The present invention provides objective methods of diagnosis and behavioural treatments of neurological disorders such as autism spectral disorders and Parkinson's disease.

An integrated circuit chip and method for EEG monitoring. In one embodiment, the integrated circuit chip includes an Analog Front End cell in communication with an electrode and a Classification Processor wherein a signal received from the electrode is processed by the Classification Engine cell and designated as seizure or non-seizure. In another embodiment, the Analog Front End cell includes an amplifier cell in communication with an electrode; and an ASPU cell in communication with the amplifier cell. In yet another embodiment, the Classification Processor includes a DBE Channel Controller cell; a Feature Extraction Engine Processor cell, and a Classification Engine cell in communication with the Feature Extraction Engine Processor cells and the DBE Channel Controller cell.

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.

An external data retrieval apparatus receives a low resolution version of a physiological signal from an active implantable medical device and determines if the physiological signal represents a clinically significant event. The apparatus provides an indication of such determination to the implantable medical device. If the physiological signal does represent a clinically significant event, the apparatus receives a full download of the physiological signal from the implantable device.

A stroke detection apparatus for determining that a stroke is occurring or has recently occurred to a user, wherein the apparatus comprises a data processing device comprising a processor and at least one wearable sensor configured to be worn by a user and configured to transmit a movement data of the user to the data processing device. The data processing device is configured to process the movement data to determine a first probability of a user stroke over a first time period and a second probability of a user stroke over a second time period. A stroke detection signal is then generated in dependence on at least the first probability and second probability.

A signal processing apparatus and a signal processing method are provided. The signal processing apparatus includes a memristor array, an input circuit, a first switching circuit, a second switching circuit, an output circuit, and a control circuit. The memristor array includes memristor units and is connected to source lines, word lines and bit lines. The control circuit is configured to control the first switching circuit to select at least one source line to apply at least one first signal to the at least one source line respectively, control the second switching circuit to select and activate at least one word line to apply the at least one first signal to a memristor unit corresponding to the at least one word line, and control the output circuit to output a plurality of second signals based on conductivity values of memristors of the memristor array.

A seizure detection system including one or more circuits configured to receive an electroencephalogram (EEG) signal generated based on electrical brain activity of a patient. The one or more circuits are configured to identify candidate seizures with a statistical analysis that identifies the candidate seizures based on changes in non-linear features of the EEG signal, determine to switch from identifying the candidate seizures with the statistical analysis to an artificial intelligence model, and switch from identifying the candidate seizures with the statistical analysis to identifying the candidate seizures based on the artificial intelligence model with the EEG signal.

Devices, systems, and techniques are described for detecting stroke or seizure with a compact system. 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, based on the electrical signals, physiological information. The system may also include processing circuitry configured to receive, from the sensing circuitry, the physiological information, determine, based on the physiological information, a seizure metric indicative of a seizure status of the patient and a stroke metric indicative of a stroke status of the patient, and store the seizure metric and the stroke metric in the memory. A housing may carry the plurality of electrodes and contain both of the sensing circuitry and the processing circuitry.

This invention concerns a system for brain signal measurement and analysis using graphene based electrodes. The system is minimally invasive with small size electrodes and a stamp-size electronic processor with wireless communication and a remote computing device, enabling brain signal collection outside of clinical settings. The electrodes and electronic processor are both imprinted onto the subject's scalp using three-dimensional printers with small size electronics. After use, the electrodes and electronic processor may be washed off or removed without injuries to the subject.

In some examples, a device includes at least three electrodes a first pair of electrodes and a second pair of electrodes. The device also includes circuitry configured to generate a first cardiac signal based on a first differential signal received across the first pair, generate a first brain signal based on the first differential signal received across the first pair, generate a second cardiac signal based on a second differential signal received across the second pair, and generate a second brain signal based on the second differential signal received across the second pair. The circuitry is also configured to output a composite cardiac signal based on the first cardiac signal and the second cardiac signal and to output a composite brain signal based on the first brain signal and the second brain signal.