Systems and methods for providing neurostimulation therapy according to machine learning operations

Patent metadata

Field	Value
Publication number	US-12280258-B2
Application number	US-202117566636-A
Country	US
Kind code	B2
Filing date	Dec 30, 2021
Priority date	Dec 31, 2020
Publication date	Apr 22, 2025
Grant date	Apr 22, 2025

Abstract

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 trained using data corresponding to time intervals in which electrical pulses are applied to the patient, including video kinematic data, patient reported pain levels, implanted or worn sensor patient data, and stimulation parameters. The model is used to control ongoing neurostimulation therapy for the patient.

First claim

The invention claimed is:

1. A method of providing a neurostimulation therapy to a patient, comprising:
applying electrical pulses to a neural target of a patient according to a plurality of stimulation parameters;
obtaining patient data from one or more sensors implanted in or worn by the patient while electrical pulses are applied to the patient;
obtaining video data of the patient;
calculating, based on the video data, kinematic data corresponding to time intervals in which the electrical pulses are applied to the patient;
obtaining patient reported pain levels from the patient using one or more patient applications on a patient therapy controller device, the patient reported pain levels corresponding to time intervals in which the electrical pulses are applied to the patient;
training a machine learning (ML) model using the plurality of stimulation parameters, the patient data, the kinematic data, and the patient reported pain levels, wherein the training comprises receiving user input from a user interface of an external controller device to select one or more patient features from a plurality of available patient features for training of the ML model;
controlling, based on the trained ML model, application of electrical pulses to the patient to treat pain of the patient in accordance with patient data from the one or more sensors.

2. The method of claim 1 , further comprising:
selecting the neurostimulation therapy from a list consisting of: spinal cord stimulation and dorsal root ganglion stimulation.

3. The method of claim 1 , further comprising:
obtaining movement data by a sensor of a wearable device of the patient.

4. The method of claim 1 , further comprising:
obtaining movement data by a sensor of an implantable pulse generator (IPG) of the patient.

5. The method of claim 1 , further comprising:
performing the training by one or more software applications executed on a patient therapy controller device.

6. The method of claim 1 , further comprising:
performing the training by one or more software applications executed by one or more processors of an implantable pulse generator (IPG) of the patient.

7. The method of claim 1 , further comprising:
performing the training by one or more software applications executed by one or more processors of a server platform of a medical device management system.

8. The method of claim 1 , further comprising:
receiving input from a user interface of an external controller device to clear a previously trained model; and
clearing model parameters for the previously trained model in response to the received input.

9. The method of claim 1 , wherein controlling application of electrical pulses to the patient includes providing dorsal root ganglion stimulation.

Assignees

• Advanced Neuromodulation Systems Inc

Inventors

• Hughes Nicole R
• Nobles Robert
• Deshazo Daran
• Mark Betty

Classifications

• G16H40/67

  for remote operation · CPC title

• A61N1/36139

  with automatic adjustment · CPC title

• A61N1/36132 Primary

  using patient feedback · CPC title

• A61B5/11

  Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb {(A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721)} · CPC title

• A61B5/7267

  involving training the classification device · CPC title