Heart: Motion-resilient heart rate monitoring with in-ear microphones

With the soaring adoption of in-ear wearables, the research community has started investigating suitable in-ear heart rate (HR) detection systems. HR is a key physiological marker of cardiovascular health and physical fitness. Continuous and reliable HR monitoring with wearable devices has therefore...

Full description

Saved in:
Bibliographic Details
Main Authors: BUTKOW, Kayla-Jade, DANG, Ting, FERLINI, Andrea, MA, Dong, MASCOLO
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2023
Subjects:
Online Access:https://ink.library.smu.edu.sg/sis_research/8278
https://ink.library.smu.edu.sg/context/sis_research/article/9281/viewcontent/hEART_Percom23.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English
id sg-smu-ink.sis_research-9281
record_format dspace
spelling sg-smu-ink.sis_research-92812023-11-10T08:38:59Z Heart: Motion-resilient heart rate monitoring with in-ear microphones BUTKOW, Kayla-Jade DANG, Ting FERLINI, Andrea MA, Dong MASCOLO, With the soaring adoption of in-ear wearables, the research community has started investigating suitable in-ear heart rate (HR) detection systems. HR is a key physiological marker of cardiovascular health and physical fitness. Continuous and reliable HR monitoring with wearable devices has therefore gained increasing attention in recent years. Existing HR detection systems in wearables mainly rely on photoplethysmography (PPG) sensors, however, these are notorious for poor performance in the presence of human motion. In this work, leveraging the occlusion effect that enhances low-frequency bone-conducted sounds in the ear canal, we investigate for the first time in-ear audio-based motion-resilient HR monitoring. We first collected HR-induced sounds in the ear canal leveraging an in-ear microphone under stationary and three different activities (i.e., walking, running, and speaking). Then, we devised a novel deep learning based motion artefact (MA) mitigation framework to denoise the in-ear audio signals, followed by an HR estimation algorithm to extract HR. With data collected from 20 subjects over four activities, we demonstrate that hEARt, our end-To-end approach, achieves a mean absolute error (MAE) of 3.02 2.97 BPM, 8.12 {6.74} BPM, 11.23 {9.20} BPM and 9.39 {6.97} BPM for stationary, walking, running and speaking, respectively, opening the door to a new non-invasive and affordable HR monitoring with usable performance for daily activities. Not only does hEARt outperform previous in-ear HR monitoring work, but it outperforms reported in-ear PPG performance 2023-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/8278 info:doi/10.1109/PERCOM56429.2023.10099317 https://ink.library.smu.edu.sg/context/sis_research/article/9281/viewcontent/hEART_Percom23.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Detection system Ear canal Earable Heart-rate Heart-rate detection Heart-rate monitoring In-ear audio Motion artifact Performance Research communities Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Detection system
Ear canal
Earable
Heart-rate
Heart-rate detection
Heart-rate monitoring
In-ear audio
Motion artifact
Performance
Research communities
Software Engineering
spellingShingle Detection system
Ear canal
Earable
Heart-rate
Heart-rate detection
Heart-rate monitoring
In-ear audio
Motion artifact
Performance
Research communities
Software Engineering
BUTKOW, Kayla-Jade
DANG, Ting
FERLINI, Andrea
MA, Dong
MASCOLO,
Heart: Motion-resilient heart rate monitoring with in-ear microphones
description With the soaring adoption of in-ear wearables, the research community has started investigating suitable in-ear heart rate (HR) detection systems. HR is a key physiological marker of cardiovascular health and physical fitness. Continuous and reliable HR monitoring with wearable devices has therefore gained increasing attention in recent years. Existing HR detection systems in wearables mainly rely on photoplethysmography (PPG) sensors, however, these are notorious for poor performance in the presence of human motion. In this work, leveraging the occlusion effect that enhances low-frequency bone-conducted sounds in the ear canal, we investigate for the first time in-ear audio-based motion-resilient HR monitoring. We first collected HR-induced sounds in the ear canal leveraging an in-ear microphone under stationary and three different activities (i.e., walking, running, and speaking). Then, we devised a novel deep learning based motion artefact (MA) mitigation framework to denoise the in-ear audio signals, followed by an HR estimation algorithm to extract HR. With data collected from 20 subjects over four activities, we demonstrate that hEARt, our end-To-end approach, achieves a mean absolute error (MAE) of 3.02 2.97 BPM, 8.12 {6.74} BPM, 11.23 {9.20} BPM and 9.39 {6.97} BPM for stationary, walking, running and speaking, respectively, opening the door to a new non-invasive and affordable HR monitoring with usable performance for daily activities. Not only does hEARt outperform previous in-ear HR monitoring work, but it outperforms reported in-ear PPG performance
format text
author BUTKOW, Kayla-Jade
DANG, Ting
FERLINI, Andrea
MA, Dong
MASCOLO,
author_facet BUTKOW, Kayla-Jade
DANG, Ting
FERLINI, Andrea
MA, Dong
MASCOLO,
author_sort BUTKOW, Kayla-Jade
title Heart: Motion-resilient heart rate monitoring with in-ear microphones
title_short Heart: Motion-resilient heart rate monitoring with in-ear microphones
title_full Heart: Motion-resilient heart rate monitoring with in-ear microphones
title_fullStr Heart: Motion-resilient heart rate monitoring with in-ear microphones
title_full_unstemmed Heart: Motion-resilient heart rate monitoring with in-ear microphones
title_sort heart: motion-resilient heart rate monitoring with in-ear microphones
publisher Institutional Knowledge at Singapore Management University
publishDate 2023
url https://ink.library.smu.edu.sg/sis_research/8278
https://ink.library.smu.edu.sg/context/sis_research/article/9281/viewcontent/hEART_Percom23.pdf
_version_ 1783955663625388032