System and method for activity classification
AssigneeCypress Semiconductor Corporation
InventorsNiall Lyons, Avik Santra, Ashutosh Pandey
Life of this patent
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Abstract
One or more computing devices, systems, and/or methods are provided. In an example, a method comprises receiving, by a device, incoming motion data from a motion sensor, generating, by the device, an incoming embedding vector based on the incoming motion data, generating, by the device, a predicted embedding vector based on the incoming embedding vector, assigning, by the device, an activity classification based on the predicted embedding vector, and modifying an operating parameter of the device based on the activity classification.
Claims18
A method comprising:
- receiving, by a device, incoming 3-axis time series motion data from a motion sensor;
- projecting, by a processor in the device, the 3-axis time series motion data into an incoming embedding vector using an embedding model;
- generating, by the processor in the device, a predicted embedding vector based on the incoming embedding vector and using a Kalman filter;
- assigning, by the processor in the device, an activity classification based on the predicted embedding vector;
- and
- modifying, by the processor in the device, an operating parameter of the device based on the activity classification.
A device, comprising:
- a motion sensor configured to generate incoming 3-axis time series motion data;
- and
- a processor configured to execute instructions to facilitate performance of operations comprising:
- projecting the 3-axis time series motion data into an incoming embedding vector using an embedding model based on the incoming motion data;
- generating a predicted embedding vector based on the incoming embedding vector and using a Kalman filter;
- assigning an activity classification based on the predicted embedding vector;
- and
- modifying an operating parameter of the device based on the activity classification.
A non-transitory computer-readable medium storing instructions that when executed facilitate performance of operations comprising:
- receiving incoming motion data from a motion sensor;
- projecting the 3-axis time series motion data into an incoming embedding vector using an embedding model based on the incoming motion data;
- generating a predicted embedding vector based on the incoming embedding vector and using a Kalman filter;
- assigning an activity classification based on the predicted embedding vector;
- and
- modifying an operating parameter of a device based on the activity classification.
Dependencies are inferred from the claim text.