kind of potassium channel regulator, its preparation method, pharmaceutical composition and application. Specifically provided are compounds as shown in formula V or pharmaceutically acceptable salts thereof. The potassium channel regulator compound of the present application has one or more of the following effect advantages: (1) novel structure; (2) good KCNQ2 / 3 channel opening activity; (3) weak KCNQ4, KCNQ5 opening activity, high KCNQ2 / 3 selectivity; (4) good in vivo efficacy, good protection effect on seizures; (5) low neuro-motor toxicity; (6) high brain-blood ratio; (7) high plasma, brain tissue concentration.

Methods, system and apparatus for identifying an extreme epileptic state / event in a patient are provided. In one aspect, at least two seizure events are identified. At least one inter-seizure interval (ISI) value related to the at least two seizure events are determined. The ISI value is compared to at least one reference value. An occurrence of an extreme seizure event is determined based upon the comparison of the determined ISI value to the at least one reference value. In another aspect, a first seizure event is detected. At least one body index affected by the first seizure event is determined. A second seizure event is detected. An occurrence of an extreme seizure event is determined based at least in part in response to a determination that the second seizure event occurred prior to the body index value returning to a reference value.

The invention relates to an auxiliary body position adjusting device for an epilepsy patient, which comprises a first air bag and an air inflation assembly, the first air bag is provided with an air inflation hole and a deflation hole, the air inflation assembly is communicated with the first air bag through the air inflation hole, the deflation hole is provided with an exhaust valve, the first air bag is worn on the waist of the patient, and the first air bag is arranged on the waist of the patient. The first air bag is flat in a contracted state, the first air bag is ellipsoidal in an expanded state, and the maximum outer convex surface faces the chest and the back of a patient. The invention aims to provide the auxiliary body position adjusting device for the epilepsy patient and the use method of the auxiliary body position adjusting device so as to solve the problem that in the prior art, the body position of the patient is difficult to adjust in time after epileptic seizure under the unattended condition.

The present invention relates to oral films containing an active pharmaceutical ingredient (API) capable of providing seizure relief and one or more film-forming polymers, the use of such films, for example for the acute treatment of ongoing seizures, and methods for preparing such films. The film according to the invention is characterized by a rapid dissolution in the buccal cavity followed by a rapid and high systemic absorption.

Systems and method for seizure detection. A seizure detection device utilizes frequency discrimination, time series features, and machine learning clustering algorithms to distinguish between the EEG signal of those experiencing a seizure compared to those who are not experiencing a seizure.

Methods and apparatus for preventing seizure activity in an environment using a computer vision system deployed within the environment are described. One example method includes detecting a seizure trigger within the environment via one or more camera devices deployed in the environment. At least one user associated with the environment that is susceptible to the seizure trigger is identified. Information associated with the seizure trigger is transmitted to a computing device associated with the at least one user.

The application discloses a pre-ictal prediction method and system based on electrocardiogram and deterministic learning, and the steps are as follows: 1. Preprocessing the electrocardiogram data of pre-ictal and dividing into three normal groups and one symptom group; 2. For the original electrocardiogram signals of different groups, the discrete high-gain observer is used to obtain the electrocardiogram state, and the neural network is constructed according to the deterministic learning theory, the dynamics mode of the electrocardiogram is extracted, and the standardized initial mode library is saved; 3. Based on the dynamic estimator, specific judgment rules and mutation prompt signals are designed, which are used for comparing the differences between the electrocardiogram state of the original electrocardiogram signal and the different electrocardiogram state modes in the mode library, outputting the point-to-point signal change graph, and establishing the test of the mutation prompt signal; 4. The modes in different groups are combined for experiment, and the result difference of different mode selection is analyzed and visualized. The application well depicts the change of the electrocardiogram signal before the seizure, and the accurate time node of the mutation can be obtained.

The invention relates to the technical field of medical education, in particular to a teaching system for rescuing pediatric epilepsy, and the system comprises a pediatric model which is used for simulating the states of different types of epilepsy seizures and physiological parameters in different states; the teaching device comprises a teaching resource library, a teaching display module, an examination and evaluation module and medical equipment; the teaching resource library is used for providing teaching videos of etiology, pathology, diagnosis standards and first-aid processes of the pediatric epilepsy and displaying the teaching videos through the teaching display module; the medical equipment is used for rescue operation of the pediatric epilepsy; the examination and evaluation module is used for providing various examination scenes, scoring the operation process of the trainee and generating an evaluation report, so that various scenes of pediatric epileptic seizure are truly and reliably simulated by providing a teaching system capable of being operated and scored, rescue skills of the trainee are evaluated, and the training efficiency of the trainee is improved. And the diagnosis and first-aid treatment capabilities of the trainee on pediatric epileptic seizure are effectively improved.

A system for seizure monitoring controls a camera to operate under a monitoring mode to continuously record data from a subject. The system establishes one or more baselines associated with the subject while operating the camera under the monitoring mode. The system detects one or more deviations from the one or more baselines during a first time window. The one or more deviations being associated with an onset of seizure. The system adjusts one or more settings of the camera while operating the camera under the monitoring mode. When the one or more deviations from the one or more baselines persist during a second time window, the system adjusts the camera to operate under a seizure mode.

Devices, systems, and techniques are described that utilize a compact system to detect stroke or seizure. For example, a system includes a memory, a plurality of electrodes, and sensing circuitry configured to sense, via at least two electrodes of the plurality of electrodes, electrical signals from a patient and generate physiological information based on the electrical signals. The system can also include processing circuitry configured to receive the physiological information from the sensing circuitry, determine, based on the physiological information, a seizure metric indicative of a seizure state of the patient and a stroke metric indicative of a stroke state of the patient, and store the seizure metric and the stroke metric in the memory. A housing can carry the plurality of electrodes and contain both the sensing circuitry and the processing circuitry.

The invention relates a composition comprising clioquinol and idebenone as active ingredients for use in treating or preventing of a seizure in epilepsy.

The present invention relates to a brain dysfunction and seizure detector monitor and system, and a method of detecting brain dysfunction and / or seizure of a subject. Preferably, the present invention also includes one or more seizure detection algorithms. The analysis method is specifically optimized to amplify abnormal brain activity and minimize normal background activity yielding a seizure index directly related to the current presence of ictal activity in the signal. Additionally, a seizure probability index based on historical values of the aforementioned seizure index, is derived for diagnostic purposes. The seizure probability index quantifies the probability that the patient has exhibited abnormal brain activity since the beginning of the recording. These indexes can be used in the context of emergency and / or clinical situations to assess the status and well-being of a patient's brain, or can be used to automatically administer treatment to stop the seizure before clinical signs appear.

Provided herein are methods and compositions related to treating or preventing seizures. In some aspects, provided herein are methods of treating or preventing seizures in a subject by administering to the subject a composition comprising Parabacteroides and Akkermansia bacteria.

Methods and apparatus for preventing seizure activity in an environment using a computer vision system deployed within the environment are described. One example method includes detecting a seizure trigger within the environment via one or more camera devices deployed in the environment. At least one user associated with the environment that is susceptible to the seizure trigger is identified. Information associated with the seizure trigger is transmitted to a computing device associated with the at least one user.

A method (100) for training an artificial intelligence to detect seizures using a first EEG sensor is provided. The method comprises steps of: receiving (S110) seizure-specific data (20) sensed using a second EEG sensor of a different type than the first EEG sensor; manipulating (S120) the seizure-specific data (20) into primary data (21), which corresponds to the seizure-specific data (20) having been sensed using the first EEG sensor; receiving (S130) secondary data (10) sensed using the first EEG sensor; detecting (S140) seizures in the secondary data (10); separating (S150) the secondary data (10) into active data (11), which comprises the detected seizures, and inactive data (12), which does not comprise the detected seizures; generating (S160) a training set (30) for the artificial intelligence by combining the inactive data (12) and the primary data (21); and training (S170) the artificial intelligence using the training set (30). A method (200) for detecting seizures using a first EEG sensor is further provided.

The present invention discloses a composition comprising not less than 10% w / w of oroxylin A, not less than 10% w / w of baicalein and not less than 2% w / w of chrysin for use reducing the incidence of seizures and in the management of neurotoxicity induced by seizures.

The disclosure includes systems and methods for detecting a seizure in one or more animals. An example system includes a camera configured to capture video data of one or more animals, a trained machine-learning (ML) model configured to determine one or more aspects of a seizure in one or more animals based on the video data, and a controller configured to determine these aspects using the ML model during a given time period based on the video data. Some example devices may also include determining a univariate scale indicative of the one or more aspects of a seizure, determining the presence of a seizure during a given time interval, or determining the likelihood of an animal having a seizure during a given time interval. Methods of training an ML model to detect seizures in one or more animals are also provided.

Blepharometric data (data describing eyelid position as a function of time) is recorded and processed for the purposes of predicting a future risk and / or current occurrence of neurological events such as seizures. For example, in one embodiment, blepharometric data is recorded via infrared reflectance oculography spectacles, and processed in real time thereby to extract a set of blepharometric artifacts. Where those artifacts indicate prolonged spiking in blink calmness (for example, based on spiking in negative inter-event duration, or negative IED), an alert is able to be generated thereby to indicate that the subject is at risk of a seizure in a proximal time period. This provides an opportunity to implement mitigation measures, for example, to reduce the likelihood of the seizure manifesting, and / or to mitigate harm should the seizure occur.

The present invention addresses the problem of providing a novel technique that is very useful for predicting seizures. A program according to the present invention causes a computer to function as an acquiring unit and a predicting unit, wherein: the acquiring unit acquires log information including at least one of behavior information indicating a behavior of a subject, emotion information input on the basis of a subjective opinion of the subject, and seizure information relating to a record of seizures that have occurred in the subject; and the predicting unit predicts seizures associated with the subject's brain activity or mental activity on the basis of the log information.

Disclosed are methods of alleviating or preventing one or more symptoms associated with fragile X syndrome in an individual in need thereof via administration of a therapeutically effective amount of a GABA(A) alpha 2 and / or 3 partial agonist. The one or more symptoms may include impaired functional communication, anxiety, inattention, hyperactivity, sensory reactivity, autonomic nervous system dysregulation, aberrant eye gaze, self-injury, aggression, seizures, EEG abnormalities, including but not limited to, abnormal spectral analysis, event related potentials which may include auditory and visual responses, abnormalities in cortical responses as evoked by transcranial magnetic stimulation including resting and active motor thresholds and abnormal responses in measures of cortical inhibition and excitation, aberrant impaired cognitive function, compromised daily living skills, or a combination thereof.

The present invention relates to the use of cannabidiol (CBD) preparations for use in the treatment of seizures associated with tuberous sclerosis (TSC). [Solution] In particular, the present invention includes the step of administering everolimus in combination with a reduced dose of cannabidiol (CBD). In an alternative embodiment, the present invention relates to the treatment of seizures associated with tuberous sclerosis in everolimus-untreated patients currently treated with CBD. Preferably, the dose of everolimus is reduced by at least 10%.

A system for seizure forecasting is provided. The system comprises a wearable device, and a mobile device. The wearable device includes one or more sensors that are configured to obtain physiological data of a user that describes pre-ictal, ictal and post-ictal and normal phases of the user's seizure related activity. The mobile device includes at least a processor, one or more machine learning models and a memory. The memory is encoded with instructions that, when executed by the at least processor of the system, cause the system to perform operations comprises periodically receiving the physiological data of the user from the wearable device; and analyzing the received physiological data using the machine learning models and forecast upcoming seizures.

Successful generation of seizures or shortening of seizure duration was associated with seizure onset time, while corresponding suppression of afterdischarges with earlier onset times was less effective. To identify targets for intervention, seizure networks originating from afterdischarges in the dorsal and ventral hippocampus were mapped using fMRI or simultaneous fMRI-LFP.