Center for Machine Learning and Intelligent Systems
About  Citation Policy  Donate a Data Set  Contact

Repository Web            Google
View ALL Data Sets

× Check out the beta version of the new UCI Machine Learning Repository we are currently testing! Contact us if you have any issues, questions, or concerns. Click here to try out the new site.

PPG-DaLiA Data Set
Download: Data Folder, Data Set Description

Abstract: PPG-DaLiA contains data from 15 subjects wearing physiological and motion sensors, providing a PPG dataset for motion compensation and heart rate estimation in Daily Life Activities.

Data Set Characteristics:  

Multivariate, Time-Series

Number of Instances:




Attribute Characteristics:


Number of Attributes:


Date Donated


Associated Tasks:


Missing Values?


Number of Web Hits:



Attila Reiss, Robert Bosch GmbH, Corporate Research, Germany, firstname.lastname '@'
Ina Indlekofer, Bosch Sensortec GmbH, Germany, firstname.lastname '@'
Philip Schmidt, Robert Bosch GmbH, Corporate Research, Germany, firstname.lastname '@'

Data Set Information:

PPG-DaLiA is a publicly available dataset for PPG-based heart rate estimation. This multimodal dataset features physiological and motion data, recorded from both a wrist- and a chest-worn device, of 15 subjects while performing a wide range of activities under close to real-life conditions. The included ECG data provides heart rate ground truth. The included PPG- and 3D-accelerometer data can be used for heart rate estimation, while compensating for motion artefacts. Details can be found in the dataset's readme-file, as well as in [1].

Attribute Information:

Raw sensor data was recorded with two devices: a chest-worn device (RespiBAN) and a wrist-worn device (Empatica E4).
The RespiBAN device provides the following sensor data: electrocardiogram (ECG), respiration, and three-axis acceleration. All signals are sampled at 700 Hz.
The Empatica E4 device provides the following sensor data: blood volume pulse (BVP, 64 Hz), electrodermal activity (EDA, 4 Hz), body temperature (4 Hz), and three-axis acceleration (32 Hz).

The dataset's readme-file contains all further details with respect to the dataset structure, data format (RespiBAN device, Empatica E4 device, synchronised data), study protocol, ground truth generation, etc.

Relevant Papers:

[1] Attila Reiss, Ina Indlekofer, Philip Schmidt, and Kristof Van Laerhoven. 2019. Deep PPG: Large-scale Heart Rate Estimation with Convolutional Neural Networks. MDPI Sensors, 19(14).

Citation Request:

You may use this data for scientific, non-commercial purposes, provided that you give credit to the owners when publishing any work based on this data. Please acknowledge publication [1].
We recommend to refer to this dataset as PPG-DaLiA, or 'PPG dataset for motion compensation and heart rate estimation in Daily Life Activities'.

Supported By:

 In Collaboration With:

About  ||  Citation Policy  ||  Donation Policy  ||  Contact  ||  CML