The present technology provides a medical stimulation system having a clinical programmer configured to operate on a computational and memory device having a wireless communication device. The technology also provides a neurostimulator configured to wirelessly communicate with the clinical programmer. The neurostimulator also includes a pulse generator operatively coupled with an electrode by a lead. The pulse generator is configured to transmit an electrical signal comprising a repeating succession of non-regular pulse trains. Each pulse train includes a plurality of pulses having non-regular, non-random, differing inter-pulse intervals therebetween. The pulse trains repeat in succession to treat a neurological condition. Further, the pulse trains are initiated by instructions communicated by the clinical programmer.

A bioelectric interface is provided. The bioelectric interface comprises a case having a channel configured to hold a nerve. An electrode array is slidably coupled to the case, wherein the electrode array comprises a number of electrode shanks. The case restricts movement of the electrode array to one degree of freedom toward or away from the nerve held in the channel for insertion of the electrode shanks into the nerve.

Embodiments may provide a general-purpose, relatively inexpensive, AI-driven implant that is able to adapt to and modulate any given region in the brain. For example, in an embodiment, an implant device adapted to be implanted within a body of a person for interacting with brain tissue may comprise a plurality of fibers adapted to receive electrical and optical signals from electrophysiological neural signals of the brain tissue and to transmit electrical and optical signals to provide electrophysiological stimulation of the brain tissue, the fibers electrically and optically coupled to at least one readout integrated circuit.

A skull-implantable electrode assembly for delivering pulses of electric current to a patient's brain, comprising a conductor housed in an insulated conduit and threaded through an electrically-conductive cannulated skull screw. Details of the exterior construction are discussed, as well as electrode arrangements and methods of treating a medical ailment of a patient.

Systems and techniques are disclosed to generate programming parameters and modifications during closed-loop adjustment of an implantable neurostimulation device treatment programming, through the identification and application of weights determined from user input indications and rankings of therapy objectives. In an example, a system to generate programming values of a neurostimulation device performs operations that: obtains human input which indicates multiple therapy objectives for neurostimulation treatment of a human patient; operates a model (such as an artificial intelligence model) to determine parameter outputs for programming of the neurostimulation device; identifies weights, based on the therapy objectives, usable in the model; produces a composite output from the model, by applying the identified weights to a combination of the parameter outputs of the programming model; and the resulting composite output provides neurostimulation device programming values for neurostimulation treatment designed to address the therapy objectives.

A system and method for diagnosing mental or emotional disorders is disclosed. An affective BCI component is incorporated into a closed loop, symptomresponsive psychiatric DBS system. A series of input data related to a brain of the patient is acquired while the patient performs a battery of behavioral tasks. From the patient's performance on the task battery, the system identifies what is abnormal for that individual patient in terms of functional domains. Patient-specific behavioral measurements are then linked to patterns of activation and de-activation across different brain regions, identifying specific structures that are the source of the patient's individual impairment.

Deep Brain Stimulation (DBS) electrodes are positioned within (or adjacent to) white matter fiber tracts in a brain of patient. The DBS electrodes may be positioned near one or more stimulation sites within the white matter fiber tracts. The stimulation sites may be selected based on the disorder of the patient. In some examples, the stimulation sites may be selected based on one or more symptoms of the patient. In some examples, additional electrodes may be positioned in another area to collect bioelectrical brain signals. The area in which the additional electrodes are placed is an area that is different from the stimulation site but is targeted by stimulation therapy provided at the stimulation site.

Systems and methods for deploying a paddle neurostimulation lead configured to provide DRG stimulation within a patient. A DRG therapy system includes a delivery tool includes a delivery tube including a first linear segment, a second linear segment, and an arcuate segment coupled between the first and second linear segments, the first and second linear segments having an angle therebetween and the second linear segment defining an elongated opening. The delivery tool further includes a stylet positioned within an interior of the delivery tube, and a handle coupled to the delivery tube and including a stylet actuation mechanism configured to selectively advance and retract the stylet between a deployed position and a retracted position, wherein the stylet extends across the elongated opening in the deployed position to engage an engagement member of the paddle neurostimulation lead.

A system and method for optimizing parameters of a DBS pulse signal for treatment of a patient is provided. In predicting optimal DBS parameters, functional brain data is input into a predictor system, the functional brain data acquired responsive to a sweeping across a multi-dimensional parameter space of one or more DBS parameters. Statistical metrics of brain response are extracted from the functional brain data for one or more ROIs or voxels of the brain via the predictor system, and a DBS functional atlas is accessed, via the predictor system, that comprises disease-specific brain response maps derived from DBS treatment at optimal DBS parameter settings for a plurality of diseases or neurological conditions. One or more optimal DBS parameters are predicted for the patient based on the statistical metrics of brain response and the DBS functional atlas via the predictor system.

A system and method for optimizing parameters of a DBS pulse signal for treatment of a patient is provided. In predicting optimal DBS parameters, functional brain data is input into a predictor system, the functional brain data acquired responsive to a sweeping across a multi-dimensional parameter space of one or more DBS parameters. Statistical metrics of brain response are extracted from the functional brain data for one or more ROIs or voxels of the brain via the predictor system, and a DBS functional atlas is accessed, via the predictor system, that comprises disease-specific brain response maps derived from DBS treatment at optimal DBS parameter settings for a plurality of diseases or neurological conditions. One or more optimal DBS parameters are predicted for the patient based on the statistical metrics of brain response and the DBS functional atlas via the predictor system.