PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 2, 20260 citationsOpen Access

Acoustic Bubble Sensing Techniques and Bioapplications

View Full Paper
RNRenjie NingJFJonathan FaulknerMWMengren Wu

Key Points

  • This review aims to explore the mechanics and applications of acoustic bubbles as sensors in biomedical contexts.
  • Summarized the physics of bubble dynamics.
  • Described the conversion of bubble dynamics into measurable sensing signals.
  • Highlighted practical applications in hemodynamic pressure, fluid rheology, and cellular mechanics.
  • Acoustic bubbles show high sensitivity due to nonlinear dynamics.
  • Demonstrated non-invasive and wireless detection methods.
  • Highlighted clinical applications for pressure, oxygenation, and tissue mechanics measurement.

Abstract

Acoustic bubbles are emerging as powerful microscale sensors that convert local biochemical and biomechanical cues into measurable signals in a remote, label-free, and clinically compatible manner. Originally developed as vascular contrast agents, microbubbles are now engineered so that their resonance frequency, nonlinear oscillations, cavitation emissions, microstreaming, and radiation-force-induced motion encode information about pressure, rheology, oxygenation, and cell or tissue mechanics. In this review, we first summarize the fundamental physics of bubble dynamics, and then describe how these dynamics are translated into practical sensing observables. We then highlight key bioapplications where acoustic bubbles function as environment-responsive probes, ranging from hemodynamic pressure and fluid rheology to oxygen levels and cellular mechanics. Across these examples, we emphasize advantages such as non-invasive and wireless readout, high sensitivity arising from nonlinear bubble dynamics, and biochemical and molecular tunability. Finally, we outline current challenges and future opportunities for translating acoustic bubble-based sensing into robust, quantitative tools for biomedical applications.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Ning et al. (2026) studied this question.

synapsesocial.com/papers/6980ffd6c1c9540dea81298ehttps://doi.org/10.3390/bios16020088
Ask AI
Helpful
Bookmark
Share
View Full Paper