An improved system for assessing cognitive function is described that uses tracked electrical activity of the brain of the individuals in response to a specific sequence of stimuli in generating data sets, which, for example, can be encapsulated as a data structure. The data sets can include tracked specific response types, at different times and amplitudes, including, but not limited to, event related potential signal components. Brainwave features including, event related potentials, are tracked in relation to both pre-attentive brain responses and consciously controlled attention responses.

An improved system for assessing cognitive function is described that uses tracked electrical activity of the brain of the individuals in response to a specific sequence of stimuli in generating data sets, which, for example, can be encapsulated as a data structure. The data sets can include tracked specific response types, at different times and amplitudes, including, but not limited to, event related potential signal components. Brainwave features including, event related potentials, are tracked in relation to both pre-attentive brain responses and consciously controlled attention responses.

The present invention relates to an apparatus for task determination during brain activity analysis. The apparatus comprises an input unit (20), a processing unit (30), and an output unit (40). The input unit is configured to provide the processing unit with measurement data of the brain of a patient performing a task during brain activity analysis. The processing unit is configured to determine a measure of brain activity based on the measurement data of the brain. The processing unit is configured to determine: that the patient should perform a different task to the task they are currently performing and select the different task; or that the patient should continue performing the task that they are currently performing; or that the patient should stop performing the task; The determination comprises utilization of information relating to the task and the determined measure of brain activity and information relating to a plurality of reference tasks and associated plurality of reference measures of brain activity. The output unit is configured to output an indication that the patient should perform the different task, that the patient should continue performing the task, or that the patient should stop performing the task.

The present invention relates to an apparatus for task determination during brain activity analysis. The apparatus comprises an input unit (20), a processing unit (30), and an output unit (40). The input unit is configured to provide the processing unit with measurement data of the brain of a patient performing a task during brain activity analysis. The processing unit is configured to determine a measure of brain activity based on the measurement data of the brain. The processing unit is configured to determine: that the patient should perform a different task to the task they are currently performing and select the different task; or that the patient should continue performing the task that they are currently performing; or that the patient should stop performing the task; The determination comprises utilization of information relating to the task and the determined measure of brain activity and information relating to a plurality of reference tasks and associated plurality of reference measures of brain activity. The output unit is configured to output an indication that the patient should perform the different task, that the patient should continue performing the task, or that the patient should stop performing the task.

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.

A method for machine learning based artifact rejection is provided. The method may include applying a machine learning model to identify artefactual independent components in transcranial magnetic stimulation electroencephalogram data collected during a transcranial magnetic stimulation procedure. Clean transcranial magnetic stimulation electroencephalogram data is generated by removing, from the transcranial magnetic stimulation electroencephalogram data, the artefactual independent components. Real-time adjustments to parameters of the transcranial magnetic stimulation procedure may be performed based on the clean transcranial magnetic stimulation electroencephalogram data. Related systems and articles of manufacture, including computer program products, are also provided.

A method for machine learning based artifact rejection is provided. The method may include applying a machine learning model to identify artefactual independent components in transcranial magnetic stimulation electroencephalogram data collected during a transcranial magnetic stimulation procedure. Clean transcranial magnetic stimulation electroencephalogram data is generated by removing, from the transcranial magnetic stimulation electroencephalogram data, the artefactual independent components. Real-time adjustments to parameters of the transcranial magnetic stimulation procedure may be performed based on the clean transcranial magnetic stimulation electroencephalogram data. Related systems and articles of manufacture, including computer program products, are also provided.

Methods, apparatuses, and systems for robotic insertion of a screw, a rod, or another component of a surgical implant into a patient are disclosed. Clinical data from previous surgical procedures or information received from a supervising surgeon can be leveraged to minimize the risk of harm to the patient and improve outcomes. The methods disclosed thus provide more precise placement of implanted surgical components and implants.

Methods, systems and devices for treating chronic pain by inducing stimulation to a predetermined region of the brain and measuring neural activity response to the stimulation and evaluating a neuroplasticity and/or excitability of neural-structures in a predetermined brain region, then stimulating the predetermined brain region to treat the chronic pain.