Abstract: A method and system for detecting a probability of psychogenic non-epileptic seizures using a portable battery powered device placed on the body of a patient and a device for manually logging detected seizures within a time period. The device may, advantageously, have a seizure detection algorithm which automatically records seizures detected within that time period. The two sets of data may then be transferred to a another device where the logged time stamps are matched to the recorded time stamps for determining if the detected seizure is a generalized tonic-clonic seizure (GTCS) or might be a psychogenic nonepileptic seizure (PNES). This provides a cheap and simple method for registering a probability of PNES by using a seizure detection device having an EMG-sensor or an accelerometer.

Abstract: A system and method for detecting and analyzing the characteristics of seizures, such as tonic-clonic seizures, comprising at least one processor unit capable of recording a signal from a sensor unit, one or more analysis modules configured to analyze the recorded signal, one or more evaluation modules configured to evaluate the output signals from the analysis modules. A first analysis module is configured to analyze the recorded signal within a first frequency band, and a second analysis module is configured to analyze the recorded signal within a second frequency band, and the evaluation module is configured to calculate the ratio between the two output signals from the analysis modules. The system includes a seizure detection module configured to detect a seizure and a time-point extraction module configured to determine at least one starting point and an end point of the seizure.

Abstract: A method and system for detecting the onset of seizures comprising a measuring unit having one or more sensors for detecting the electromyographic signal of one or more muscles of the user. The sensors are connected to a pre-processing module comprising a high-pass filter which filters out noise and motion artefacts related to normal muscle activities. The preprocessing module is connected to a feature extraction module comprising a threshold detector which counts the number of crossings with a hysteresis within a predetermined time window. The feature extraction module is connected to a classification module which compares the extracted features to a first and second threshold and generates an event signal if the extracted features are above the first and second threshold.

Abstract: An apparatus and a method for monitoring muscle activity are provided. The apparatus comprises a sensor for detecting the generated electromyographic signals and processing means. The processing means generates an event signal if the electromyographic signal exceeds a predetermined power content within a predetermined time window. The event signal triggers an event, which may be an alarm. The apparatus further comprises communication means for transmitting the detected electromyographic signals from the sensor to the processing means. The means comprises the steps of detecting and evaluating the electromyographic signals. Furthermore, the method comprises generating an event signal and triggering an event by the event signal.

Abstract: The invention relates to a system and a method for the prediction of epileptic seizures by continuous measurement of at least one signal on the body of a user. A sensor unit measures the heart rate continuously and is connected to a processor unit. The processor unit comprises a verification unit, which stores those measurements that comprise verifiable heartbeats or heart rates in a database. An analysis unit in the processor analyzes the verified measurements to determine whether a preictal phase is present or not. The processor comprises a summation unit, which continuously determines the value of an indication signal on the basis of the signal from the analysis unit. The signal indicates the probability of an imminent epileptic seizure. The value of the indication signal may be determined on the basis of at least two values of the signal from the analysis unit. An alarm unit connected to the processor unit generates one or more alarms, if the indication signal exceeds one or more alarm levels.

Abstract: An apparatus and a method for monitoring muscle activity are provided. The apparatus comprises a sensor for detecting the generated electromyographic signals and processing means. The processing means generates an event signal if the electromyographic signal exceeds a predetermined power content within a predetermined time window. The event signal triggers an event, which may be an alarm. The apparatus further comprises communication means for transmitting the detected electromyographic signals from the sensor to the processing means. The means comprises the steps of detecting and evaluating the electromyographic signals. Furthermore, the method comprises generating an event signal and triggering an event by the event signal.