A neuromodulator includes an electromagnetic (EM) wave generator configured to generate EM waves remote from a patient and to direct the EM waves to one or more target regions within the patient. Frequencies of the EM waves fall outside a range of frequencies that activates neurons. Intersection of the EM waves in each target region creates envelope-modulated electric and magnetic fields having one or more frequencies that fall within the range of frequencies that activates neurons. The neuromodulator includes control circuitry configured to control parameters of the EM waves produced by the EM wave generator. The neuromodulator may use feedback based on one or more of patient input and/or sensing of physiological signals in order to close the loop and control the EM waves.

Disclosed herein are methods and apparatus for the imaging of brain electrical activity from electromagnetic measurements, using deep learning neural networks where a simulation process is designed to model realistic brain activation and electromagnetic signals to train generalizable neural networks and a residual convolutional neural network and/or a recurrent neural network is trained using the simulated data, capable of estimating source distributions from electromagnetic measurements, and their temporal dynamics over time, for pathological signals in diseased brains, such as interictal activity and ictal signals, and physiological brain signals such as evoked brain responses and spontaneous brain activity.

Disclosed herein are methods and apparatus for the imaging of brain electrical activity from electromagnetic measurements, using deep learning neural networks where a simulation process is designed to model realistic brain activation and electromagnetic signals to train generalizable neural networks and a residual convolutional neural network and/or a recurrent neural network is trained using the simulated data, capable of estimating source distributions from electromagnetic measurements, and their temporal dynamics over time, for pathological signals in diseased brains, such as interictal activity and ictal signals, and physiological brain signals such as evoked brain responses and spontaneous brain activity.

Disclosed herein are various embodiments of an interface control subsystem that may be used between an electrode terminal and a recording terminal of a neurostimulation and neurorecording system. The interface control subsystem may operate in three modes. In a disable mode, a first transistor and a second transistor disposed between the electrode terminal and the recording terminal may operate in a cutoff region and generate a high impedance. In an active mode, the first transistor and the second transistor may operate in a saturation region and generate a low impedance. In a stimulation mode, the first transistor and the second transistor operate in a triode region and generate an impedance between the high impedance of the disable mode and the low impedance of the active mode. The interface control subsystem may further limit voltage at the recording terminal in response to a detected overvoltage condition.

Systems and methods for automatically analyzing and selecting prominent channels from multi-dimensional biomedical signals in order to detect particular diseases or ailments are provided. Such systems and methods may be applied in different ways to obtain numerous benefits, such as lowering of power and processing requirements, reducing an amount of data acquired, simplifying hardware deployment, detecting non-trivial patterns, obtaining, clinical episode prognosis, improving patient care, and/or the like.

Systems and methods for automatically analyzing and selecting prominent channels from multi-dimensional biomedical signals in order to detect particular diseases or ailments are provided. Such systems and methods may be applied in different ways to obtain numerous benefits, such as lowering of power and processing requirements, reducing an amount of data acquired, simplifying hardware deployment, detecting non-trivial patterns, obtaining, clinical episode prognosis, improving patient care, and/or the like.

An index output device for appropriately evaluating the conditions of the patient under anesthesia. An index output device 100 includes an electric stimulation section 170, an acquisition section 180, a calculation section, and an output section. The electric stimulation section 170 is configured to apply an electric stimulus to a living body. The acquisition section 180 is configured to acquire a plurality of physiological responses from the living body in response to the common electric stimulus applied to the living body by the electric stimulation section 170. The calculation section is configured to calculate, from the plurality of responses of the living body acquired by the acquisition section, an index related to a level of muscular relaxation (TOF) and an index related to a level of analgesia (PIR). The output section is configured to output the indexes calculated by the calculation section.

An index output device for appropriately evaluating the conditions of the patient under anesthesia. An index output device 100 includes an electric stimulation section 170, an acquisition section 180, a calculation section, and an output section. The electric stimulation section 170 is configured to apply an electric stimulus to a living body. The acquisition section 180 is configured to acquire a plurality of physiological responses from the living body in response to the common electric stimulus applied to the living body by the electric stimulation section 170. The calculation section is configured to calculate, from the plurality of responses of the living body acquired by the acquisition section, an index related to a level of muscular relaxation (TOF) and an index related to a level of analgesia (PIR). The output section is configured to output the indexes calculated by the calculation section.

A mobile device for measuring at least one electrical biosignal. The device comprises a first input and a second input, a measuring circuit part for providing an output signal indicating the electrical biosignal to be measured, the measuring circuit part comprising a first input and a second input, and a charging circuit part for charging a rechargeable battery inserted in the device, the charging circuit part comprising a first input and a second input. The first input of the measuring circuit part and the first input of the charging circuit part are connected to the first input of the mobile device and the second input of the measuring circuit part and the second input of the charging circuit part are connected to the second input of the mobile device.

A mobile device for measuring at least one electrical biosignal. The device comprises a first input and a second input, a measuring circuit part for providing an output signal indicating the electrical biosignal to be measured, the measuring circuit part comprising a first input and a second input, and a charging circuit part for charging a rechargeable battery inserted in the device, the charging circuit part comprising a first input and a second input. The first input of the measuring circuit part and the first input of the charging circuit part are connected to the first input of the mobile device and the second input of the measuring circuit part and the second input of the charging circuit part are connected to the second input of the mobile device.