Heartbeat detection and personal authentication using a 60 GHz Doppler sensor

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.

Authors

Institutions

Publication Details

Journal
Frontiers in Digital Health
Published
2025-08-21
DOI
https://doi.org/10.3389/fdgth.2025.1570144
Citations
1
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
0.67

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Heartbeat detection and personal authentication using a 60 GHz Doppler sensor

Hiroshi Kawaguchi, Tomoyuki Asano, Shintaro Izumi
1 citations
Frontiers in Digital Health
Non-Invasive Vital Sign Monitoring
0.67
article

Heartbeat detection and personal authentication using a 60 GHz Doppler sensor

Hiroshi Kawaguchi, Tomoyuki Asano, Shintaro Izumi
article en
1 citations

Abstract

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.

Frontiers in Digital HealthVol. 7
Kobe University (JP)
Japan Science and Technology Agency
Openalex Percentile: Top 28%
Non-Invasive Vital Sign Monitoring
0.67
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.