Methods and systems for optimizing therapy using stimulation mimicking natural seizures
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Publication Number
US-12303694-B2
Publication Date
2025-05-20
Expiration Date
Abstract
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.
Core Innovation
The document describes optimizing epilepsy neuromodulation by detecting an instance of an electrographic seizure based on a patient's electrographic activity, wherein the electrographic seizure is characterized by an offset. Responsive to the detection, a stimulation therapy is delivered to the patient such that the stimulation therapy emulates a canonical seizure offset constructed from a plurality of seizure offsets in electrographic seizures.
To construct and use the canonical seizure offset, the document describes using machine learning for seizure processing, including detecting seizure onset and characterizing seizure type. The approach includes generating a canonical seizure termination pattern for one or multiple seizure types using techniques that align and aggregate seizure termination patterns and that operate in feature space, including dynamic time warping with averaging, median, or mode, clustering, and deep learning approaches such as autoencoder and generative model approaches.
The document further describes converting a characterized waveform pattern into stimulation therapy through pulse characterization data. A threshold-based discretization is described to convert the waveform pattern into a train of stimulation pulses, including biphasic pulses with pulse amplitude variability and pulse width variability matched to waveform portions, and delivering the therapy when seizure onset is detected; the document also discusses iterating or selecting therapies by seizure type and provides examples involving canonical termination and derived stimulation patterns.
Claims Coverage
The partial content provides two independent claims, covering both a method and an implantable neurostimulator system. Across these independent claims, the coverage centers on seizure detection based on electrographic activity with an offset characterization, and delivering responsive stimulation that emulates a canonical seizure offset constructed from multiple seizure offsets.
Detect electrographic seizure characterized by an offset and deliver responsive therapy emulating a canonical seizure offset
Detecting an instance of an electrographic seizure based on a patient's electrographic activity, wherein the electrographic seizure is characterized by an offset; and responsive to a detection of an instance of the electrographic seizure, delivering a stimulation therapy to the patient, wherein the stimulation therapy emulates a canonical seizure offset constructed from a plurality of seizure offsets in electrographic seizures.
Implantable neurostimulator system with electrodes, offset-based detection, and therapy emulating canonical seizure offset
An implantable neurostimulator system comprising a plurality of electrodes; a detection module coupled to the plurality of electrodes configured to detect an instance of an electrographic seizure based on a patient's electrographic activity, wherein the electrographic seizure is characterized by an offset; and a stimulation generator configured to deliver a stimulation therapy to the patient in response to a detection of an instance of the electrographic seizure, wherein the stimulation therapy emulates a canonical seizure offset constructed from a plurality of seizure offsets in electrographic seizures.
Overall, the independent-claim coverage is directed to offset-characterized electrographic seizure detection and responsive stimulation whose waveform or behavior emulates a canonical seizure offset derived from multiple seizure offsets.
Stated Advantages
Not explicitly described in patent.
Documented Applications
Optimization and delivery of epilepsy neurostimulation using responsive stimulation that emulates canonical seizure termination or offset patterns constructed from seizure offsets in electrographic seizures.
Seizure termination or offset emulation therapy selection or iteration based on seizure type.
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