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.

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).

An electroencephalography net (44) comprised of electrodes (34, 36) coupled together by a connector (28) comprising separate elastically (32) and plastically (30) deformable elements.

An electroencephalography net (44) comprised of electrodes (34, 36) coupled together by a connector (28) comprising separate elastically (32) and plastically (30) deformable elements.

The disclosed biopotential measurement device may include a front end comprising a biopotential measurement sensor and a back end comprising a processor programmed to process biopotential signals detected by the biopotential measurement sensor. The biopotential measurement device may also include an isolation circuit that, during at least a sampling phase of the biopotential measurement sensor, electrically isolates the front end from the back end. Various other methods, systems, and computer-readable media are also disclosed.

The disclosed biopotential measurement device may include a front end comprising a biopotential measurement sensor and a back end comprising a processor programmed to process biopotential signals detected by the biopotential measurement sensor. The biopotential measurement device may also include an isolation circuit that, during at least a sampling phase of the biopotential measurement sensor, electrically isolates the front end from the back end. Various other methods, systems, and computer-readable media are also disclosed.

There is provided a sensor for an electroencephalographic (EEC) device for measuring electrical signals generated by the neuronal activity of a subject. The sensor has at least one blade-like contact surface and the contact surface has a curved profile adapted for user comfort and electrical contact.

There is provided a sensor for an electroencephalographic (EEC) device for measuring electrical signals generated by the neuronal activity of a subject. The sensor has at least one blade-like contact surface and the contact surface has a curved profile adapted for user comfort and electrical contact.

[Object] To provide an information processing apparatus, a biological data measurement system, an information processing method, and a program that can improve the accuracy of acquired biological data. [Solving Means] An information processing apparatus according to the present technology includes a body motion noise prediction unit and a control unit. The body motion noise prediction unit predicts, on the basis of a reference signal that is body motion information of a person to be measured detected by a reference signal sensor, that body motion noise caused by body motion of the person to be measured is added to a detection biological signal detected by a biological sensor from the person to be measured. The control unit controls signal processing of the detection biological signal on the basis of a prediction result of the body motion noise prediction unit.