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Dennis Stanke is a researcher in the Human-Computer Interaction Group at the University of Hannover. His main interest is the research of new techniques in the field of mobile interaction and wearable computing.
During his studies on the University of Hannover he focused on Human-Computer Interaction as well as on Software Engineering. Dennis worked for nearly three years as a student assistant at the University of Hannover before joining the Human-Computer Interaction Group as a researcher in July '19.
TactileWear: A Comparison of Electrotactile and Vibrotactile Feedback on the Wrist and Ring Finger
Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences, Shaping Society
Wearables are getting more and more powerful. Tasks like notifications can be delegated to smartwatches. But the output capabilities of wearables seem to be stuck at displays and vibration. Electrotactile feedback may serve as an energy-efficient alternative to standard vibration feedback. We developed prototypes of wristbands and rings and conducted two studies to compare electrotactile and vibrotactile feedback. The prototypes have either four electrodes for electrotactile feedback or four actuators for vibration feedback. In a first study we analyzed the localization characteristics of the created stimuli. The results suggest more strongly localized sensations for electrotactile feedback, compared to vibrotactile feedback, which was more diffuse. In a second study we created notification patterns for both modalities and evaluated recognition rates, verbal associations, and satisfaction. Although the recognition rates were higher with electrotactile feedback, vibrotactile feedback was judged as more comfortable and less stressful. Overall, the results show that electrotactile feedback can be a viable alternative to vibrotactile feedback for wearables, especially for notification rings.
EmojiZoom: Emoji Entry via Large Overview Maps 😄 🔍
Proceedings of the 18th international conference on Human-computer interaction with mobile devices and services - MobileHCI '16
Current soft keyboards for emoji entry all present emoji in the same way: in long lists, spread over several categories. While categories limit the number of emoji in each individual list, the overall number is still so large, that emoji entry is a challenging task. The task takes particularly long if users pick the wrong category when searching for an emoji. Instead, we propose a new zooming keyboard for emoji entry. Here, users can see all emoji at once, aiding in building spatial memory where related emoji are to be found. We compare our zooming emoji keyboard against the Google keyboard and find that our keyboard allows for 18% faster emoji entry, reducing the required time for one emoji from 15.6s to 12.7s. A preliminary longitudinal evaluation with three participants showed that emoji entry time over the duration of the study improved at up to 60% to a final average of 7.5s.