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.

Systems and methods for presenting electrostimulation data and patient clinical responses to electrostimulation are disclosed. A system comprises an implantable stimulator, and a programming device including a controller to identify first and second sets of base stimulation settings each comprising an electrode configuration and stimulation parameter values selected from a configuration and parameter search space. The controller can detect clinical effects and evaluate a clinical response indicator in response to electrostimulation for each base stimulation setting of the first set, and predict clinical effects and estimate a clinical response indicator without delivering electrostimulation for each base stimulation setting of the second set. Based on the clinical response indicators, the controller can determine characteristic stimulation amplitudes for one or more electrode configurations. A formatted monopolar review report comprising the characteristic stimulation amplitudes can be displayed to the user.

The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

In some embodiments, a method of providing a neurostimulation therapy to a patient, comprises: generating a noise pulse pattern defining a pulse train of pulses to be generated according to a noise profile in an external device; communicated the generated noise pulse pattern to an implantable pulse generator (IPG) of a patient; generating, by the IPG, a series of pulses in sequence for noise stimulation of the patient using the noise pulse pattern from the external device, wherein the IPG applies one or more randomization operations to the pulse pattern from the external device without expanding memory storage for the pulse pattern while maintaining the noise profile of the pulse pattern from the external device; and applying the series of pulses in sequence to neural tissue of the patient using one or more electrodes of one or more stimulation leads.

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.

This disclosure is directed to devices, systems, and techniques for controlling electrical stimulation. In some examples, a computing device includes a therapy-management application configured to assist a user to: capture a representative evoked compound action potential (ECAP) signal from a patient based; apply one or more filters to the representative ECAP signal to select one or more parameters of the representative ECAP signal; and control electrical stimulation therapy based at least in part on the one or more parameters.

Systems, methods, and interfaces are described herein for identification of effective electrodes to be used in sensing and/or therapy. Two or more portions of a signal monitored using an electrode may be compared to determine whether the electrode is effective. The two or more portions may correspond to the same portion or window of a cardiac cycle. Further, signals from a first electrode and from a second electrode located proximate the first electrode may be compared to determine whether one or both of the electrodes are effective.

Controlling the interaction between an external device and an implanted device, including a method of controlling interaction between an external device and an implanted device, the method including at least the steps of: establishing communications between the implanted device and the external device; the external device determining an identification of the implant and comparing the identification with identifications in a stored list; if the device matches one of said identifications, then using a corresponding set of operating parameters to interact with said implant; and otherwise, not interacting with said device.

In some examples, a processor of a system evaluates a therapy program based on a score determined based on a volume of tissue expected to be activated (“VTA”) by therapy delivery according to the therapy program. The score may be determined using an efficacy map comprising a plurality of voxels that are each assigned a value. In some examples, the efficacy map is selected from a plurality of stored efficacy maps based on a patient condition, one or more patient symptoms, or both the patient condition and one or more patient symptoms. In addition, in some examples, voxels of the efficacy map are assigned respective values that are associated with a clinical rating scale.

Systems and methods are described herein for configuration of cardiac therapy. The systems and methods may select, or determine, a plurality of different configuration parameters based electrical activity monitored or measured using a plurality of external electrodes. For example, the systems and methods may select, or determine, a left ventricular pacing vector, adaptive or non-adaptive pacing therapy, an interventricular pacing delay, and a atrioventricular pacing delay.