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Authors: Christian Lins 1 ; Andreas Klausen 2 ; Sebastian Fudickar 2 ; Sandra Hellmers 2 ; Myriam Lipprandt 2 ; Rainer Röhrig 2 and Andreas Hein 2

Affiliations: 1 OFFIS - Institute for Information Technology, Germany ; 2 Carl von Ossietzky University, Germany

Keyword(s): CPR Training, Curve Fitting, Evolutionary Algorithm, Cardiac Massage.

Abstract: In this paper, we present a robust sinusoidal curve fitting method based on the Differential Evolution (DE) algorithm for determining cardiopulmonary resuscitation (CPR) parameters – naming chest compression frequency and depth – from skeletal motion data. Our implementation uses skeletal data from the RGB-D (RGB + Depth) Kinect v2 sensor and works without putting non-sensor related constraints such as specific view angles or distance to the system. Our approach is intended to be part of a robust and easy-to-use feedback system for CPR training, allowing its unsupervised training. We compare the sensitivity of our DE implementation with data recorded by a Laerdal Resusci Anne mannequin. Results show that the frequency of the DE-based CPR is recognized with a variance of 4:4 bpm (4.1%) in comparison to the reference of the Resusci Anne mannequin.

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Paper citation in several formats:
Lins, C. ; Klausen, A. ; Fudickar, S. ; Hellmers, S. ; Lipprandt, M. ; Röhrig, R. and Hein, A. (2018). Determining Cardiopulmonary Resuscitation Parameters with Differential Evolution Optimization of Sinusoidal Curves. In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - AI4Health; ISBN 978-989-758-281-3; ISSN 2184-4305, SciTePress, pages 665-670. DOI: 10.5220/0006732806650670

@conference{ai4health18,
author={Christian Lins and Andreas Klausen and Sebastian Fudickar and Sandra Hellmers and Myriam Lipprandt and Rainer Röhrig and Andreas Hein},
title={Determining Cardiopulmonary Resuscitation Parameters with Differential Evolution Optimization of Sinusoidal Curves},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - AI4Health},
year={2018},
pages={665-670},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006732806650670},
isbn={978-989-758-281-3},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - AI4Health
TI - Determining Cardiopulmonary Resuscitation Parameters with Differential Evolution Optimization of Sinusoidal Curves
SN - 978-989-758-281-3
IS - 2184-4305
AU - Lins, C.
AU - Klausen, A.
AU - Fudickar, S.
AU - Hellmers, S.
AU - Lipprandt, M.
AU - Röhrig, R.
AU - Hein, A.
PY - 2018
SP - 665
EP - 670
DO - 10.5220/0006732806650670
PB - SciTePress

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