Methods, systems and devices for reducing anxiety, including increasing relaxation and/or calm. In some variations these methods may include reducing anxiety, increase relaxation and/or calm by non-invasive temperature regulation of the frontal cortex prior to and/or during sleep. The subject may have an anxiety disorder, or may not have a diagnosed anxiety disorder.

Embodiments may provide self-guided, self-directed diagnostics and treatment of neural conditions. For example, a system may comprise a processor, memory accessible by the processor, and program instructions and data stored in the memory, a plurality of stimulation devices connected to signal output circuitry interfacing the processor with the stimulation devices, program instructions and data to control the stimulation devices to generate and transmit stimulation signals, a plurality of sensing devices connected to signal input circuitry interfacing the processor with the sensing devices, program instructions and data to receive sensed signals from the sensing devices, a communication device adapted to wirelessly communicate with a server computer system, and program instructions and data to perform dynamic closed loop feedback of the stimulation signals based on the received sensed signals to provide self-guided, self-directed diagnostics and treatment of neural conditions using at least one recipe for a treatment strategy guided by artificial intelligence.

An active implantable stimulating device (10) includes: (a) a tissue coupling unit (40) for being implanted directly onto a vagus nerve (Vn) of a patient, (b) an EEG-unit (70) for measuring an electroencephalogram of the patient, (c) an encapsulation unit (50) configured for being subcutaneously implanted, (d) an energy transfer lead (30) for transferring pulses of electrical and/or optical energy, (e) a signal transfer lead (60) for transferring signals between the EEG unit and the encapsulation unit. EEG electrodes (70a-70d) monitor the electric activity of the brain of a patient. The EEG signal is conveyed to the electronic circuit (53) in the form of EEG conditioned data. The electronic circuit analyses the EEG conditioned data to yield analysis results. The electronic circuit takes a decision to trigger energy pulses to stimulate the vagus nerve (VN).

A data processing method for detecting and classifying a segment of a signal that is obtained from a single-channel EEG-recording as a target signal segment or as a non-target signal segment. The method includes a voting process to determine whether classification of a first detected segment of the signal as a target signal segment or classification of a second detected segment of the signal as a non-target signal segment is correct. A device and a system that are configured and arranged to perform the data processing method.

A metaverse multimedia system based on user brainwaves causes that emotional messages, voice messages and color messages could be captured from the brainwaves of the users. The emotional messages are integrated to the role of the user in the metaverse space. Hence, the role in the metaverse can respond the emotions of the user, while the voice messages and color messages are integrated into the sceneries in the metaverse, which is selected by the user. As a result, the metaverse space completely presents user's states of mind which are captured from the brainwaves of the users. Furthermore the whole sceneries and presentations of the roles in the metaverse space are adjustable with the changes of the users. It can also express user's personalities. Interaction modes between the users and visitors entering into the metaverse space of the user could be analyzed based on the method disclosed in the present invention.

A flexible sheet for neurostimulation has a flexible non-conductive substrate matrix in which electrodes are embedded along a lower surface. Electrically conductive wires extend from the electrodes through the flexible substrate to another exterior surface of the substrate. Methods of making the flexible sheet and making a device using the flexible sheet are also disclosed.

The present application discloses various methods and apparatuses for determining a head movement, wherein a method for determining a head movement disclosed comprises: acquiring, in response to a head movement of a human body, brain electricity detection information of a human body; and determining the head movement corresponding to the brain electricity detection information. The present application provides a new solution for head movement recognition, by which accuracy of head movement recognition is improved.

The present invention comprises methods and devices for modulating the activity or activities of living cells, such as cells found in or derived from humans, animals, plants, insects, microorganisms and other organisms. Methods of the present invention comprise use of the application of ultrasound, such as low intensity, low frequency ultrasound, to living cells to affect the cells and modulate the cells' activities. Devices of the present invention comprise one or more components for generating ultrasound waves, such as ultrasonic emitters, transducers or piezoelectric transducers, composite transducers, CMUTs, and which may be provided as single or multiple transducers or in an array configurations. The ultrasound waves may be of any shape, and may be focused or unfocused.

An estimation apparatus is configured to be capable of accessing a model storage unit that stores a model built by machine learning, using, as training data, information on a predetermined sound and information relating to a signal source of a signal indicating a brain activity of a first subject presented with the predetermined sound, the model outputting information on a sound estimated to be recognized by the subject. The estimation apparatus acquires a brain wave of a second subject presented with the predetermined sound. The estimation apparatus estimates, based on a mode of the brain wave acquired, a signal source of the brain wave, from among a plurality of regions in a brain of the second subject. The estimation apparatus inputs the information relating to the signal source estimated to the model and acquires information on a sound estimated to be recognized by the second subject.

An apparatus for providing information about a user's brain resources is provided. The apparatus includes at least sensor interface circuitry and processing circuitry coupled to the sensor interface circuitry. In a calibration mode, the sensor interface circuitry is configured to receive first sensor data from an electroencephalography sensor. The first sensor data are indicative of an electroencephalogram of the user. Further, the sensor interface circuitry is configured to receive second sensor data from a physiological sensor in the calibration mode. The second sensor data are indicative of a physiological property of the user. In the calibration mode, the processing circuitry is configured to train a brain-physiological model for the user based on the first sensor data and the second sensor data.