User Authentication and Vital Signs Extraction from Low-Frame-Rate and Monochrome No-contact Fingerprint Captures
원문 초록
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.
함께 살펴볼 논문
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KID-PPG: Knowledge Informed Deep Learning for Extracting Heart Rate from a Smartwatch
ALPHA: AnomaLous Physiological Health Assessment Using Large Language Models
TAU: Modeling Temporal Consistency Through Temporal Attentive U-Net for PPG Peak Detection
WildPPG: A Real-World PPG Dataset of Long Continuous Recordings
EnhancePPG: Improving PPG-based Heart Rate Estimation with Self-Supervision and Augmentation
Remote Heart Rate Monitoring in Smart Environments from Videos with Self-supervised Pre-training
토론
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