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Depth cameras are an interesting modality for capturing vital signs such as respiratory rate. Plenty approaches exist to extract vital signs in a controlled setting, but in order to apply them more flexibly for example in multi-camera…

计算机视觉与模式识别 · 计算机科学 2024-11-18 Maurice Rohr , Sebastian Dill

Remote Photoplethysmography (rPPG) aims to measure physiological signals and Heart Rate (HR) from facial videos. Recent unsupervised rPPG estimation methods have shown promising potential in estimating rPPG signals from facial regions…

计算机视觉与模式识别 · 计算机科学 2025-04-29 Pei-Kai Huang , Tzu-Hsien Chen , Ya-Ting Chan , Kuan-Wen Chen , Chiou-Ting Hsu

Continuous monitoring of respiratory activity is desirable in many clinical applications to detect respiratory events. Non-contact monitoring of respiration can be achieved with near- and far-infrared spectrum cameras. However, current…

信号处理 · 电气工程与系统科学 2020-06-02 Gaetano Scebba , Giulia Da Poian , Walter Karlen

Camera-based contactless photoplethysmography refers to a set of popular techniques for contactless physiological measurement. The current state-of-the-art neural models are typically trained in a supervised manner using videos accompanied…

计算机视觉与模式识别 · 计算机科学 2022-04-25 Xin Liu , Yuntao Wang , Sinan Xie , Xiaoyu Zhang , Zixian Ma , Daniel McDuff , Shwetak Patel

This paper presents a novel method for remote heart rate (HR) estimation. Recent studies have proved that blood pumping by the heart is highly correlated to the intense color of face pixels, and surprisingly can be utilized for remote HR…

计算机视觉与模式识别 · 计算机科学 2020-02-13 Mohammad Sabokrou , Masoud Pourreza , Xiaobai Li , Mahmood Fathy , Guoying Zhao

Photoplethysmography (PPG) sensors allow for non-invasive and comfortable heart-rate (HR) monitoring, suitable for compact wrist-worn devices. Unfortunately, Motion Artifacts (MAs) severely impact the monitoring accuracy, causing high…

Remote photoplethysmography (rPPG) is an attractive method for noninvasive, convenient and concomitant measurement of physiological vital signals. Public benchmark datasets have served a valuable role in the development of this technology…

计算机视觉与模式识别 · 计算机科学 2023-05-02 Jiankai Tang , Kequan Chen , Yuntao Wang , Yuanchun Shi , Shwetak Patel , Daniel McDuff , Xin Liu

Cardiac abnormalities affecting heart rate and rhythm are commonly observed in both healthy and acutely unwell people. Although many of these are benign, they can sometimes indicate a serious health risk. ECG monitors are typically used to…

信号处理 · 电气工程与系统科学 2018-07-12 Stewart Whiting , Samuel Moreland , Jason Costello , Glen Colopy , Christopher McCann

Objective- Heart rate monitoring using wrist type Photoplethysmographic (PPG) signals is getting popularity because of construction simplicity and low cost of wearable devices. The task becomes very difficult due to the presence of various…

Analyzing the cardiovascular system condition via Electrocardiography (ECG) is a common and highly effective approach, and it has been practiced and perfected over many decades. ECG sensing is non-invasive and relatively easy to acquire,…

Photoplethysmography (PPG) sensor in wearable and clinical devices provides valuable physiological insights in a non-invasive and real-time fashion. Specialized Foundation Models (FM) or repurposed time-series FMs are used to benchmark…

计算机视觉与模式识别 · 计算机科学 2025-10-14 Saurabh Kataria , Ayca Ermis , Lovely Yeswanth Panchumarthi , Minxiao Wang , Xiao Hu

Non-contact remote photoplethysmography (rPPG) technology enables heart rate measurement from facial videos. However, existing network models still face challenges in accu racy, robustness, and generalization capability under complex…

计算机视觉与模式识别 · 计算机科学 2025-07-11 Kang Cen , Chang-Hong Fu , Hong Hong

Digital twins for 1D bio-signals enable real-time monitoring of physiological processes of a person, which enables early disease diagnosis and personalized treatment. This work introduces a novel non-contact method for digital twin (DT)…

Vital sign monitoring plays a critical role in healthcare and well-being, as parameters such as respiration and heart rate offer valuable insights into an individual's physiological state. While wearable devices allow for continuous…

信号处理 · 电气工程与系统科学 2025-09-15 Christian Eckrich , Abdelhak M. Zoubir , Vahid Jamali

Camera-based physiological measurement is a growing field with neural models providing state-the-art-performance. Prior research have explored various "end-to-end" models; however these methods still require several preprocessing steps.…

计算机视觉与模式识别 · 计算机科学 2022-12-20 Xin Liu , Brian L. Hill , Ziheng Jiang , Shwetak Patel , Daniel McDuff

Photoplethysmography (PPG) is a widely used non-invasive physiological sensing technique, suitable for various clinical applications. Such clinical applications are increasingly supported by machine learning methods, raising the question of…

Remote photoplethysmography (rPPG) based on traditional frame-based cameras often struggles with motion artifacts and limited temporal resolution. To address these limitations, we introduce EMPD (Event-based Multimodal Physiological…

信号处理 · 电气工程与系统科学 2026-03-31 Qian Feng , Pengfei Li , Rongshan Gao , Jiale Xu , Rui Gong , Yidi Li

Remote Photoplethysmography (rPPG) is the process of estimating PPG from facial videos. While this approach benefits from contactless interaction, it is reliant on videos of faces, which often constitutes an important privacy concern.…

计算机视觉与模式识别 · 计算机科学 2023-06-05 Divij Gupta , Ali Etemad

Photoplethysmography (PPG) is a cost-effective and non-invasive technique that utilizes optical methods to measure cardiac physiology. PPG has become increasingly popular in health monitoring and is used in various commercial and clinical…

机器学习 · 计算机科学 2024-06-13 Khuong Vo , Mostafa El-Khamy , Yoojin Choi

Multi-point vital sign monitoring is essential for providing detailed insights into physiological changes. Traditional single-sensor approaches are inadequate for capturing multi-point vibrations. Existing contact-based solutions, while…

硬件体系结构 · 计算机科学 2024-11-15 Wei Ren , Jiannong Cao , Huansheng Yi , Kaiyue Hou , Miaoyang Hu , Jianqi Wang , Fugui Qi