Camilo Hernandez Mejia

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Touchscreens are nowadays the preferred choice for user interfaces in consumer electronics. Significant technological advances have been made in terms of touch sensing and visual quality. However, the haptic feedback offered by commercial products is still ...

Recently, the interest in haptic feedback is growing thanks to its ability to enhance the interaction with Human Machine Interfaces (HMIs). This research project is exploring the potential of machine learning combined with piezoelectric actuators to genera ...

Touch-screens have become the most common way of interaction between humans and machines. Nevertheless, the lack of rich haptic-feedback on most of the devices limits the quality and effectivity of the interaction. To develop novel haptic feedback generati ...

Touch is commonly used to mediate human-machine interactions, notably in the setting of Digital Musical Instruments (DMIs), where touch screens are prevalent. The lack of rich haptic feedback has an impact on the richness and quality of the interaction. Pi ...

Camilo Hernandez Mejia

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Deep Learning for Localized-Haptic Feedback in Tactile Surfaces

Artificial Neural Networks for Impact Position Detection in Haptic Surfaces

Effect of the Impact Contact Duration on Machine Learning Models for Impact Position Detection

Reinforcement Learning and Hardware in the Loop for Localized Vibrotactile Feedback in Haptic Surfaces