Adaptive model-based system to automatically quantify fall risk
US10692011B2 · kind B2 · utility
12Cited by
2References
20Claims
0Family size
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Key dates
| Filing date | Jan 21, 2016 |
| Grant date | Jun 23, 2020 |
| Priority date | — |
| Expiry date | Jun 20, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/30
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
A method predicts the fall risk of a user based on a machine learning model. The model is trained using data about the user, which may be from wearable sensors and depth sensors, manually input by the user, and received from other types of sources. Data about a population of users and data from structured tests completed by the user can also be used to train the model. The model uses features and motifs discovered based on the data that correlate to fall risk events to update fall risk scores and predictions. The user is provided a recommendation describing how the user can reduce a predicted fall risk for the user.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.