Non-Invasive Vital Sign Monitoring

Neueste Paper

• A Low-Power Wearable Respiratory Sensor for Non-Invasive Stress Monitoring

  Mohammad Hosseini, Hamed Khatounabadi, Mohammad Fakharzadeh · 7. August 2026

  Respiration provides a continuously available window into physiological state and behavior. However, monitoring it outside controlled settings remains challenging because a wearable system must capture small body deformations while remaining comfortable, low power, and robust to changes in posture a…

• Prototype-based Self-Supervised Multimodal Learning for PPG and Accelerometry Signals

  Wanting Mao, Maxwell A Xu, Harish Haresamudram, Mithun Saha, Santosh Kumar, James Matthew Rehg · 6. August 2026

  Modeling multi-modal time-series data is critical for capturing system-level dynamics, particularly in biosignals where modalities such as ECG, PPG, EDA, and accelerometry provide complementary perspectives on interconnected physiological processes. While recent self-supervised learning (SSL) advanc…

• Reassessing the Feasibility of PPG-Based Non-Invasive Blood Glucose Level Estimation

  Supraja Ramesh, Markus Neufeld, Michael K\"uttner, Tobias R\"oddiger, Michael Beigl · 4. August 2026

  Non-invasive blood glucose level (BGL) estimation from photoplethysmography (PPG) holds great promise for wearable health monitoring, but results across studies are hard to compare due to inconsistent datasets, data leakage, and non-standardized evaluation metrics. We present the first reproducible,…

• Single-Beat Cuffless Blood Pressure Estimation Using Ear-PPG and ECG with a Lightweight Hybrid Learning Framework

  Kindeep K. Dhatt, Tengyue Wu, Hanbang Hua, Yayun Du · 30. Juli 2026

  Continuous cuffless blood pressure (BP) monitoring remains challenging due to motion artifacts, physiological variability, and the limited robustness of conventional pulse transit time (PTT) models under dynamic conditions. Many prior approaches rely on multi-second windows to stabilize estimation, …

• Low-cost Embedded Breathing Rate Determination Using 802.15.4z IR-UWB Hardware for Remote Healthcare

  Anton Lambrecht, Stijn Luchie, Jaron Fontaine, Ben Van Herbruggen, Adnan Shahid, Eli De Poorter · 30. Juli 2026

  Respiratory diseases account for a significant portion of global mortality. Affordable and early detection is an effective way of addressing these ailments. To this end, a low-cost commercial off-the-shelf (COTS), IEEE 802.15.4z standard compliant impulse-radio ultra-wideband (IR-UWB) radar system i…

• Blood Pressure Estimation from PPG: A Comparative Study of Direct and ECG-Mediated Deep Learning Pipelines

  Bo Wu, Haoling Wang, Zhuodiao Kuang, Kateryna Shapovalenko · 28. Juli 2026

  Continuous cuffless blood pressure (BP) monitoring is essential for connected health systems and wearable devices, enabling early detection, longitudinal tracking, and personalized management of cardiovascular disease. Many prior approaches attempt to estimate BP indirectly by reconstructing electro…

• Physiological Signals as a Forensic Modality for Talking-Face Deepfake Detection

  Othmane Harraq, Tamer Aldwairi · 27. Juli 2026

  Talking-face (TF) deepfake generation synthesizes photore- alistic facial video from a static source image and an au- dio signal, producing forgeries that current image-based detectors consistently fail to identify. Unlike face-swap ma- nipulation, TF synthesis has no underlying real video from whic…

• Good Practice Guide for quantifying uncertainties for machine learning models applied to photoplethysmography signals

  P. Harris, C. Bench, M. Rinkevi\v{c}ius, V. Marozas, L. Coquelin, A. Thompson, M. Nandi, U. Hackstein, P. J. Aston · 23. Juli 2026

  This Good Practice Guide presents work done in the QUMPHY project (Uncertainty quantification for machine learning models applied to photoplethysmography signals) that considered both machine learning and uncertainty quantification for problems which used photoplethysmography (PPG) signals from wear…

• CanonicalPhys: Pose-Robust Remote Photoplethysmography via Canonical-Space Priors

  Hui Wei, Seyedata Jodeiri Seyedian, Xiaobai Li, Guoying Zhao · 20. Juli 2026

  Deep remote photoplethysmography (rPPG) attains sub-bpm heart-rate error on frontal, stationary faces yet degrades sharply under head pose: on MMPD, the state-of-the-art FactorizePhys backbone's MAE grows $1.60\times$ from frontal ($|\text{yaw}|{<}15^\circ$) to large-yaw ($|\text{yaw}|{\geq}45^\circ…

• SpO$_2$ Predictor-Guided Stage-Wise Time-Frequency Reconstruction of Low-Quality Dual-Wavelength PPG for Oxygen Saturation Estimation

  Zequan Liang, Elahe Hosseini, Ning Miao, Mahdi Pirayesh Shirazi Nejad, Wei Shao, Ehsan Kourkchi, Setareh Rafatirad, Houman Homayoun · 10. Juli 2026

  Continuous oxygen saturation (SpO$_2$) estimation from wearable photoplethysmography (PPG) is important for long-term health monitoring, but low-quality red and infrared PPG segments can distort waveform morphology and degrade SpO$_2$ prediction accuracy. Existing PPG denoising and reconstruction me…

• Non-contact, Real-time, Heart-rate Measurement using Image Processing with Commodity Cameras and AI Agents

  Kelly Li, Fulu Li · 9. Juli 2026

  Heart rate measurement is one of the key requirements for real-time health monitoring, in particular for health caring of elderly people. Traditional heart rate measurement relies on contact sensing mechanisms such as some heart rate measurement devices at medical hospitals or some wearable devices …

• Video-based detection of cessation of breathing in pre-term infants using machine learning

  Dineo Serame, Lionel Tarassenko, Mauricio Villarroel · 7. Juli 2026

  Pre-term infants are susceptible to potentially harmful apnoea-related cessations of breathing due to immature respiratory control. However, reliable respiratory monitoring in the neonatal intensive care unit (NICU) remains challenging because motion artefacts, sensor displacement, and skin fragilit…

• A Wearable Device Dataset for Mental Health Assessment Using Laser Doppler Flowmetry and Fluorescence Spectroscopy Sensors

  Minh Ngoc Nguyen, Khai Le-Duc, Tan-Hanh Pham, Trong Nhan Nguyen, Bailey Trang, Ba Kien Tran, Viktor Dremin, Sergei Sokolovsky, Edik Rafailov, Truong-Son Hy · 3. Juli 2026

  Mental health problems such as stress, anxiety, and depression affect millions of people worldwide. These conditions are usually assessed using questionnaires, which rely on how people describe their own feelings. In this study, we explore whether a wearable device can help measure mental health usi…

• Physically-Constrained Harmonic Separation for Robust Heart and Respiratory Rate Estimation from Wrist Photoplethysmography

  Nouhaila Fraihi, Ouassim Karrakchou, Mounir Ghogho · 30. Juni 2026

  Wrist-worn photoplethysmography (PPG) enables continuous monitoring of cardiopulmonary physiology, but reliable heart rate (HR) and respiratory rate (RR) estimation in free-living conditions remains challenging due to non-stationary motion artifacts that spectrally overlap with physiological dynamic…

• Deep learning-based detection of cessation of breathing in pre-term infants

  Dineo Serame, Lionel Tarassenko, Mauricio Villarroel · 23. Juni 2026

  Apnoea of prematurity is characterised by recurrent episodes of cessation of breathing and remains difficult to detect reliably using routinely monitored physiological signals in the Neonatal Intensive Care Unit (NICU). Existing bedside monitors rely primarily on respiratory rate and oxygen saturati…

• MS-rPPG: Multi-spectral State Space Model for Remote Photoplethysmography in Driver Monitoring Systems

  Jiho Choi, Sang Jun Lee · 23. Juni 2026

  Remote photoplethysmography (rPPG) is a camera-based technique for measuring physiological signals, particularly cardiac activity. From the remotely measured signals, heart rate can be estimated, which is crucial for health monitoring. In this study, we investigate a driver health monitoring system …

• CAP: Towards PPG Universal Representation Learning with Patient-level Supervision

  Chenyang He, Xinyi Shao, Shun Huang, Bosong Huang, Daoqiang Zhang, Ming Jing, Cheng Ding · 16. Juni 2026

  Photoplethysmography (PPG) plays a central role in wearable health monitoring and clinical decision support. Yet existing approaches to universal PPG representation learning largely focus on signal-level objectives and often overlook patient-level health context, which limits generalization to compl…

• An Exploratory Study of Blood Glucose Estimation from Photoplethysmography Signals using Machine Learning

  Ruhani Bhatia, Vijval Ekbote · 16. Juni 2026

  Diabetes and extreme blood sugar levels are some of the major health problems faced by humans today across the world. While Continuous Glucose Monitoring (CGM) has emerged as an effective technology for management of diabetes as well as for monitoring blood sugar levels, this technology has traditio…

• Explaining RhythmFormer: A Systematic XAI Analysis of Periodic Sparse Attention for Remote Photoplethysmography

  Louis Chen, Torbj\"orn E. M. Nordling · 15. Juni 2026

  Remote photoplethysmography (rPPG) transformers achieve low heart-rate error on benchmarks, yet their decisions remain opaque--a growing concern as rPPG moves toward clinical heart rate estimation. Existing rPPG XAI is dominated by qualitative heatmap inspection without quantitative faithfulness met…

• Illumination-Robust Camera-Based Heart-Rate Estimation for Physiological Sensing in Robots

  Zhi Wei Xu, Torbj\"orn E. M. Nordling · 11. Juni 2026

  Physiological awareness is important for service, social, and assistive robots that interact with humans in everyday environments. Remote photoplethysmography (rPPG) enables non-contact heart-rate (HR) estimation from an RGB camera, making it a promising sensing modality for robot-mounted vision sys…

• DMT: Demographic Conditioning, Morphology-Enhanced Transformer for Cuffless Blood Pressure Estimation from PPG Signals

  Yidan Shen, Neville Mathew, Maham Rahimi, Deependra Dhakal, George Zouridakis, Xin Fu, Renjie Hu · 10. Juni 2026

  Blood pressure (BP) is a key marker for cardiovascular risk assessment and therapeutic decision-making, and Photoplethysmography (PPG) enables low-cost, wearable-friendly cuffless BP estimation. However, even with recent progress, many PPG-based models are trained with BP regression alone and may re…

• BCG-FM: A Foundation Model for Ambient Cardiac Health Sensing

  Magnus Ruud Kjaer, Haejun Han, Ashish Neupane, David Q. Sun · 9. Juni 2026

  Foundation models for wearable biosignals have matched or exceeded supervised specialists across a range of clinical tasks, yet all rely on modalities that require deliberate user action--wearing a device or visiting a sleep lab. We introduce BCG-FM, the first foundation model for ambient mechanical…

• A robust PPG foundation model using multimodal physiological supervision

  Eloy Geenjaar, Vince Calhoun, Scott Daly, Gouthaman KV, Lie Lu, Trisha Mittal, Daniel P. Darcy · 8. Juni 2026

  Photoplethysmography (PPG), a non-invasive measure of changes in blood volume, is widely used in both wearable devices and clinical settings. Recent PPG foundation models either use open-source ICU datasets with pretraining paradigms that require curated data and thus complicate generalization to fi…

• A multimodal dataset of photoplethysmography and continuous behavioral responses to ASMR and nature videos

  Tushar Das, Daigo Hozaki, Koushlendra Kumar Singh, Hirohito M. Kondo · 2. Juni 2026

  Autonomous Sensory Meridian Response (ASMR) is a somatosensory phenomenon characterized by pleasant tingling sensations and cardiovascular slowing. However, ASMR research has been hindered by a dearth of standardized, open-access multimodal datasets. To address this limitation, we present REST-ASMR …

• Adaptive data selection improves wearable prediction under low baseline performance

  Ali Kargarandehkordi · 2. Juni 2026

  Adaptive sensing strategies that selectively sample data are increasingly used in wearable health systems to improve prediction performance under limited data budgets, yet their benefits across individuals remain poorly understood. Here, we evaluate adaptive selection of time windows for model train…