Machine learning system for predicting optimal interruptions based on biometric data collected using wearable devices
US11157832B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 19, 2017 |
| Grant date | Oct 26, 2021 |
| Priority date | — |
| Expiry date | May 8, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F1/163
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Method and apparatus for using machine learning to monitor biometric data to provide intelligent alerts are provided. At a first moment in time, first biometric data for a plurality of users are received from a plurality of sensor devices. A group metric is generated by processing the first biometric data using at least one trained machine learning model, and it is determined that the group metric does not satisfy one or more predefined criteria. At a second moment in time, second biometric data for the plurality of users is received from the plurality of sensor devices, and an updated group metric is generated by processing the second biometric data using the at least one trained machine learning model. Upon determining that the updated group metric satisfies the one or more predefined criteria, an indication is provided that the one or more predefined criteria have been satisfied.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.