User calibration of a machine learning model to recognize neural activities, and applications thereof
US12380193B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 27, 2024 |
| Grant date | Aug 5, 2025 |
| Priority date | — |
| Expiry date | Dec 27, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2221/2117
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
In an embodiment, a computer-implemented method for decoding neural activity is provided. In the method, at least one machine learning model is trained using a training data set of EEG data and concurrently collected environmental data collected from data collection participants. Once the at least one machine learning model is trained, EEG data measured from sensors attached to or near a user's head is received. Environmental data describing stimulus the user is exposed to concurrently with the measurement of the EEG data is also received. The EEG data and the environmental data is input into the at least one machine learning model to determine an inference related to the neural activity. Based on the inference, an operation of a computer program is altered.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.