Method for generating a personalized classifier for human motion activities of a mobile or wearable device user with unsupervised learning
US10588517B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | May 19, 2017 |
| Grant date | Mar 17, 2020 |
| Priority date | — |
| Expiry date | May 11, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/20
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
Described herein is a method of operating an electronic device that includes collecting initial motion activity data from at least one sensor of the electronic device, and generating a initial probabilistic context of the electronic device relative to its surroundings from the initial collected motion activity data using a motion activity classifier function. The collected motion activity data is stored in a training data set, and the motion activity classifier function is updated using the training data set. The method also includes collecting subsequent motion activity data from the at least one sensor of the electronic device, and generating a subsequent probabilistic context of the electronic device relative to its surroundings from the subsequently collected motion activity data using the updated motion activity classifier function.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.