ArticleNature biomedical engineering2023
Synchronized wearables for the detection of haemodynamic states via electrocardiography and multispectral photoplethysmography.
Article in Nature biomedical engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.
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Who cites it
45 citing papers in PubMed, 1 synthesis or guideline pooled it, 103 citations in OpenAlex.
- Wearable Blood Pressure Monitoring Devices: Understanding Heterogeneity in Design and Evaluation.IEEE transactions on bio-medical engineering · 2024Pooled it
- Fusing Wearable and Environmental Sensors for Context-Aware Firefighter Wellbeing Monitoring.Sensors (Basel, Switzerland) · 2026Article
- A unified mechano-ionic skin for resolving native electromechanical coupling.Nature communications · 2026Article
- Advances in cardiac devices and bioelectronics augmented with artificial intelligence.The Journal of physiology · 2026Review
- Wearable Sensing for Clinical Physiology Monitoring: Emerging Paradigms.Physiology (Bethesda, Md.) · 2026Review
- Wearable and Implantable Devices for Continuous Monitoring of Muscle Physiological Activity: A Review.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Artificial Intelligence-Enhanced Wearable Blood Pressure Monitoring in Resource-Limited Settings: A Co-Design of Sensors, Model, and Deployment.Nano-micro letters · 2026Review
- Smart Paper-Based Nanosensor for Simultaneous Environmental eMonitoring of Nitrate and Nitrite.ACS measurement science au · 2025Article
- A conformal piezoelectric microsystem for demographic-adaptive and calibration-free cuffless blood pressure monitoring.Nature communications · 2025Article
- Advances in Photonic Materials and Integrated Devices for Smart and Digital Healthcare: Bridging the Gap Between Materials and Systems.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Article
- AI-enhanced flexible ECG patch for accurate heart disease diagnosis, optimal wear positioning, and interactive medical consultation.National science review · 2025Article
- A textile-based alignment-free electrophysiological sensing sleeve for comprehensive cardiovascular monitoring.Microsystems & nanoengineering · 2025Article
- Artificial Intelligence for Cardiovascular Care in Action: From Learning to Implementation in Health Systems.JACC. Advances · 2025Review
- A Pilot Human Study on Dual Photoplethysmography for Continuously Monitoring Pulse Wave Velocity and Blood Pressure.IEEE journal on flexible electronics · 2025Article
- State-of-the-art wearable sensors for cardiovascular health: a review.NPJ cardiovascular health · 2025Review
- Continuous biosignal acquisition beyond the limit of epidermal turnover.Materials horizons · 2025Review
- Tactile-Transparent Wearable Sensor for Clinician-Friendly Pulse Wave Velocity Monitoring and Cardiovascular Risk Profiling.ACS nano · 2025Article
- Wearable blood pressure sensors for cardiovascular monitoring and machine learning algorithms for blood pressure estimation.Nature reviews. Cardiology · 2025Review
- Flexible Smart Insole and Plantar Pressure Monitoring Using Screen-Printed Nanomaterials and Piezoresistive Sensors.ACS applied materials & interfaces · 2025Article
Corrections and comments
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Authors and funding
17 authors at 5 institutions in 2 countries.
Funding
Abstract
Cardiovascular health is typically monitored by measuring blood pressure. Here we describe a wireless on-skin system consisting of synchronized sensors for chest electrocardiography and peripheral multispectral photoplethysmography for the continuous monitoring of metrics related to vascular resistance, cardiac output and blood-pressure regulation. We used data from the sensors to train a support-vector-machine model for the classification of haemodynamic states (resulting from exposure to heat or cold, physical exercise, breath holding, performing the Valsalva manoeuvre or from vasopressor administration during post-operative hypotension) that independently affect blood pressure, cardiac output and vascular resistance. The model classified the haemodynamic states on the basis of an unseen subset of sensor data for 10 healthy individuals, 20 patients with hypertension undergoing haemodynamic stimuli and 15 patients recovering from cardiac surgery, with an average precision of 0.878 and an overall area under the receiver operating characteristic curve of 0.958. The multinodal sensor system may provide clinically actionable insights into haemodynamic states for use in the management of cardiovascular disease.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.