Abstract
In recent years, smartwatches have emerged as a viable platform for a variety of medical and health-related applications. In addition to the benefits of a stable hardware platform, these devices have a significant advantage over other wrist-worn devices, in that user acceptance of watches is higher than other custom hardware solutions. In this paper, we describe signal-processing techniques for identification of chews and swallows using a smartwatch device׳s built-in microphone. Moreover, we conduct a survey to evaluate the potential of the smartwatch as a platform for monitoring nutrition. The focus of this paper is to analyze the overall applicability of a smartwatch-based system for food-intake monitoring. Evaluation results confirm the efficacy of our technique; classification was performed between apple and potato chip bites, water swallows, talking, and ambient noise, with an F-measure of 94.5% based on 250 collected samples.
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