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Exploring the Feasibility of Remote Cardiac Auscultation Using Earphones

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Longfei ShangguanAuthors Info & Claims

ACM MobiCom '24: Proceedings of the 30th Annual International Conference on Mobile Computing and Networking

Pages 357 - 372

https://doi.org/10.1145/3636534.3649366

Published: 29 May 2024 Publication History

Abstract

The elderly over 65 accounts for 80% of COVID deaths in the United States. In response to the pandemic, the federal, state governments, and commercial insurers are promoting video visits, through which the elderly can access specialists at home over the Internet, without the risk of COVID exposure. However, the current video visit practice barely relies on video observation and talking. The specialist could not assess the patient's health conditions by performing auscultations.

This paper tries to address this key missing component in video visits by proposing Asclepius, a hardware-software solution that turns the patient's earphones into a stethoscope, allowing the specialist to hear the patient's fine-grained heart sound (i.e., PCG signals) in video visits. To achieve this goal, we contribute a low-cost plug-in peripheral that repurposes the earphone's speaker into a microphone and uses it to capture the patient's minute PCG signals from her ear canal. As the PCG signals suffer from strong attenuation and multi-path effects when propagating from the heart to ear canals, we then propose efficient signal processing algorithms coupled with a data-driven approach to de-reverberate and further correct the amplitude and frequency distortion in raw PCG receptions. We implement Asclepius on a 2-layer PCB board and follow the IRB protocol to evaluate its performance with 30 volunteers. Our extensive experiments show that Asclepius can effectively recover Phonocardiogram (PCG) signals with different types of earphones. The objective blind testing and subjective interview with five cardiologists further confirm the clinical efficacy and efficiency of our system. PCG signal samples, benchmark results, and cardiologist interviews can be found at: https://asclepius-system.github.io/

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Cited By

Parikh VMahmud SAgarwal DLi KGuimbretière FZhang CKostakos VKay JHoang T(2024)EchoGuide: Active Acoustic Guidance for LLM-Based Eating Event Analysis from Egocentric VideosProceedings of the 2024 ACM International Symposium on Wearable Computers10.1145/3675095.3676611(40-47)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675095.3676611
Christofferson KBhalla SCafazzo JMariakakis AKostakos VKay JHoang T(2024)On the Production and Measurement of Cardiac Sounds in the Ear CanalCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3680526(685-690)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675094.3680526
Chen TYang YQiu CFan XGuo XShangguan LOkoshi TKo JLiKamWa R(2024)Enabling Hands-Free Voice Assistant Activation on EarphonesProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661890(155-168)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3643832.3661890

Index Terms

Exploring the Feasibility of Remote Cardiac Auscultation Using Earphones
1. Applied computing
  1. Life and medical sciences
    1. Consumer health
2. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools

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cover image ACM Conferences

ACM MobiCom '24: Proceedings of the 30th Annual International Conference on Mobile Computing and Networking

December 2024

2476 pages

ISBN:9798400704895

DOI:10.1145/3636534

Chair:
Weisong Shi,
Program Chairs:
Deepak Ganesan,
Nicholas Lane

This work is licensed under a Creative Commons Attribution International 4.0 License.

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Published: 29 May 2024

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ACM MobiCom '24: 30th Annual International Conference on Mobile Computing and Networking

November 18 - 22, 2024

DC, Washington D.C., USA

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Cited By

Parikh VMahmud SAgarwal DLi KGuimbretière FZhang CKostakos VKay JHoang T(2024)EchoGuide: Active Acoustic Guidance for LLM-Based Eating Event Analysis from Egocentric VideosProceedings of the 2024 ACM International Symposium on Wearable Computers10.1145/3675095.3676611(40-47)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675095.3676611
Christofferson KBhalla SCafazzo JMariakakis AKostakos VKay JHoang T(2024)On the Production and Measurement of Cardiac Sounds in the Ear CanalCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3680526(685-690)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675094.3680526
Chen TYang YQiu CFan XGuo XShangguan LOkoshi TKo JLiKamWa R(2024)Enabling Hands-Free Voice Assistant Activation on EarphonesProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661890(155-168)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3643832.3661890

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