A device and a method for acquiring brain electrical signal. The device for acquiring brain electrical signal includes a plurality of electrodes and an electrode base. The electrode base is provided with a plurality of screw holes, and each of the plurality of electrodes passes through a corresponding screw hole of the plurality of screw holes.

A device and a method for acquiring brain electrical signal. The device for acquiring brain electrical signal includes a plurality of electrodes and an electrode base. The electrode base is provided with a plurality of screw holes, and each of the plurality of electrodes passes through a corresponding screw hole of the plurality of screw holes.

A surgical robot system including: at least one slave manipulator for handling a surgical instrument within a body of a patient; and a control console, including: at least one master operating unit configured to be manually operated by an operating person to at least control the at least one slave manipulator; a display for displaying information; and at least one switch configured to: couple the at least one master operating unit with the at least one slave manipulator; decouple the at least one master operating unit from the at least one slave manipulator, and when the at least one master operating unit is decoupled from the at least one slave manipulator, couple the at least one master operating unit with the display.

A device and a signal processing method that can be used with a device to recognize and distinguish a physiological high-frequency oscillation (HFO) from a pathological high-frequency oscillation. The signal processing method detects a physiological HFO in the electrical brain signal one regimen of electrical or optogenetic brain stimulation can be triggered, alternatively if the method detects a pathological HFO associated with epilepsy a different regimen of electrical or optogenetic brain stimulation can be triggered. Thus, the signal processing method can be utilized in a closed loop brain stimulation device that serves the dual purpose of both enhancing memory encoding, consolidation, and recall, or improving cognition, and reducing the probability of a seizure in a patient with epilepsy.

A device and a signal processing method that can be used with a device to recognize and distinguish a physiological high-frequency oscillation (HFO) from a pathological high-frequency oscillation. The signal processing method detects a physiological HFO in the electrical brain signal one regimen of electrical or optogenetic brain stimulation can be triggered, alternatively if the method detects a pathological HFO associated with epilepsy a different regimen of electrical or optogenetic brain stimulation can be triggered. Thus, the signal processing method can be utilized in a closed loop brain stimulation device that serves the dual purpose of both enhancing memory encoding, consolidation, and recall, or improving cognition, and reducing the probability of a seizure in a patient with epilepsy.

The present invention relates to systems for providing noninvasive cranial nerve stimulation and methods for using the same. The present invention administers therapy through electrodes that are noninvasively attached to one or more of a subject's cranial nerve. The systems can be used to enhancing rehabilitation and recovery by improving neuroplasticity and coupling muscle training with feedback.

Described herein is a system and method for controlling a computing system by an AI network based upon an electroencephalograph (EEG) signal from a user. The user's EEG signals are first detected as the user operates an existing controller, during which time the associated artificial intelligence (AI) system learns by correlating the EEG signals with the commands received from the controller. Once the AI system determines that there is sufficient correlation to predict the user's actions, it can take control of the computing system and initiate commands based upon the user's EEG signal in place of the user's actions with the controller. At this point, weights in the AI network may be locked so that further commands from the controller, or the lack thereof, do not reduce correlation with the EEG signals. In some embodiments, the AI network may initiate commands faster than the user would be able to do.

Described herein is a system and method for controlling a computing system by an AI network based upon an electroencephalograph (EEG) signal from a user. The user's EEG signals are first detected as the user operates an existing controller, during which time the associated artificial intelligence (AI) system learns by correlating the EEG signals with the commands received from the controller. Once the AI system determines that there is sufficient correlation to predict the user's actions, it can take control of the computing system and initiate commands based upon the user's EEG signal in place of the user's actions with the controller. At this point, weights in the AI network may be locked so that further commands from the controller, or the lack thereof, do not reduce correlation with the EEG signals. In some embodiments, the AI network may initiate commands faster than the user would be able to do.

A stimulation system includes an energy source, an electronics unit with a controller, and an actuator that is coupled with the electronics unit and/or the energy source. The actuator emits electromagnetic waves for stimulation of genetically manipulated tissue. The electronics unit is disposed in a housing. The stimulation system is configured for at least temporary implantation in a human or animal body. The controller controls the stimulation of tissue in the body by way of the electromagnetic waves emitted by the actuator. A selector of the stimulation system selects the area of the said tissue for stimulation. The selector includes a masking device for masking certain areas of the tissue, so that an intensity of the stimulation for the masked areas is reduced or equal to zero.

An electrode system for an intracranial electroencephalogram is described. A substrate is configured to be applied directly on a brain of a patient. The substrate has a profile that is suitable to be placed within a subdural space in between a portion of intact cranium and cerebral cortex of the brain. A tracking device is arranged on the substrate. A plurality of electrodes are configured to sense electrical activity associated with the brain. Each of the plurality of electrodes has a predefined relationship with the tracking device. A tracking system is operable to determine a position of the tracking device relative to a reference point based on a strength of an electromagnetic field relative to the tracking device. A controller is configured to selectively determine a position for each of the plurality of electrodes based on the position of the tracking device and the predefined relationship.