Simulation-based training offers a safe and repeatable environment where users can increase their skill level. Development of products facilitating such training is, however, faced with high uncertainty and ambiguous ...

We developed a wearable experimental sensor setup featuring multimodal EEG+fNIRS neuroimaging data capture applicable for in situ experiments at a lower financial threshold. Consistent application of a good protocol and ...

This paper presents a new approach for evaluating and controlling expressive humanoid robotic faces using open-source computer vision and machine learning methods. Existing research in Human-Robot Interaction lacks flexible ...

The idea of remote controlling ships for operational and commercial uses has developed beyond concepts. Controlling and monitoring vessels from a distant location requires updating the concept and requirements of shore ...

The use of intraoperative tool-tissue interaction data for arthroscopic digital twins has the potential to enhance haptic feedback in surgical simulations. This study demonstrates the implementation of an interpolation-based ...

This work presents a modular research platform to design, test and run human-machine interaction (HMI) experiments. Traditionally, HMI experiments are time and resource consuming, particularly in the piloting phase. ...

Tactile hands-only training is particularly important for medical palpation. Generally, equipment for palpation training is expensive, static, or provides too few study cases to practice on. We have therefore developed a ...

Functional near-infrared spectroscopy (fNIRS) is often praised for its portability and robustness towards motion artifacts. While an increasing body of fNIRS research in real-world environments is emerging, most fNIRS ...