Seizure detection, prediction and prevention using neurostimulation technology and deep neural network
US10596377B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 30, 2017 |
| Grant date | Mar 24, 2020 |
| Priority date | — |
| Expiry date | May 29, 2038 |
Classification
- Technology area (CPC A)Human Necessities
- CPC primaryA61B2505/07
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
A method for neuromodulation includes monitoring brain activity of a patient using one or more electrodes attached to the patient, and using a first machine learning model to predict whether a patient will have a seizure based on the monitored brain activity of the patient. The method also includes, responsive to the first machine learning model predicting that the patient will have a seizure, using a second machine learning model to determine a neuromodulation signal pattern for preventing the predicted seizure. The method further includes using a neurostimulator to apply the determined neuromodulation signal pattern to the patient. The method also includes, after applying the determined neuromodulation signal pattern to the patient, detecting whether the patient had the predicted seizure based on the monitored brain activity of the patient. The method further includes adjusting at least the second machine learning model based on whether the patient had the predicted seizure.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.