Staying Alive - CPR Quality Parameters from Wrist-worn Inertial Sensor Data with Evolutionary Fitted Sinusoidal Models

2018/08/31 by Lins, Christian, Klausen, Andreas, Hellmers, Sandra +2
#FOS: Computer and information sciences #FOS: Physical sciences #Medical Physics (physics.med-ph) #Neural and Evolutionary Computing (cs.NE)

paper · doi:10.48550/arxiv.1809.07692

Abstract

In this paper, a robust sinusoidal model fitting method based on the Differential Evolution (DE) algorithm for determining cardiopulmonary resuscitation (CPR) quality-parameters - naming chest compression frequency and depth - as measured by an inertial sensor placed at the wrist is presented. Once included into a smartphone or smartwatch app, the proposed algorithm will enable bystanders to improve CPR (as part of a continuous closed-loop support-system). By evaluating the precision of the model with data recorded by a Laerdal Resusci Anne mannequin as reference standard, a low variance for compression frequency of ± 2.0 cpm has been found for the sensor placed at the wrist, making this previously unconsidered position a suitable alternative to the typical placement in the hand for CPR-training smartphone apps.

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