TECHNIQUES FOR ESTIMATING SKIN TONE USING A MACHINE LEARNING MODEL

Abstract

Methods, systems, and devices for estimating skin tone using a machine learning (ML) model are described. A wearable device may transmit light using a light-emitting component, and generate a signal based on the light received at a photodetector. In some examples, a strength of the received signal may be maintained within a signal strength band. The wearable device may identify a data set pair based on the signal, the data set pair including the signal strength band and a transmit power parameter that corresponds to the signal strength band. The data set pair may be inputted into an ML model and the ML model may output a skin tone metric for the user. The estimated skin tone metric may then be used to adjust measurement parameters used by the wearable device to improve a quality of physiological data, or validate algorithms used by the wearable device across skin tones.

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