  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 $\pm 2.0$ 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.
