A method of restoring a high-frequency biosignal includes the steps of loading a first biosignal by a processor and converting the first biosignal that is a low-frequency signal into a second biosignal that is a high-frequency signal on the basis of a first neural network model.

A method for controlling connectivity between two or more brain regions of a subject includes receiving signals corresponding to a connectivity between two or more regions of a subject's brain, measuring a connectivity level from the signals, and delivering at least one stimulation pulse to at least one target region of the subject's brain if the measured connectivity level is outside of a predetermined range.

This apparatus (1) comprises at least one intravascular device (10), (20) that is disposed in a blood vessel of an organism and that is equipped with at least one electrode (11), (12), (21), (22) for detecting or stimulating the activity of nerve tissue positioned outside the blood vessel nearby, the electrodes (11), (12), (21), (22) being provided on a wire member.

Methods and systems for assessing a stroke rehabilitation outcome of a subject include a home-based brain-controlled interface (BCI) apparatus and a computer processor in communication with the BCI apparatus. The BCI apparatus has i) a portable brain signal acquisition headset that acquires a brain signal from a subject; ii) an orthosis device having a body part interface configured to be coupled to a body part of the subject and a plurality of sensors that generate force data and movement data; and iii) a BCI component that receives the brain signal from the brain signal acquisition headset. The BCI component is capable of controlling the orthosis device. The computer processor performs instructions to process input data to output a rehabilitation outcome prediction for the subject, where the input data includes the brain signal, the force data, the movement data, and background information about the subject.

A mote includes an optical receiver that wirelessly receives a power and data signal in form of NIR light energy within a patient and converts the NIR light energy to an electrical signal having a supply voltage. A control module supplies the supply voltage to power devices of the mote. A clock generation circuit locks onto a target clock frequency based on the power and data signal and generates clock signals. A data recovery circuit sets parameters of one of the devices based on the power and data signal and a first clock signal. An amplifier amplifies a neuron signal detected via an electrode inserted in tissue of the patient. A chip identifier module, based on a second clock signal, generates a recorded data signal based on a mote chip identifier and the neuron signal. A driver transmits the recorded data signal via a LED or a RF transmitter.

A mote includes an optical receiver that wirelessly receives a power and data signal in form of NIR light energy within a patient and converts the NIR light energy to an electrical signal having a supply voltage. A control module supplies the supply voltage to power devices of the mote. A clock generation circuit locks onto a target clock frequency based on the power and data signal and generates clock signals. A data recovery circuit sets parameters of one of the devices based on the power and data signal and a first clock signal. An amplifier amplifies a neuron signal detected via an electrode inserted in tissue of the patient. A chip identifier module, based on a second clock signal, generates a recorded data signal based on a mote chip identifier and the neuron signal. A driver transmits the recorded data signal via a LED or a RF transmitter.

An apparatus and method is provided for intraoperative tissue stimulation during port-based surgery. The apparatus includes an access port and electrical terminals attached to the access port for tissue stimulation. In an alternative embodiment, the apparatus may include an access port, with or without electrical terminals attached to the access port for tissue stimulation, and electrocorticography sensors attached to the access port. The method includes inserting an access port into a tissue, applying an electrical potential to the tissue using electrical terminals attached to the access port, and measuring consequent neural activity using electrocorticography sensors attached to the access port.

An apparatus for measuring intracranial dynamics comprises the at least one sensing device (100): an electroencephalo-graphic electrode arrangement, which senses direct-current electroencephalographic signals from the brain, an optic measurement Marrangement (120), which directs optic radiation toward the brain through the cranium, and receives the optic radiation reflected and/or scattered therefrom, and/or a capacitive sensor arrangement (130), which senses electric potential signals of the head. The apparatus additionally comprises a data processing arrangement (150), which receives electric signals from the at least one sensing device (100), and determine data on at least one of the following dynamics: glymphatic activity, water within the cranium, brain tissue movements, water and/or electrolyte movements and intracranial pressure based on said electric signals from the at least one sensing device (100). The data processing arrangement (150) then outputs at least one piece of the data on the dynamics through a user interface (152).

A systems and methods for calibrating a neural device using transfer learning techniques. The methods can include aggregating calibration data across a user population to define a global dataset, identifying similar data segments across the global dataset to define a task-independent training dataset, training a feature extraction model based on the task-independent training dataset to define a trained, task-independent feature extraction model, receiving the calibration data from a user calibrating the neural device, and calibrating a user-specific feature extraction model using the trained, task-independent feature extraction model and the calibration data.

A neural device system that can include a neural device configured to sense data associated with the subject or receive control input, an external device communicably coupled to the neural device, a storage medium communicable coupled to the external device, and one or more communications interfaces between the neural device, the external device, and the storage medium or components thereof, wherein the one or more communications interfaces comprise an encryption protocol.