Method for generating a personalized classifier for human motion activities of a mobile or wearable device user with unsupervised learning
US11096593B2 · kind B2 · utility
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Inventors
Key dates
| Filing date | Feb 6, 2020 |
| Grant date | Aug 24, 2021 |
| Priority date | — |
| Expiry date | Feb 12, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/20
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
Motion activity data is collected from at least one sensor. An initial motion activity classifier function is applied to the motion activity data to produce an initial motion activity posteriorgram. Pre-processing and segmenting the motion activity data into windows produces segmented motion activity data from which sensor specific features are extracted. An updated motion activity classifier function is generated from the extracted sensor specific features. Subsequent motion activity data is also collected from the at least one sensor, and the updated motion activity classifier function is applied to the subsequent motion activity data to produce an updated motion activity posteriorgram.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.