Back to Evidence Hub
Case Study S041
2013 Release

García-González 2013: CEBS Database

M. A. García-González et al.
Access Paper

Quick Conclusion: S041 (CEBS Database) is a 'gold standard' dataset for technical SCG research. For OpenSCG, it serves as the primary benchmarking tool for validating our signal processing filters and basic peak detection logic before moving to complex real-world data.


📊 Key Accuracy Metrics

MetricResult
Total Data60 records (Basal, Music, Post-music)
Sampling frequency5 kHz
SensorBiopac MP36, triaxial accelerometer (LIS344ALH)
Duration~1 hour per volunteer

🔍 Study Analysis

Objective & Population

Dataset Description / Technical Study. Cohort: 20 presumed healthy volunteers (N=20).

What it Supports

The study supports the use of SCG as a reliable surrogate for ECG in measuring heart rate variability (HRV). It provides a high-resolution (5 kHz) open-access database that is a global benchmark for testing and optimizing automated SCG beat detection algorithms, especially under different respiratory conditions.

What it Does Not Support

The study does not provide evidence for clinical monitoring in active or pathological subjects, as the data collection was restricted to healthy individuals lying still in a lab.


🛠 Technical Context

  • DOI: 10.13026/C2KW23
  • Authors: M. A. García-González et al.
  • Confidence Tier: Supporting

Study Snapshot

Metadata Summary

Target Population

20 presumed healthy volunteers

N

Sample Size

20 Subjects

Validated Metric

60 records (Basal, Music, Post-music)

Critical Appraisal
supporting

Provided a high-resolution open database (CEBS) for benchmarking SCG-based heartbeat detection and HRV analysis.