Picture of athlete cycling

Open Access research with a real impact on health...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the Physical Activity for Health Group based within the School of Psychological Sciences & Health. Research here seeks to better understand how and why physical activity improves health, gain a better understanding of the amount, intensity, and type of physical activity needed for health benefits, and evaluate the effect of interventions to promote physical activity.

Explore open research content by Physical Activity for Health...

Comparison of pulse active ratio similarity measurement

Haidawati Binti Mohamad Nasir, H and Bin Safie, Sairul Izwan and Kushsairy Bin Abdul Kadir, K and Soraghan, John and Petropoulakis, Lykourgos (2013) Comparison of pulse active ratio similarity measurement. In: 1st International Conference on Artificial Intelligence, Modelling and Simulation (AIMS), 2013. IEEE, 309 - 314. ISBN 978-1-4799-3250-4

Full text not available in this repository. Request a copy from the Strathclyde author

Abstract

Distance measurement is a quantitative tool to measure similarity or dissimilarity between two objects. A correct selection of distance measurement will enhance the performance of a biometric authentication system. In this paper, various types of distance measurement methods such as Euclidean distance, City block distance, Chebyshevdistance, Minkowskidistance, Sorensen distance, Cosine distance and Mahalanobis distance are evaluated to determine the best similarity measure to be used with the novel pulse active ratio (PAR) feature extraction method. The results are obtained based on comparing 486 electrocardiography (ECG)signals which provide a total of 42,149 ECG comparisons. The comparisons show that the similarity measurement based on Sorensen distance gives the best matching algorithm to increase the performance of the PAR ECG biometric approach.