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20212025
most citedrPPG-Toolbox: Deep Remote PPG Toolbox

21 citations · 52 across the 19 of their papers we have counts for

collaborators

19 papers

cs.CV2025

FacePhys: State of the Heart Learning

Kegang Wang, Jiankai Tang, Yuntao Wang +5

Vital sign measurement using cameras presents opportunities for comfortable, ubiquitous health monitoring. Remote photoplethysmography (rPPG), a foundational technology, enables ca…

cs.CV2025

M3PD Dataset: Dual-view Photoplethysmography (PPG) Using Front-and-rear Cameras of Smartphones in Lab and Clinical Settings

Jiankai Tang, Tao Zhang, Jia Li +10

Portable physiological monitoring is essential for early detection and management of cardiovascular disease, but current methods often require specialized equipment that limits acc…

cs.CE2025

τ-Ring: A Smart Ring Platform for Multimodal Physiological and Behavioral Sensing

Jiankai Tang, Zhe He, Mingyu Zhang +5

Smart rings have emerged as uniquely convenient devices for continuous physiological and behavioral sensing, offering unobtrusive, constant access to metrics such as heart rate, mo…

cs.CE2025

Contact Sensors to Remote Cameras: Quantifying Cardiorespiratory Coupling in High-Altitude Exercise Recovery

Jiankai Tang, Meng Kang, Yiru Zhang +5

Cardiorespiratory coupling (CRC) captures the dynamic interaction between the cardiac and respiratory systems--an interaction strengthened by physical exercise and linked to improv…

cs.AI2025

PhysDrive: A Multimodal Remote Physiological Measurement Dataset for In-vehicle Driver Monitoring

Jiyao Wang, Xiao Yang, Qingyong Hu +6

Robust and unobtrusive in-vehicle physiological monitoring is crucial for ensuring driving safety and user experience. While remote physiological measurement (RPM) offers a promisi…

cs.CV2025

Non-Contact Health Monitoring During Daily Personal Care Routines

Xulin Ma, Jiankai Tang, Zhang Jiang +7

Remote photoplethysmography (rPPG) enables non-contact, continuous monitoring of physiological signals and offers a practical alternative to traditional health sensing methods. Alt…

cs.CV2025

Memory-efficient Low-latency Remote Photoplethysmography through Temporal-Spatial State Space Duality

Kegang Wang, Jiankai Tang, Yuxuan Fan +3

Remote photoplethysmography (rPPG), enabling non-contact physiological monitoring through facial light reflection analysis, faces critical computational bottlenecks as deep learnin…

cs.CE2025

Camera Measurement of Blood Oxygen Saturation

Jiankai Tang, Xin Liu, Daniel McDuff +11

Blood oxygen saturation (SpO2) is a crucial vital sign routinely monitored in medical settings. Traditional methods require dedicated contact sensors, limiting accessibility and co…

eess.IV2024

A Plug-and-Play Temporal Normalization Module for Robust Remote Photoplethysmography

Kegang Wang, Jiankai Tang, Yantao Wei +3

Remote photoplethysmography (rPPG) extracts PPG signals from subtle color changes in facial videos, showing strong potential for health applications. However, most rPPG methods rel…

cs.CV2024

Summit Vitals: Multi-Camera and Multi-Signal Biosensing at High Altitudes

Ke Liu, Jiankai Tang, Zhang Jiang +4

Video photoplethysmography (vPPG) is an emerging method for non-invasive and convenient measurement of physiological signals, utilizing two primary approaches: remote video PPG (rP…

cs.CV2024★ 1 cited

Camera-Based Remote Physiology Sensing for Hundreds of Subjects Across Skin Tones

Jiankai Tang, Xinyi Li, Jiacheng Liu +3

Remote photoplethysmography (rPPG) emerges as a promising method for non-invasive, convenient measurement of vital signs, utilizing the widespread presence of cameras. Despite adva…

cs.CV2024

Spiking-PhysFormer: Camera-Based Remote Photoplethysmography with Parallel Spike-driven Transformer

Mingxuan Liu, Jiankai Tang, Yongli Chen +7

Artificial neural networks (ANNs) can help camera-based remote photoplethysmography (rPPG) in measuring cardiac activity and physiological signals from facial videos, such as pulse…

eess.IV2023★ 1 cited

A Comprehensive Dataset and Automated Pipeline for Nailfold Capillary Analysis

Linxi Zhao, Jiankai Tang, Dongyu Chen +5

Nailfold capillaroscopy is widely used in assessing health conditions, highlighting the pressing need for an automated nailfold capillary analysis system. In this study, we present…

cs.LG2023★ 1 cited

ALPHA: AnomaLous Physiological Health Assessment Using Large Language Models

Jiankai Tang, Kegang Wang, Hongming Hu +4

This study concentrates on evaluating the efficacy of Large Language Models (LLMs) in healthcare, with a specific focus on their application in personal anomalous health monitoring…

cs.CV2023★ 3 cited

Camera-Based HRV Prediction for Remote Learning Environments

Kegang Wang, Yantao Wei, Jiankai Tang +5

In recent years, due to the widespread use of internet videos, remote photoplethysmography (rPPG) has gained more and more attention in the fields of affective computing. Restoring…

cs.CV2023★ 1 cited

MMPD: Multi-Domain Mobile Video Physiology Dataset

Jiankai Tang, Kequan Chen, Yuntao Wang +4

Remote photoplethysmography (rPPG) is an attractive method for noninvasive, convenient and concomitant measurement of physiological vital signals. Public benchmark datasets have se…

cs.CV2022★ 21 cited

rPPG-Toolbox: Deep Remote PPG Toolbox

Xin Liu, Girish Narayanswamy, Akshay Paruchuri +7

Camera-based physiological measurement is a fast growing field of computer vision. Remote photoplethysmography (rPPG) utilizes imaging devices (e.g., cameras) to measure the periph…

cs.CV2022★ 20 cited

MobilePhys: Personalized Mobile Camera-Based Contactless Physiological Sensing

Xin Liu, Yuntao Wang, Sinan Xie +4

Camera-based contactless photoplethysmography refers to a set of popular techniques for contactless physiological measurement. The current state-of-the-art neural models are typica…

cs.HC2021★ 4 cited

SplitSR: An End-to-End Approach to Super-Resolution on Mobile Devices

Xin Liu, Yuang Li, Josh Fromm +4

Super-resolution (SR) is a coveted image processing technique for mobile apps ranging from the basic camera apps to mobile health. Existing SR algorithms rely on deep learning mode…