Towards Detecting Auditory Attention from in-Ear Muscle Contractions using Commodity Earbuds
Harshvardhan Takawale, Yang Liu, Khaldoon Al-Naimi, Fahim Kawsar, Alessandro Montanari
Abstract
In a world dominated by podcasts and audiobooks, maintaining auditory attention is essential, yet lapses in focus are common. Auditory attention is crucial for effective communication and comprehension in a distraction-filled environment, as it enables us to focus on important sounds while avoiding external distractions. This work introduces a novel, imperceptible method for detecting auditory attention using earbuds by monitoring muscle movement within the ear canal. We employ an ultrasound-based sensing technique to track phase changes in reflected signals, detecting muscle vibrations associated with shifts in attention. A preliminary user study reveals significant changes in in-ear signal characteristics when participants switch between auditory and cognitive tasks. We show that our system can classify periods of auditory attention and lack of it with an accuracy of 85.7% and a variance of 0.0033. Our findings pave the way for earables that continuously monitor and enhance auditory attention in real-time.
BibTeX
@inproceedings{icassp2025_towardsdetecting,
title = {Towards Detecting Auditory Attention from in-Ear Muscle Contractions using Commodity Earbuds},
author = {Harshvardhan Takawale and Yang Liu and Khaldoon Al-Naimi and Fahim Kawsar and Alessandro Montanari},
booktitle = {ICASSP 2025},
year = {2025}
}