Earinter: A Closed-Loop System for Eating Pace Regulation with Just-in-Time Intervention Using Commodity Earbuds

TL;DR

Earinter is a novel system using commodity earbuds to accurately monitor and regulate eating pace in real-world settings through real-time sensing and timely interventions, promoting healthier eating habits.

Contribution

This work introduces Earinter, a new earbud-based closed-loop system that combines in-the-wild sensing, real-time reasoning, and theory-grounded interventions for eating pace regulation.

Findings

Achieved high chewing detection accuracy (F1=0.97).

Accurately estimated eating pace (MAE=0.18 chews/min).

Significantly increased chewing per swallow and reduced eating speed in field study.

Abstract

Rapid eating is common yet difficult to regulate in situ, partly because people seldom notice pace changes and sustained self-monitoring is effortful. We present Earinter, a commodity-earbud-based closed-loop system that integrates in-the-wild sensing, real-time reasoning, and theory-grounded just-in-time (JIT) intervention to regulate eating pace during daily meals. Earinter repurposes the earbud's bone-conduction voice sensor to capture chewing-related vibrations and estimate eating pace as chews per swallow (CPS) for on-device inference. With data collected equally across in-lab and in-the-wild sessions, Earinter achieves reliable chewing detection (F1 = 0.97) and accurate eating pace estimation (MAE: 0.18 $\pm$ 0.13 chews/min, 3.65 $\pm$ 3.86 chews/swallow), enabling robust tracking for closed-loop use. Guided by Dual Systems Theory and refined through two Wizard-of-Oz pilots, Earinter adopts a user-friendly design for JIT intervention content and delivery policy in daily meals. In a 13-day within-subject field study (N=14), the closed-loop system significantly increased CPS and reduced food-consumption speed, with statistical signs of carryover on retention-probe days and acceptable user burden. Our findings highlight how single-modality commodity earables can support practical, theory-driven closed-loop JIT interventions for regulating eating pace in the wild.