Your new experience awaits. Try the new design now and help us make it even better

ORIGINAL RESEARCH article

Front. Digit. Health

Sec. Connected Health

Volume 7 - 2025 | doi: 10.3389/fdgth.2025.1570144

This article is part of the Research TopicUnconscious Monitoring of Physiological Information for Behavioral Changes in Daily Life: Advances in Sensor Technology and Data AnalysisView all 6 articles

Heartbeat detection and personal authentication using a 60 GHz Doppler sensor

Provisionally accepted
  • Graduate School of Science, Technology and Innovation, Kobe University, Kobe, Japan

The final, formatted version of the article will be published soon.

Background: Microwave Doppler sensors, capable of detecting minute physiological movements, enable the measurement of biometric information, such as walking patterns, heart rate, and respiration. Unlike fingerprint and facial recognition systems, they offer authentication without physical contact or privacy concerns. This study focuses on non-contact seismocardiography using microwave Doppler sensors and aims to apply this technology for biometric authentication.We proposed a method for authenticating and identifying heartbeat signals through supervised learning using a conditional variational autoencoder (CVAE). A 60 GHz microwave Doppler sensor was used to capture heartbeat signals, which were processed using a conformer network to detect peaks and segment individual beats. High signal-to-noise ratio waveforms were selected, and time-frequency analysis extracted relevant features. Spectrograms labeled with subject data were input into the CVAE, which encoded subject-specific features into a latent space for authentication.The proposed heartbeat-based authentication method, validated on 13 subjects, achieved an average balanced accuracy of 97.3% for authentication and an average accuracy of 94.7% for identification. Compared with conventional methods, this approach demonstrated superior performance by effectively encoding subject-specific features while mitigating noise-related challenges.The proposed method enhanced the feasibility of non-contact heartbeat-based authentication by achieving high accuracy while addressing noise-related challenges. Its application could improve biometric security without compromising user privacy. Further advancements in handling posture variations and scalability are essential for real-world implementation.

Keywords: Biometric authentication, Conditional variational autoencoder (CVAE), heartbeat, microwave Doppler sensor, Non-contact measurement

Received: 03 Feb 2025; Accepted: 04 Aug 2025.

Copyright: © 2025 Asano, Izumi and kawaguchi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Takuma Asano, Graduate School of Science, Technology and Innovation, Kobe University, Kobe, Japan

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.