OpenSCG.org
OverviewCAD EvolutionSmartphone AccuracyFiducial PointsAbout
Stable v2.1.0
Back to Science Hub

Paolo Castiglioni

Verified Contributor2 Publications in Hub

Research Bibliography

ID: beat-to-beat-estimation-of-lvet-and-qs2-indices-of-cardiac-mechanics-from-wearable-seismocardiography-in-ambulant-subjects2013

Beat-to-beat estimation of LVET and QS2 indices of cardiac mechanics from wearable seismocardiography in ambulant subjects

This study shows that smartphones can accurately detect heartbeats using vibrations from the chest, with improved algorithms achieving near-perfect accuracy.

ID: wearable-seismocardiography2007

Wearable Seismocardiography

This study shows that wearable devices can use heart vibrations and AI to diagnose aortic valve problems and predict blood flow metrics as accurately as advanced MRI scans, offering a cheaper and faster alternative for heart health monitoring.

SCG
OpenSCG.org

An open-source ecosystem bridging the gap between high-fidelity mechanical vibrations and actionable cardiac digital biomarkers.

Clinical Resources

  • Evidence Hub Overview
  • CAD Analysis
  • Sensor Validation
  • Waveform Blueprint

Project Governance

  • Open Source (MIT)
  • About Initiative
  • Affiliated Projects

© 2026 OpenSCG.org Project. Clinical grade research.

v2.1.0 STABLEBUILD 2026-03-10