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During exercise, heart rate has proven to be a good measure in planning workouts. It is not only simple to measure but also well understood and has been used for many years for workout planning. To use heart rate to control physical exercise, a model which predicts future heart rate dependent on a given strain can be utilized. In this paper, we present a mathematical model based on convolution for predicting the heart rate response to strain with four physiologically explainable parameters. This model is based on the general idea of the Fitness-Fatigue model for performance analysis, but is revised here for heart rate analysis. Comparisons show that the Convolution model can compete with other known heart rate models. Furthermore, this new model can be improved by reducing the number of parameters. The remaining parameter seems to be a promising indicator of the actual subject’s fitness.
Cognitive robotics aims at understanding biological processes, though it has also the potential to improve future robotics systems. Here we show how a biologically inspired model of motor control with neural fields can be augmented with additional components such that it is able to solve a basic robotics task, that of obstacle avoidance. While obstacle avoidance is a well researched area, the focus here is on the extensibility of a biologically inspired framework. This work demonstrates how easily the biological inspired system can be used to adapt to new tasks. This flexibility is thought to be a major hallmark of biological agents.
Steigende psychische Arbeitsanforderungen werden im betrieblichen Alltag zunehmend als Normalität empfunden. Trotz erhöhtem Leistungsdruck werden Arbeitspausen oftmals unregelmäßig bis gar nicht wahrgenommen, obwohl mit einer Pause eine gesteigerte Erholung und eine erhöhte Produktivität einhergehen. Der vorliegende Artikel zeigt auf, wie Arbeitspausen und deren systematische Implementierung zu einem "gesunden Unternehmen" beitragen können.