An implantable neurostimulator system including an electrical lead having formed thereon a pair of bipolar electrodes, the electrical lead is configured for placement of the pair of bipolar electrodes proximate protrusor muscles of a patient. The system also includes a pulse generator electrically connected to the electrical lead and configured to deliver electrical energy to the pair of bipolar electrodes, the pulse generator having mounted therein a sensor configured to detect one or more physiological parameters, a memory, a control circuit, and a telemetry circuit. The system also including a communications telemetry module (CTM) in communication with the telemetry circuit and configured to receive a data collected by the sensor and data related to delivery of electrical energy to the bipolar electrodes, and an external programmer in communication with the CTM and configured to display a user interface the data collected by the sensor and data related to delivery of electrical energy to the bipolar electrodes.

A device is provided for stimulating neurons that includes a non-invasive stimulation unit that generates stimuli in multiple stimulation channels. The stimulation unit generates the stimuli to stimulate a neuron population in the brain and/or spinal cord of a patient using the stimulation channels in different locations. Moreover, the device includes a control unit that controls the stimulation unit to repeatedly generates sequences of the stimuli with the order of the stimulation channels in which stimuli are generated within a sequence being constant for 20 or more successively generated sequences before it is varied.

Methods and systems for programming stimulation parameters for an implantable medical device for neuromodulation, such as spinal cord stimulation (SCS) are disclosed. The stimulation parameters define user-configured waveforms having at least a first phase having a first polarity and a second phase having a second polarity, wherein the first and second phases are separated by an interphase interval (IPI). By delivering user-configured waveforms with different IPIs, stimulation geometry, and other waveform settings, therapeutic asynchronous activation of dorsal column fibers can be obtained.

Systems, methods, and devices for automatic generation of a stimulation therapy that mimics electrographic activity in the brain at natural seizure termination define a stimulation therapy to be generated by an implanted component of a medical device system and delivered to a subject through identifying data characterizing a patient's seizures, especially at termination. A machine learning model identifies the seizures or seizure types from which to establish a canonical seizure or seizure type, and an algorithm translates the canonical seizure or seizure type into data that can be used to characterize a stimulation therapy. The systems, methods, and devices, include those configured to deliver the stimulation therapy that emulates the canonical seizure or seizure type when the seizure is detected, with the aim of terminating the seizure sooner than it would terminate without intervention.

An electrical stimulation method is provided. The electrical stimulation method is applied to an electrical stimulation device. The steps of the electrical stimulation method include obtaining a target energy value; providing an electrical stimulation signal to a target area; calculating a total energy value according to an energy value transmitted from the electrical stimulation signal to the target area; and determining whether the total energy value has reached the target energy value.

Described herein are systems and methods for applying extremely low duty-cycle stimulation sufficient to treat chronic inflammation using feedback to adjust the off times between stimulations. In particular, the feedback include an assessment of the level of inflammation by the patient or the healthcare provider, or by measure the level of an inflammatory analyte or biomarker, or by detecting nerve activity correlated with inflammation.

An electrical stimulation method for impedance compensation is provided. The electrical stimulation method for impedance compensation is applied to an electrical stimulation device for providing high frequency electrical stimulation. In the above method, by an impedance compensation device, a high-frequency environment is provided and a first impedance value of a lead is calculated according to at least one of a measured first resistance value, a measured first capacitance value and a measured first inductance value of the lead is calculated. By the impedance compensation device, the high-frequency environment is provided and a second impedance value of the electrical stimulation device is calculated according to at least one of a measured second resistance value, a measured second capacitance value and a measured second inductance value of the electrical stimulation device. The first impedance value and the second impedance value are stored for calculating a tissue impedance.

Systems and methods for treating a patient having a blood glucose abnormality, such as type 2 diabetes (T2D), using an electrical signal are disclosed. A representative method for treating a patient includes, based at least in part on a patient indication of a blood glucose abnormality, positioning at least one implantable signal delivery device proximate to a target location at the patient's spinal cord within a vertebral range of from about C8 to about T12. The method further includes directing an electrical signal to the target location via the implantable signal delivery device, wherein the electrical signal has a frequency in a frequency range of from 1.2 kHz to 100 kHz.

The present invention provides materials and methods for using electrical stimulation to treat a mammal having a proteinopathy (e.g., neurodegenerative diseases) or at risk of developing a proteinopathy are provided. For example, the present invention provides materials and methods for modulating glymphatic clearance (e.g., enhancing glymphatic clearance) of pathogenic proteins.

Information relevant to making clinical decisions for a patient is identified based on electrical activity records of the patient's brain and electrical activity records of other patients' brains. A deep learning algorithm is applied to an electrical activity record of the patient, i.e., an input record, and to a set of electrical activity records of other patients, i.e., a set of search records, to obtain an input feature vector of the patient and a set of search feature vectors, each including features extracted by the deep learning algorithm. A similarities algorithm is applied to the input feature vector and the set of search feature vectors to identify a subset of search records most like the input record. Clinical information associated with one or more search records in the identified subset of search records is extracted from a database and used to make decisions regarding the patient's neuromodulation therapies.