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Data 2017, 2(1), 1; doi:10.3390/data2010001

Description of a Database Containing Wrist PPG Signals Recorded during Physical Exercise with Both Accelerometer and Gyroscope Measures of Motion

School of Electrical and Electronic Engineering, The University of Manchester, Manchester, M13 9PL, UK
Author to whom correspondence should be addressed.
Academic Editor: Jamal Jokar Arsanjani
Received: 5 July 2016 / Revised: 8 December 2016 / Accepted: 9 December 2016 / Published: 24 December 2016
View Full-Text   |   Download PDF [6863 KB, uploaded 24 December 2016]   |  


Wearable heart rate sensors such as those found in smartwatches are commonly based upon Photoplethysmography (PPG) which shines a light into the wrist and measures the amount of light reflected back. This method works well for stationary subjects, but in exercise situations, PPG signals are heavily corrupted by motion artifacts. The presence of these artifacts necessitates the creation of signal processing algorithms for removing the motion interference and allowing the true heart related information to be extracted from the PPG trace during exercise. Here, we describe a new publicly available database of PPG signals collected during exercise for the creation and validation of signal processing algorithms extracting heart rate and heart rate variability from PPG signals. PPG signals from the wrist are recorded together with chest electrocardiography (ECG) to allow a reference/comparison heart rate to be found, and the temporal alignment between the two signal sets is estimated from the signal timestamps. The new database differs from previously available public databases because it includes wrist PPG recorded during walking, running, easy bike riding and hard bike riding. It also provides estimates of the wrist movement recorded using a 3-axis low-noise accelerometer, a 3-axis wide-range accelerometer, and a 3-axis gyroscope. The inclusion of gyroscopic information allows, for the first time, separation of acceleration due to gravity and acceleration due to true motion of the sensor. The hypothesis is that the improved motion information provided could assist in the development of algorithms with better PPG motion artifact removal performance. View Full-Text
Keywords: photoplethysmography (PPG); electrocardiography (ECG); heart rate monitoring; physical exercise photoplethysmography (PPG); electrocardiography (ECG); heart rate monitoring; physical exercise

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Jarchi, D.; Casson, A.J. Description of a Database Containing Wrist PPG Signals Recorded during Physical Exercise with Both Accelerometer and Gyroscope Measures of Motion. Data 2017, 2, 1.

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