Pulse Transit Time (PTT) is the time that pulse waves require to travel in blood vessels between two sites. It is an important indicator for many medical properties and recent research focused on its potential for continuous blood pressure monitors. Three challenges make it difficult to measure PTT precisely: 1) Photoplethysmogram (PPG) measurements are inherently noisy, 2) the required wave phase detection accuracy for measurement sited in proximity (e.g., on the same finger) is in the order of milliseconds and 3) the lack of available datasets for PPG measurements in proximity at the required high sample rates. This dataset is designed to address these challenges by providing, amongst other physiologic time series and numerics such as blood pressure, 2x3 unfiltered raw PPG sensor signals of multiple wavelengths for 2 measurement sites in a defined distance to each other.

The dataset contains 66 recordings of 19 physiologic time series for more than 40000 heartbeats. These data were collected to conduct investigations into signal processing and machine learning models for applications in short distance Pulse Transit Time (PTT) recognition, cuffless pressure sensing and other cardiovascular activity modelling research.

Original Data

Data Description

The data is distributed in two formats, WFDB (WaveForm DataBase) and CSV (comma-separated-value). The WFDB data for all participants have been placed in the root directory along with a corresponding RECORDS file. Each WFDB .hea header file contains the participants' numerics such as