Systems and methods are disclosed related to using acoustic waves to detect neural activity in a brain and/or localize the neural activity in the brain. Sensors positioned outside of a skull encasing the brain can detect acoustic waves associated with the neural activity in the brain. From output signals of the sensors, a particular type of neural activity (e.g., a seizure) can be detected. A location of the neural activity can be determined based on outputs of the sensors. In some embodiments, the ultrasound energy can be applied to the location of the neural activity in response to detecting the neural activity.

Methods, devices, and systems induce neuromodulation by focusing a source of stimulation through a skull/brain interface in the form of an aperture formed in the skull, a naturally occurring fenestration in the skull, or a transcranial channel. Methods, devices, and systems identify where to locate skull/brain interfaces, accessories that can be used with the interfaces, and features for controlling stimulation delivered through the interfaces. Multiple indications for the skull/brain interfaces include diagnosis and treatment of neurological disorders and conditions such as epilepsy, movement disorders, depression, Alzheimer's disease, autism, coma, and pain.

Electrodes for use in electroencephalographic recording, including consciousness and seizure monitoring applications, have novel features that speed, facilitate or enforce proper placement of the electrodes, including aligning tabs and arrowed aligning juts, color coding, and an insulating bridge between reference and ground electrodes which ensures a safe application distance between the conductive regions of the two electrodes in the event of cardiac defibrillation or to prevent shorting between the adjacent electrodes by preventing the conductive path to be shared. A method of using a set of four such electrodes is also disclosed.

One embodiment provides a method, including: obtaining EEG data from one or more single channel EEG sensor worn by a user; classifying, using a processor, the EEG data as one of nominal and abnormal; and providing an indication associated with a classification of the EEG data. Other embodiments are described and claimed.

A method of processing EEC signals received from a plurality electrodes. The method comprises processing the EEC signals to determine a modulation index value for each electrode, determining one or more electrodes that have a modulation index value above a threshold level observed during ictal activity, and using the determined one or more electrodes, to identify one or more possible regions of interest corresponding to seizure zones of a subject's brain.

An adaptive cognitive prosthetic that learns to replace neural function that was lost due to a brain injury or disease is described herein. In some embodiments, an adaptive cognitive prosthetic comprises a processing unit for converting input data from an input assembly into a cognitive variable and selecting a stimulation pattern for conveying the cognitive variable. The processing unit employs an adaptive algorithm to assemble the stimulation pattern by combination of subset stimulation patterns, the combination of subset stimulation patterns learned by the adaptive algorithm through error analysis.

The application relates to a hearing device, e.g. a hearing aid, comprising a first part for being inserted in an ear canal or fully or partially implanted in the head of a user, the first part comprising at least one electrode unit, termed a PR-electrode unit, for making contact to skin or tissue of a user when mounted or implanted in an operational condition, the at least one PR-electrode unit being configured to pick up a physiological response from the user, and wherein the at least one PR-electrode unit comprises an electrically conductive material, e.g. a shape memory alloy. The first part may comprise an implanted part, e.g. in combination with an external part adapted for being located in an ear canal, wherein both parts comprise one or more PR-electrode units. The invention may e.g. be used hearing aids, headsets, ear phones, active ear protection systems, or combinations thereof, e.g. to control processing of the hearing device or to monitor a condition of the user wearing the hearing device.

A system for identifying amygdala hyperactivity in a human patient includes a network-connected mobile apparatus associated with the user. The network-connected mobile apparatus may be used to accept mood, energy and behavior input from the user and to accept third party patient observation data via the network. The network-connected device may be further used to accept provider-labeled patient observation data via the network and to provide behavioral suggestions to the user based on a set of profile rules. The profile rules may be generated from the behavior input from the user, the third-party patient observation data, and provider-labeled patient observation data as processed by a machine-learning system.

An in-ear stimulation system including a first device configured to be worn at least partially in a first ear canal of a subject and a second device configured to be worn at least partially in a second ear canal of the subject. Each of the first device and the second device includes: at least one in-ear active electrode configured to receive a bio-signal and at least one in-ear reference electrode configured to receive a bio-signal; at least one stimulation device configured for emitting at least one electrical or sensory stimulus; and an electronic system configured to detect at least one bio-signal pattern from the bio-signals measured from the electrodes.

Systems and methods are described for detecting and characterizing seizures or seizure-related events. The methods herein may include determining magnitude and/or scaled magnitude data for each of at least one high and low frequency group of signals. Based on the determined magnitudes and/or scaled magnitude data, seizures or seizure-related events may be characterized.