ArticleMicrosystems & nanoengineering2021
A two-stage amplified PZT sensor for monitoring lung and heart sounds in discharged pneumonia patients.
Article in Microsystems & nanoengineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 30 citations in OpenAlex.
- Broadband wearable acoustic sensing for continuous cardiopulmonary monitoring.Microsystems & nanoengineering · 2026Article
- Exceptional point-enhanced piezoelectric thermometry via anti-parity-time symmetry.Microsystems & nanoengineering · 2026Article
- Fabrication of Stretchable Piezoelectric Sensor with a Kirigami Design for Heart Sound Monitoring.Sensors (Basel, Switzerland) · 2025Article
- Topology in Biological Piezoelectric Materials.Advanced materials (Deerfield Beach, Fla.) · 2025Review
- Diaphragm Design for an Electret Microphone Stethoscope.IEEE sensors journal · 2025Article
- Emerging Wearable Acoustic Sensing Technologies.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- MEMS Acoustic Sensors: Charting the Path from Research to Real-World Applications.Micromachines · 2024Review
- MEMS and ECM Sensor Technologies for Cardiorespiratory Sound Monitoring-A Comprehensive Review.Sensors (Basel, Switzerland) · 2024Review
- Advances in Respiratory Monitoring: A Comprehensive Review of Wearable and Remote Technologies.Biosensors · 2024Review
- Health Monitoring via Heart, Breath, and Korotkoff Sounds by Wearable Piezoelectret Patches.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Electrostatic Acoustic Sensor with an Impedance-Matched Diaphragm Characterized for Body Sound Monitoring.ACS applied bio materials · 2023Article
- Soft Electronics for Health Monitoring Assisted by Machine Learning.Nano-micro letters · 2023Review
- An aerosol deposition based MEMS piezoelectric accelerometer for low noise measurement.Microsystems & nanoengineering · 2023Article
- An ultrahigh sensitivity acoustic sensor system for weak signal detection based on an ultrahigh-Microsystems & nanoengineering · 2023Article
- Review
- A Focused Review on the Flexible Wearable Sensors for Sports: From Kinematics to Physiologies.Micromachines · 2022Review
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Assessment of lung and heart states is of critical importance for patients with pneumonia. In this study, we present a small-sized and ultrasensitive accelerometer for continuous monitoring of lung and heart sounds to evaluate the lung and heart states of patients. Based on two-stage amplification, which consists of an asymmetric gapped cantilever and a charge amplifier, our accelerometer exhibited an extremely high ratio of sensitivity to noise compared with conventional structures. Our sensor achieves a high sensitivity of 9.2 V/g at frequencies less than 1000 Hz, making it suitable to use to monitor weak physiological signals, including heart and lung sounds. For the first time, lung injury, heart injury, and both lung and heart injuries in discharged pneumonia patients were revealed by our sensor device. Our sound sensor also successfully tracked the recovery course of the discharged pneumonia patients. Over time, the lung and heart states of the patients gradually improved after discharge. Our observations were in good agreement with clinical reports. Compared with conventional medical instruments, our sensor device provides rapid and highly sensitive detection of lung and heart sounds, which greatly helps in the evaluation of lung and heart states of pneumonia patients. This sensor provides a cost-effective alternative approach to the diagnosis and prognosis of pneumonia and has the potential for clinical and home-use health monitoring.
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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.