User Authentication and Vital Signs Extraction from Low-Frame-Rate and Monochrome No-Contact Fingerprint Captures

We present our work on leveraging low-frame-rate monochrome (blue light) videos of fingertips, captured with an off-the-shelf fingerprint capture device, to extract vital signs and identify users. These videos utilize photoplethysmography (PPG), commonly used to measure vital signs like heart rate. While prior research predominantly utilizes high-frame-rate, multi-wavelength PPG sensors (e.g., infrared, red, or RGB), our preliminary findings demonstrate that both user identification and vital sign extraction are achievable with the low-frame-rate data we collected. Preliminary results are promising, with low error rates for both heart rate estimation and user authentication. These results indicate promise for effective biometric systems. We anticipate further optimization will enhance accuracy and advance healthcare and security.

Authors

Institutions

Publication Details

Published
2024-10-27
DOI
https://doi.org/10.1109/ieeeconf60004.2024.10942696
Citations
1
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

User Authentication and Vital Signs Extraction from Low-Frame-Rate and Monochrome No-Contact Fingerprint Captures

Logan Drake, Masudul H. Imtiaz, Mahesh K. Banavar, Naveenkumar G Venkataswamy et al.
1 citations
Biometric Identification and Security
0.35
article

User Authentication and Vital Signs Extraction from Low-Frame-Rate and Monochrome No-Contact Fingerprint Captures

Logan Drake, Masudul H. Imtiaz, Mahesh K. Banavar, Naveenkumar G Venkataswamy, Olaoluwayimika Olugbenle, Afiquer Rahman, Yemi Afolayanka
article en
1 citations

Abstract

We present our work on leveraging low-frame-rate monochrome (blue light) videos of fingertips, captured with an off-the-shelf fingerprint capture device, to extract vital signs and identify users. These videos utilize photoplethysmography (PPG), commonly used to measure vital signs like heart rate. While prior research predominantly utilizes high-frame-rate, multi-wavelength PPG sensors (e.g., infrared, red, or RGB), our preliminary findings demonstrate that both user identification and vital sign extraction are achievable with the low-frame-rate data we collected. Preliminary results are promising, with low error rates for both heart rate estimation and user authentication. These results indicate promise for effective biometric systems. We anticipate further optimization will enhance accuracy and advance healthcare and security.

Clarkson University (US)
Openalex Percentile: Top 38%
Biometric Identification and Security
0.35
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.

User Authentication and Vital Signs Extraction from Low-Frame-Rate and Monochrome No-Contact Fingerprint Captures — Logan Drake, Masudul H. Imtiaz, et al. · (2024) | TGRS Research Map | TGRS