Machine-learning based gesture recognition using multiple sensors

A device, comprising:

• a first sensor;
• a second sensor;
• at least one processor;
• and
• a memory including instructions that, when executed by the at least one processor, cause the at least one processor to:
• receive, from the first sensor, first sensor output of a first type;
• receive, from the second sensor, second sensor output of a second type that differs from the first type;
• provide the first sensor output and the second sensor output as inputs to a machine learning model, the machine learning model having been trained to output a predicted gesture based on sensor output of the first type and sensor output of the second type;
• determine the predicted gesture based on an output from the machine learning model;
• and
• perform, in response to determining the predicted gesture, a predetermined action on the device.

A computer program product comprising code, stored in a non-transitory computer-readable storage medium, the code comprising:

• code to receive, from a first sensor of a device, first sensor output of a first type, the first sensor comprising a bio-signal sensor;
• code to receive, from a second sensor of the device, second sensor output of a second type that differs from the first type;
• code to provide the first sensor output and the second sensor output as inputs to a machine learning model, the machine learning model having been trained to output a predicted gesture based on sensor output of the first type and sensor output of the second type;
• code to determine the predicted gesture based on an output from the machine learning model;
• and
• code to perform, in response to determining the predicted gesture, a predetermined action on the device.