相关论文: VIPL-HR: A Multi-modal Database for Pulse Estimati…
Longitudinal monitoring of heart rate (HR) and heart rate variability (HRV) can aid in tracking cardiovascular diseases (CVDs), sleep quality, sleep disorders, and reflect autonomic nervous system activity, stress levels, and overall…
Facial motion capture in mixed reality headsets enables real-time avatar animation, allowing users to convey non-verbal cues during virtual interactions. However, as facial motion data constitutes a behavioral biometric, its use raises…
Understanding how humans interact with each other is key to building realistic multi-human virtual reality systems. This area remains relatively unexplored due to the lack of large-scale datasets. Recent datasets focusing on this issue…
Remote Photoplethysmography (rPPG), or the remote monitoring of a subject's heart rate using a camera, has seen a shift from handcrafted techniques to deep learning models. While current solutions offer substantial performance gains, we…
Remote photoplethysmography (rPPG) allows for the contactless estimation of physiological signals from facial videos by analyzing subtle skin color changes. However, rPPG signals are extremely susceptible to illumination changes, motion,…
Oscillometric monitors are the most common automated blood pressure (BP) measurement devices used in non-specialist settings. However, their accuracy and reliability vary under different settings and for different age groups and health…
In this study, we make non-invasive, remote, passive measurements of the heart beat frequency and determine the map of blood pulsation intensity in a region of interest (ROI) of skin. The ROI used was the forearm of a volunteer. The method…
Camera-based physiological measurement is a fast growing field of computer vision. Remote photoplethysmography (rPPG) utilizes imaging devices (e.g., cameras) to measure the peripheral blood volume pulse (BVP) via photoplethysmography, and…
Heart rate (HR) and its variability (HRV) has been proposed as a marker for depressive symptoms and other aspects of mental health. However, the real correlation between them is presently uncertain, as previous studies have generally been…
This study creates a physiologically realistic virtual patient database (VPD), representing the human arterial system, for the primary purpose of studying the affects of arterial disease on haemodynamics. A low dimensional representation of…
We present the Deception Detection and Physiological Monitoring (DDPM) dataset and initial baseline results on this dataset. Our application context is an interview scenario in which the interviewee attempts to deceive the interviewer on…
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…
Auscultation, particularly heart sound, is a non-invasive technique that provides essential vital sign information. Recently, self-supervised acoustic representation foundation models (FMs) have been proposed to offer insights into…
Human Mesh Recovery (HMR) from an image is a challenging problem because of the inherent ambiguity of the task. Existing HMR methods utilized either temporal information or kinematic relationships to achieve higher accuracy, but there is no…
Chest X-ray images are commonly used for predicting acute and chronic cardiopulmonary conditions, but efforts to integrate them with structured clinical data face challenges due to incomplete electronic health records (EHR). This paper…
This paper presents a robust method to monitor heart rate (HR) from BCG (Ballistocardiography) signal, which is acquired from the sensor embedded in a chair or a mattress. The proposed algorithm addresses the shortfalls in traditional Fast…
Recent studies showed that Photoplethysmography (PPG) sensors embedded in wearable devices can estimate heart rate (HR) with high accuracy. However, despite of prior research efforts, applying PPG sensor based HR estimation to embedded…
Electronic health record (EHR) data is sparse and irregular as it is recorded at irregular time intervals, and different clinical variables are measured at each observation point. In this work, we propose a multi-view features integration…
Camera-based vital signs monitoring in recent years has attracted more and more researchers and the results are promising. However, a few research works focus on heart rate extraction under extremely low illumination environments. In this…
Precise measurement of physiological signals is critical for the effective monitoring of human vital signs. Recent developments in computer vision have demonstrated that signals such as pulse rate and respiration rate can be extracted from…