Machine learning based artifact rejection for transcranial magnetic stimulation electroencephalogram
US11577090B2 · kind B2 · utility
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Inventors
Key dates
| Filing date | Dec 19, 2017 |
| Grant date | Feb 14, 2023 |
| Priority date | — |
| Expiry date | Apr 25, 2040 |
Classification
- Technology area (CPC A)Human Necessities
- CPC primaryA61N2/02
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
A method for machine learning based artifact rejection is provided. The method may include applying a machine learning model to identify artefactual independent components in transcranial magnetic stimulation electroencephalogram data collected during a transcranial magnetic stimulation procedure. Clean transcranial magnetic stimulation electroencephalogram data is generated by removing, from the transcranial magnetic stimulation electroencephalogram data, the artefactual independent components. Real-time adjustments to parameters of the transcranial magnetic stimulation procedure may be performed based on the clean transcranial magnetic stimulation electroencephalogram data. Related systems and articles of manufacture, including computer program products, are also provided.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.