In rehabilitation, a stimulation pattern when applied to a body part by a neuromuscular electrical stimulation (NMES) device is effective to cause the body part to perform an intended action. The applying includes increasing a stimulation level at which the stimulation pattern is applied over time and, during the applying, acquiring video of the body part. The body part is monitored during the applying by analysis of the video, and the applying is automatically stopped in response to the monitoring indicating the body part has performed the intended action. The stimulation pattern may be defined as one or more subsets of electrodes of the NMES device and an electrode group stimulation level for each respective subset of electrodes, and the increasing of the stimulation level comprises increasing a scaling factor applied to the electrode group stimulation levels over time.

An assistance method for assisting a person in grasping or otherwise manipulating an object includes receiving video of a hand of the person and of an object. An intent to grasp the object is identified based on proximity of the hand to the object in the video or as measured by a proximity sensor, or using gaze tracking, or based on measured neural activity of the person. The object and the hand in the video are analyzed to determine an object grasping action for grasping or otherwise manipulating the object. An actuator is controlled to cause the hand to perform the determined hand action for grasping or otherwise manipulating the object.

The present disclosure provides systems and methods for providing neurostimulation therapy according to patient features. The patient features may be analyzed to develop a patient model between physiological and/or patient reported features and optimal settings for a neurostimulation therapy using machine learning operations. The model is used to control ongoing neurostimulation therapy for the patient.

The present invention provides improved methods for positioning of an implantable lead in a patient with an integrated EMG and stimulation clinician programmer. The integrated clinician programmer is coupled to the implantable lead, wherein the implantable lead comprises at least four electrodes, and to at least one EMG sensing electrode minimally invasively positioned on a skin surface or within the patient. The method comprises delivering a test stimulation at a stimulation amplitude level from the integrated clinician programmer to a nerve tissue of the patient with a principal electrode of the implantable lead. Test stimulations are delivered at a same stimulation amplitude level for a same period of time sequentially to each of the four electrodes of the implantable lead. A stimulation-induced EMG motor response is recorded with the integrated clinician programmer for each test stimulation on each electrode of the implantable lead via the at least one pair of EMG sensing electrodes so as to facilitate initial positioning of the implantable lead at a target stimulation region.

Improved stimulation circuitry for controlling the stimulation delivered by an implantable stimulator is disclosed. The stimulation circuitry includes memory circuitry that stores pulse programs that define pulse shapes, steering programs that define electrode configurations, and aggregate programs that link a selected pulse program with a selected steering program. The aggregate programs also include an amplitude modulation factor that modulates the amplitude defined by the pulse program. The inclusion of an amplitude modulation factor in the aggregate program allows complex amplitude-modulated waveforms to be produced. Pulse definition circuits in the stimulation circuitry execute aggregate programs to generate stimulation waveforms, which stimulation waveforms can be generated simultaneously by the different pulse definition circuits.

An example of a system for programming neurostimulation according to a stimulation configuration may include stimulation configuration circuitry, volume definition circuitry, stimulation effect circuitry, and recording circuitry. The stimulation configuration circuitry may be configured to determine the stimulation configuration. The volume definition circuitry may be configured to determine stimulation field model(s) (SFM(s)) each representing a volume of tissue activated by the neurostimulation. The stimulation effect circuitry may be configured to determine a stimulation effect type for each tagging point specified for the SFM(s) and to tag the SFM(s) at each tagging point with the stimulation effect type determined for that tagging point. The stimulation effect type for each tagging point is a type of stimulation resulting from the neurostimulation as measured at that tagging point. The recording circuitry may be configured to generate SFM data representing the determined SFM(s) with the stimulation effect type tagged at each tagging point.

A method of neurostimulation includes applying a probe signal to an electrode implanted in or near a target neural structure of the brain. The method further includes detecting a first response from the target neural structure evoked by the probe signal and determining a first time period between application of the probe signal and a first temporal feature of the response. Further, the method includes generating a therapeutic signal comprising a plurality of pulses, at least two of the plurality of pulses separated by the first time period, and applying the therapeutic signal to the electrode or another electrode implanted in or near the target neural structure.

Systems and methods for closed-loop control of electrostimulation while avoiding, or maintaining a substantially low level of, evoked neural activity are disclosed. A system comprises an electrostimulator to deliver a stimulation pulse train, a sensing circuit to sense evoked responses to respective pulses in the pulse train, and a controller to detect an evoked neural activity from an averaged evoked response by averaging evoked responses to respective pulses. The averaging operation can be controlled by a noise level of the averaged evoked response, or by a count of epochs (pulses) being used for averaging. Responsive to the evoked neural activity satisfying a detection criterion, the controller recursively adjusts stimulation parameters until the detection criterion is no longer satisfied. The electrostimulator delivers electrostimulation according to the recursively adjusted stimulation parameters.

In some embodiments, a clinician programmer device for controlling a deep brain stimulation (DBS) system is adapted to assist a clinician to conduct an electrode screening review for the DBS system including screening of segmented electrodes. The clinician programmer stores software code for conducting a screening review in memory. The software code may comprise: code for providing one or more interface screens for guiding the user of the device through testing of electrode configurations of the implantable stimulation lead, wherein the code for providing applies at least one testing progression for guiding the user of the device through a defined testing order.

An electrical stimulation system for use with a plurality of electrodes implanted within a tissue region comprises a neurostimulator configured for delivering electrical stimulation energy to the plurality of electrodes in accordance with a set of stimulation parameters, thereby injecting a charge into the tissue region, a control device configured for receiving user input to modify the set of stimulation parameters, and controller/processor circuitry configured for, in response to the user input computing a charge injection metric value as a function of a physical electrode parameter and an electrical source parameter for a first set of the electrodes, wherein the electrode set comprises at least two electrodes, comparing the computed charge injection metric value to a safety threshold value, and performing a corrective action based on the comparison.