research-article

CardiacWave: A mmWave-based Scheme of Non-Contact and High-Definition Heart Activity Computing

Authors:

Aditya Singh Rathore,

Ming-chun Huang,

Wenyao XuAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 5, Issue 3

Article No.: 135, Pages 1 - 26

https://doi.org/10.1145/3478127

Published: 14 September 2021 Publication History

Abstract

Using wireless signals to monitor human vital signs, especially heartbeat information, has been intensively studied in the past decade. This non-contact sensing modality can drive various applications from cardiac health, sleep, and emotion management. Under the circumstance of the COVID-19 pandemic, non-contact heart monitoring receives increasingly market demands. However, existing wireless heart monitoring schemes can only detect limited heart activities, such as heart rate, fiducial points, and Seismocardiography (SCG)-like information. In this paper, we present CardiacWave to enable a non-contact high-definition heart monitoring. CardiacWave can provide a full spectrum of Electrocardiogram (ECG)-like heart activities, including the details of P-wave, T-wave, and QRS complex. Specifically, CardiacWave is built upon the Cardiac-mmWave scattering effect (CaSE), which is a variable frequency response of the cardiac electromagnetic field under the mmWave interrogation. The CardiacWave design consists of a noise-resistant sensing scheme to interrogate CaSE and a cardiac activity profiling module for extracting cardiac electrical activities from the interrogation response. Our experiments show that the CardiacWave-induced ECG measures have a high positive correlation with the heart activity ground truth (i.e., measurements from a medical-grade instrument). The timing difference of P-waves, T-waves, and QRS complex is 0.67%, 0.71%, and 0.49%, respectively, and a mean cardiac event difference is within a delay of 5.3 milliseconds. These results indicate that CaridacWave offers high-fidelity and integral heart clinical characteristics. Furthermore, we evaluate the CardiacWave system with participants under various conditions, including heart and breath rates, ages, and heart habits (e.g., tobacco use).

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 5, Issue 3

Sept 2021

1443 pages

EISSN:2474-9567

DOI:10.1145/3486621

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Published: 14 September 2021

Published in IMWUT Volume 5, Issue 3

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