ReviewBiosensors2022
Mechanical Sensors for Cardiovascular Monitoring: From Battery-Powered to Self-Powered.
Review in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 23 citations in OpenAlex.
- Unobtrusive Sensing at Home Towards Healthcare 5.0: Technologies, Applications, and Future Directions.Biosensors · 2026Review
- Integrated Polymeric Sensors in Heart and Blood Vessel Monitoring: A Review.Sensors (Basel, Switzerland) · 2025Review
- Recent Advances in Micro- and Nano-Enhanced Intravascular Biosensors for Real-Time Monitoring, Early Disease Diagnosis, and Drug Therapy Monitoring.Sensors (Basel, Switzerland) · 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
- Recent Progress in Blood Flow Sensing.Sensors and actuators. A, Physical · 2025Article
- Enhancing output efficiency in self-powered hybrid nanogenerators with micro-pyramid surface design using ceramic/polymer film for flexible wearable electronic devices.RSC advances · 2025Article
- Effect of Sonication Batch on Electrical Properties of Graphitic-Based PVDF-HFP Strain Sensors for Use in Health Monitoring.Sensors (Basel, Switzerland) · 2024Article
- DiScO: novel rapid systems mapping to inform digital transformation of health systems.Frontiers in public health · 2024Article
- Wearable Two-Dimensional Nanomaterial-Based Flexible Sensors for Blood Pressure Monitoring: A Review.Nanomaterials (Basel, Switzerland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
Cardiovascular disease is one of the leading causes of death worldwide. Long-term and real-time monitoring of cardiovascular indicators is required to detect abnormalities and conduct early intervention in time. To this end, the development of flexible wearable/implantable sensors for real-time monitoring of various vital signs has aroused extensive interest among researchers. Among the different kinds of sensors, mechanical sensors can reflect the direct information of pressure fluctuations in the cardiovascular system with the advantages of high sensitivity and suitable flexibility. Herein, we first introduce the recent advances of four kinds of mechanical sensors for cardiovascular system monitoring, based on capacitive, piezoresistive, piezoelectric, and triboelectric principles. Then, the physio-mechanical mechanisms in the cardiovascular system and their monitoring are described, including pulse wave, blood pressure, heart rhythm, endocardial pressure, etc. Finally, we emphasize the importance of real-time physiological monitoring in the treatment of cardiovascular disease and discuss its challenges in clinical translation.
Indexed as
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.