Ming03/DSI-SCG-ECG

Dataset Description

This repository contains the dataset for the paper: "Cardiac 3D Mechanical and Electrical Signal Reconstruction via Defocused Speckle Imaging".

It provides dual-camera Defocused Speckle Imaging (DSI) videos and cardiac signals. The dataset is collected from two distinct cohorts to ensure robustness and clinical relevance.

• Total Participants: 50
  • Lab Cohort: 20 healthy subjects.
  • Clinical Cohort: 30 patients from the ultrasound department.
• Data Modalities: Dual-camera DSI videos, Seismocardiogram (SCG), Gyrocardiogram (GCG), and Electrocardiogram (ECG).

Data Structure

The dataset includes raw videos and processed signal files in Python .pkl format:

• Lab_data.pkl: Processed signals for the 20 healthy subjects.
• Clinic_data.pkl: Processed signals for the 30 ultrasound department patients.

Sampling Rates

• DSI Optical Flow & Mechanical Signals (SCG/GCG): 250 Hz
• ECG Reference Signals: 500 Hz

Signal Dictionary (Processed Data)

When loading the .pkl files, the data for each subject is stored as dictionaries containing numpy ndarray objects. Most 2D arrays (e.g., (N, 500)) represent N cardiac cycles resampled to a fixed length of 500.

1. Reference Signals (Ground Truth)

• ECG: Reference Electrocardiogram signal.
• SCG: Reference Seismocardiogram signal.
• GCGx: Reference Gyrocardiogram signal (x-axis).
• GCGy: Reference Gyrocardiogram signal (y-axis).

2. Reconstructed Signals (via Physical Model)

Signals reconstructed using the physical model from two tracked points (g and r):

• SCG_g / SCG_r: Reconstructed SCG signals from point g and point r.
• GCGx_g / GCGx_r: Reconstructed GCGx signals from point g and point r.
• GCGy_g / GCGy_r: Reconstructed GCGy signals from point g and point r.

3. Camera Motion Signals (DSI Optical Flow)

Raw motion signals captured by the two cameras at two specific points (g and r) across the x and y axes:

• Camera 1: cam1_gx, cam1_gy, cam1_rx, cam1_ry
• Camera 2: cam2_gx, cam2_gy, cam2_rx, cam2_ry

4. Raw Signal Lengths

1D arrays recording the original signal length of each cardiac cycle before length normalization:

• ECG_Raw: Original length of ECG signals per cardiac cycle.
• SCG_Raw: Original length of SCG signals per cardiac cycle.
• GCGx_Raw: Original length of GCGx signals per cardiac cycle.
• GCGy_Raw: Original length of GCGy signals per cardiac cycle.

Usage Example

Here is a quick example of how to load and explore the .pkl files in Python:

import pickle

# Load the Lab data
with open('Lab_data.pkl', 'rb') as f:
    lab_data = pickle.load(f)

subject_id = 'Lab_1'
video_id = 0

subject_data = lab_data[subject_id][video_id]

# Extract reference ECG and reconstructed SCG
ecg_ref = subject_data['ECG']             # shape: (N_cycles, 500)
scg_reconstructed = subject_data['SCG_g'] # shape: (N_cycles, 500)
raw_lengths = subject_data['ECG_Raw']     # shape: (N_cycles,)

print(f"Number of cardiac cycles: {ecg_ref.shape[0]}")

License

Our dataset is CC-BY-NC 4.0 licensed, as found in the LICENSE file.