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Updated: Nov 2, 2025

Assessment of Cardiac Morphological and Functional Changes in Mouse Model of Transverse Aortic Constriction by Echocardiographic Imaging
09:05

Assessment of Cardiac Morphological and Functional Changes in Mouse Model of Transverse Aortic Constriction by Echocardiographic Imaging

Published on: June 21, 2016

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Recent Advances in Seismocardiography

Amirtahà Taebi1,2, Brian E Solar2, Andrew J Bomar2,3

  • 1Department of Biomedical Engineering, University of California Davis, One Shields Ave, Davis, CA 95616, USA.

Vibration
|June 11, 2021
PubMed

Insights

Seismocardiography (SCG), a noninvasive heart activity evaluation, shows promise for early cardiovascular disease detection. Advances in sensors and machine learning enhance SCG

Area of Science:

  • Biomedical Engineering
  • Cardiology
  • Signal Processing

Background:

  • Cardiovascular disease remains a leading global cause of mortality.
  • Early detection and intervention are crucial for improving patient outcomes.
  • Seismocardiography (SCG) offers a noninvasive method for cardiac activity assessment, but signal complexity poses challenges.

Purpose of the Study:

  • To review recent advancements in Seismocardiography (SCG) for cardiovascular disease detection.
  • To highlight the potential clinical utility of SCG signals.
  • To discuss innovations in sensors, signal processing, and machine learning applied to SCG.

Main Methods:

  • Review of recent scientific literature on Seismocardiography.
  • Analysis of studies focusing on SCG signal processing and feature extraction.
  • Examination of machine learning applications in SCG data analysis.

Main Results:

  • Recent studies demonstrate the potential of SCG for detecting and monitoring cardiovascular conditions.
  • Advances in low-cost sensors and sophisticated algorithms have accelerated SCG research.
  • SCG shows promise as a valuable tool for noninvasive cardiac evaluation.

Conclusions:

  • SCG is a rapidly advancing field with significant potential in cardiovascular diagnostics.
  • Integration of new technologies is overcoming previous limitations in SCG analysis.
  • Further research is warranted to fully realize the clinical applications of SCG.

Keywords:
cardiovascular diseasefeature extractionheart-induced vibrationsmachine learningnoise removalseismocardiographysignal processingsignal segmentation

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