MSCardio Seismocardiography (SCG) Dataset
Executive Summary
The MSCardio Seismocardiography (SCG) Dataset is an open-access resource collected using smartphone sensors from 123 participants, with 502 unique recordings after preprocessing. It provides axial chest vibration data in three directions, enabling research in SCG signal processing, machine learning applications, and remote cardiovascular health assessment. The dataset addresses the scarcity of open-access SCG data and supports scalable, real-world cardiovascular monitoring without specialized equipment.
Answer Machine Insights
Q: What is the primary purpose of the MSCardio dataset?
To support research in SCG signal processing, machine learning applications, and remote cardiovascular health assessment.
This dataset is intended for research in: SCG signal processing and feature extraction, machine learning applications in cardiovascular monitoring, investigating inter- and intra-subject variability in SCG signals, remote cardiovascular health assessment.
Q: How were the SCG signals collected?
Participants placed their smartphone on their chest while lying in a supine position, and the app recorded SCG signals for approximately two minutes.
Participants placed their smartphone on their chest while lying in a supine position. The app recorded SCG signals for approximately two minutes.
Key Results
502 unique SCG recordings collected from 123 participants using smartphones.
Data includes axial chest vibrations in three directions with demographic metadata for each participant.
Clinical Snapshot
Evidence Rating
Relevance
high Priority