@conference {1408,
	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},
	year = {2018},
	month = {2018},
	pages = {665 - 670},
	publisher = {SCITEPRESS - Science and Technology Publications},
	organization = {SCITEPRESS - Science and Technology Publications},
	address = {Funchal - Madeira, Portugal},
	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 {\^a}{\texteuro}{\textquotedblleft} naming chest compression fre-quency and depth {\^a}{\texteuro}{\textquotedblleft} 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 an-gles 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 {\^A}{\textpm}4.4 bpm (4.1\%) in comparison to the reference of the Resusci Anne mannequin.},
	keywords = {Cardiac Massage, CPR training, Curve Fitting, Evolutionary Algorithm, UNIAMT, UNILLM},
	isbn = {978-989-758-281-3},
	doi = {10.5220/0006732806650670},
	url = {http://www.scitepress.org/DigitalLibrary/Link.aspx?doi=10.5220/0006732806650670},
	author = {Lins, Christian and Klausen, Andreas and Fudickar, Sebastian and Hellmers, Sandra and Lipprandt, Myriam and R{\"o}hrig, Rainer and Hein, Andreas}
}
