Patent · US Active

Systems and methods for training a personalized machine learning model for fall detection

US11170295B1 · kind B1 · utility

9Cited by

0References

20Claims

0Family size

Assignee

Tidyware, LLC · US

Inventors

Philip Carmichael · Bellevue, US
Brian Hayward · Lawrence, US
Alvin G Solidum · Bellevue, US
Travis T Okahara · Kirkland, US
William L Richman · Seattle, US
Raman Chandrasekar · Seattle, US
Patrick Dean Kennedy · Fall City, US
Ray Sun · Issaquah, US

Key dates

Filing date	Sep 19, 2017
Grant date	Nov 9, 2021
Priority date	—
Expiry date	Aug 24, 2040

Classification

Technology area (CPC G)Physics
CPC primaryG06N20/20
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

Systems and methods for training a personalized Machine Learning (ML) model used to detect fall events are described herein. The methods may be implemented by one or more computing devices and may include obtaining sensor data associated with one or more activities of a user. A processed or unprocessed version of at least a copy of the sensor data having been fed to a personalized ML model associated with the user and that has been determined not to be associated with a fall event; and using the obtained sensor data training the personalized ML model.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.