Fall detection using machine learning

US10422814B2 · kind B2 · utility

Assignee

• Vital Connect, Inc. · US

Inventors

• Alexander Chan · Colorado Springs, US
• Nima Ferdosi · San Jose, US
• Ravi Narasimhan · Los Altos, US

Key dates

• Filing date: Jul 18, 2013
• Grant date: Sep 24, 2019
• Expiry date: Feb 8, 2034

Classification

• Technology area (CPC G): Physics
• CPC primary: G01P15/0891
• WIPO field: Measurement
• WIPO sector: Instruments

Abstract

A method and system for fall detection using machine learning are disclosed. The method comprises detecting at least one signal by a wireless sensor device and calculating a plurality of features from the at least one detected signal. The method includes training a machine learning unit of the wireless sensor device using the features to create a fall classification and a non-fall classification for the fall detection. The system includes a sensor to detect at least one signal, a processor coupled to the sensor, and a memory device coupled to the processor, wherein the memory device includes an application that, when executed by the processor, causes the processor to calculate a plurality of features from the at least one detected signal and to train a machine learning unit of the wireless sensor device using the features to create a fall classification and a non-fall classification for the fall detection.