An EMG-based Eating Behaviour Monitoring System with Haptic Feedback to Promote Mindful Eating
Ben Nicholls, Chee Siang Ang, Eiman Kanjo, Panote Siriaraya, Woon-Hong, Yeo, Athanasios Tsanas

TL;DR
This paper presents an innovative EMG-based wearable system that automatically detects eating behaviors and uses haptic feedback to promote mindful eating, potentially improving health outcomes by reducing mindless eating habits.
Contribution
The study introduces a novel lightweight system combining EMG sensors and real-time haptic feedback for automatic eating behavior detection and behavior modification.
Findings
High accuracy in detecting chewing (F1-Score=0.94) and swallowing (F1-Score=0.86) using EMG features and SVM.
Haptic feedback significantly reduced chewing rate during the experiment (p<0.001).
System demonstrates potential for real-time mindful eating interventions.
Abstract
Mindless eating, or the lack of awareness of the food we are consuming, has been linked to health problems attributed to unhealthy eating behaviour, including obesity. Traditional approaches used to moderate eating behaviour often rely on inaccurate self-logging, manual observations or bulky equipment. Overall, there is a need for an intelligent and lightweight system which can automatically monitor eating behaviour and provide feedback. In this paper, we investigate: i) the development of an automated system for detecting eating behaviour using wearable Electromyography (EMG) sensors, and ii) the application of such a system in combination with real time wristband haptic feedback to facilitate mindful eating. Data collected from 16 participants were used to develop an algorithm for detecting chewing and swallowing. We extracted 18 features from EMG and presented those features to…
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Taxonomy
TopicsErgonomics and Musculoskeletal Disorders · Tactile and Sensory Interactions
