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WildPPG
Manuel Meier, Berken Utku Demirel, Christian Holz
Sensing, Interaction & Perception Lab, Department of Computer Science, ETH Zürich, Switzerland
Quick Links: - Project Website - Paper
Loading the Dataset
The dataset is available for download here The dataset is split into .mat MATLAB files representing participants and can be loaded with MATLAB.
Loading the Data
You can load the .mat
file using either Python or MATLAB:
Python:
Usescipy.io.loadmat
:from scipy.io import loadmat data = loadmat('WildPPG.mat')
MATLAB:
Use the built-inload
function:data = load('WildPPG.mat');
The .mat
file contains 14 cell arrays, each representing a variable (e.g., data_altitude_values
, data_bpm_values
, data_ppg_wrist
).
Each cell array includes 16 entries, corresponding to data from 16 individual subjects.
Example loader
import numpy as np
import scipy.io
def load_domain_data(domain_idx):
"""Loads wrist PPG and heart rate data for a single subject (domain).
Args:
domain_idx (int): Index of the subject (0–15).
Returns:
X (np.ndarray): PPG signal data (n_samples × signal_dim).
y (np.ndarray): Heart rate values (bpm), adjusted to start from 0.
d (np.ndarray): Domain labels (same shape as y), equal to domain_idx.
"""
data_path = 'data/WildPPG/WildPPG.mat'
data_all = scipy.io.loadmat(data_path)
# Load PPG signal and heart rate values
data = data_all['data_ppg_wrist']
data_labels = data_all['data_bpm_values']
domain_idx = int(domain_idx)
X = data[domain_idx, 0]
y = np.squeeze(data_labels[domain_idx][0]).astype(int)
# Mask out invalid samples (e.g., NaNs, infs, and HR < 30 bpm)
mask_Y = y >= 30
mask_X = ~np.isnan(X).any(axis=1) & ~np.isinf(X).any(axis=1)
combined_mask = mask_Y & mask_X
X = X[combined_mask]
y = y[combined_mask] - 30 # Normalize HR: min HR is 30 bpm → range starts from 0
d = np.full(y.shape, domain_idx, dtype=int)
return X, y, d
Load PPG & Heart Rate Data for a Single Subject
The function load_domain_data(domain_idx)
loads wrist PPG signal data and heart rate (HR) labels for a single subject from the WildPPG.mat
file.
domain_idx
ranges from0
to15
, each corresponding to one of the 16 subjects.- The data is preprocessed by:
- Removing invalid samples (NaNs, infs, and HR < 30 bpm)
- Normalizing HR values to start from 0 (by subtracting 30 bpm)
- The function returns:
X
: preprocessed PPG signal (shape:n_samples × signal_dim
)y
: adjusted heart rate labelsd
: domain label (same shape asy
, filled withdomain_idx
)
Example usage:
x, y, d = load_domain_data(3) # Load data for subject 3
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