ReviewRSC advances2023
Recent development of piezoelectric biosensors for physiological signal detection and machine learning assisted cardiovascular disease diagnosis.
Review in RSC advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 44 citations in OpenAlex.
- Review
- Potential biomarkers and their recent applications ofr point-of-care biosensors for the diagnosis of malaria.Mikrochimica acta · 2026Review
- Transforming Coagulation Testing: The Role of Biosensors in Prothrombin Time (PT) Measurement.ACS omega · 2026Review
- Wearable technology for athletes: material innovations, performance monitoring, and emerging paradigms.Mikrochimica acta · 2026Review
- Fabrication of Stretchable Piezoelectric Sensor with a Kirigami Design for Heart Sound Monitoring.Sensors (Basel, Switzerland) · 2025Article
- Detection of Atrial Fibrillation Using Multi-Site Ballistocardiogram with Piezoelectric Rubber Sheet Sensors.Sensors (Basel, Switzerland) · 2025Article
- Next-Generation Piezoelectric Materials in Wearable and Implantable Devices for Continuous Physiological Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Point-of-care biosensors for infectious disease diagnosis: recent updates and prospects.RSC advances · 2025Review
- A Dual-Modal Wearable Pulse Detection System Integrated with Deep Learning for High-Accuracy and Low-Power Sleep Apnea Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Biosensors, Artificial Intelligence Biosensors, False Results and Novel Future Perspectives.Diagnostics (Basel, Switzerland) · 2025Review
- Leveraging innovative diagnostics as a tool to contain superbugs.Antonie van Leeuwenhoek · 2025Review
- Analysis of Personalized Cardiovascular Drug Therapy: From Monitoring Technologies to Data Integration and Future Perspectives.Biosensors · 2025Review
- Synergistic integration of energy harvesters and supercapacitors for enhanced performance.Heliyon · 2025Article
- Innovations in Biosensor Technologies for Healthcare Diagnostics and Therapeutic Drug Monitoring: Applications, Recent Progress, and Future Research Challenges.Sensors (Basel, Switzerland) · 2024Review
- Bioelectrochemical biosensors for water quality assessment and wastewater monitoring.Open life sciences · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As cardiovascular disease stands as a global primary cause of mortality, there has been an urgent need for continuous and real-time heart monitoring to effectively identify irregular heart rhythms and to offer timely patient alerts. However, conventional cardiac monitoring systems encounter challenges due to inflexible interfaces and discomfort during prolonged monitoring. In this review article, we address these issues by emphasizing the recent development of the flexible, wearable, and comfortable piezoelectric passive sensor assisted by machine learning technology for diagnosis. This innovative device not only harmonizes with the dynamic mechanical properties of human skin but also facilitates continuous and real-time collection of physiological signals. Addressing identified challenges and constraints, this review provides insights into recent advances in piezoelectric cardiac sensors, from devices to circuit systems. Furthermore, this review delves into the integration of machine learning technologies, showcasing their pivotal role in facilitating continuous and real-time assessment of cardiac status. The synergistic combination of flexible piezoelectric sensor design and machine learning holds substantial potential in automating the detection of cardiac irregularities with minimal human intervention. This transformative approach has the power to revolutionize patient care paradigms.
Identifiers
What OpenQuestion holds
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.