ArticleNature communications2025
Multi-point sensing organic light-emitting diode display based mobile cardiovascular monitor.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A Single OLED With Hybrid Synaptic Plasticity Enabling In Situ Neuromorphic Processing and Visualization.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- Wearable Flexible Sensors for Cardiovascular Disease Monitoring.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Low-frequency ionic-electronic coupling for energy-efficient noise-resilient wireless bioelectronics.Nature communications · 2026Article
Corrections and comments
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiovascular diseases are the major cause of death globally and require ubiquitous monitoring due to their asymptomatic yet modifiable nature. Photoplethysmography is an effective optical sensing technique for non-invasive health monitoring. However, its reliance on the current relatively large and rigid inorganic semiconductor-based light-emitting diodes and silicon photodiodes hampers high-resolution integration thus restricts a sensing from single measurement point. So, it limits detectable biomarkers to monitor cardiovascular diseases in a ubiquitous manner. In order to facilitate, here we report a single smartphone type multi-functional cardiovascular health monitor based on the massive array of organic photodiodes integrated into the most user interactive display device. Therefore, we achieved: 1) multi-point concurrent photoplethysmography and high-resolution dynamic image sensing, and 2) user-interactive sensing within the large display area. These advancements enabled new functions, including high-accuracy screening for cardiovascular diseases, blood pressure monitoring from both fingers, monitoring of finger blood vessels and flow dynamics, and single-device-based biofeedback. Applied machine learning enhanced diagnostic accuracy, with pilot studies showing results comparable to medical-grade devices. As a result, we believe smartphones harnessing the sensor organic light-emitting diode display could evolve into mobile health monitors and digital therapeutics thus revolutionizing diagnostic and treatment.
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Registered trials
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