US 2022/0044820 A1 · METHODS AND APPARATUS FOR INJURY PREDICTION BASED ON MACHINE LEARNING TECHNIQUES

Abstract

Systems and methods of the present disclosure enable injury prediction using one or more processors for receiving a time-varying signal of sensor measurements from a sensor device associated with a user. The processor(s) generate time windows of the time-varying signal, including a series of the sensor measurements across a predetermined time period, and generate motion features based at least in part on the series of the sensor measurements of the time windows. The processor(s) utilize an injury risk classification machine learning model to predict an injury risk during each time window based at least in part on the motion features. An injury alert message is generated based at least in part on the injury risk being predicted; and transmitting the injury alert message to at least one user computing device.

Claims20

Dependent claims

A method comprising:

receiving, by at least one processor, a time-varying signal of sensor measurements from at least one sensor device associated with at least one user;
generating, by the at least one processor, at least one time window of the time-varying signal, wherein the at least one time window comprises a series of the sensor measurements across a predetermined time period;
generating, by the at least one processor, at least one motion feature based at least in part on the series of the sensor measurements of the at least one time window;
utilizing, by the at least one processor, an injury risk classification machine learning model to predict an injury risk during the at least one time window based at least in part on the at least one motion feature;
generating, by the at least one processor, an injury alert message based at least in part on the injury risk being predicted;
and
transmitting, by the at least one processor, the injury alert message to at least one user computing device.

4 more elements

A system comprising:

at least one processor;
and
a non-transitory memory storing instructions which, when executed by the at least one processor, causes the at least one processor to:
receive a time-varying signal of sensor measurements from at least one sensor device associated with at least one user;
generate at least one time window of the time-varying signal, wherein the at least one time window comprises a series of the sensor measurements across a predetermined time period;
generate at least one motion feature based at least in part on the series of the sensor measurements of the at least one time window;
utilize an injury risk classification machine learning model to predict an injury risk during the at least one time window based at least in part on the at least one motion feature;
generate an injury alert message based at least in part on the injury risk being predicted;
and
transmit the injury alert message to at least one user computing device.

7 more elements

A non-transitory computer readable medium storing instructions which, when executed by at least one processor, are configured to cause the at least one processor to perform steps comprising:

receiving a time-varying signal of sensor measurements from at least one sensor device associated with at least one user;
generating at least one time window of the time-varying signal, wherein the at least one time window comprises a series of the sensor measurements across a predetermined time period;
generating at least one motion feature based at least in part on the series of the sensor measurements of the at least one time window;
utilizing an injury risk classification machine learning model to predict an injury risk during the at least one time window based at least in part on the at least one motion feature;
generating an injury alert message based at least in part on the injury risk being predicted;
and
transmitting the injury alert message to at least one user computing device.

4 more elements

Dependencies are inferred from the claim text.

Methods and apparatus for injury prediction based on machine learning techniques

Life of this patent

Methods and apparatus for injury prediction based on machine learning techniques

Life of this patent

Abstract

Claims20