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- research-articleApril 2023
CatAlyst: Domain-Extensible Intervention for Preventing Task Procrastination Using Large Generative Models
CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing SystemsArticle No.: 157, Pages 1–19https://doi.org/10.1145/3544548.3581133CatAlyst uses generative models to help workers’ progress by influencing their task engagement instead of directly contributing to their task outputs. It prompts distracted workers to resume their tasks by generating a continuation of their work and ...
- short-paperMarch 2021
Estimating Levels of Engagement for Social Human-Robot Interaction using Legendre Memory Units
HRI '21 Companion: Companion of the 2021 ACM/IEEE International Conference on Human-Robot InteractionPages 362–366https://doi.org/10.1145/3434074.3447193In this study, we examine whether the data requirements associated with training a system to recognize multiple 'levels' of an internal state can be reduced by training systems on the 'extremes' in a way that allows them to estimate "intermediate" ...
- research-articleApril 2020
Self-Interruptions of Non-Driving Related Tasks in Automated Vehicles: Mobile vs Head-Up Display
CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing SystemsPages 1–9https://doi.org/10.1145/3313831.3376751Automated driving raises new human factors challenges. There is a paradox that allows drivers to perform non-driving related tasks (NDRTs), while benefiting from a driver who regularly attends to the driving task. Systems that aim to better manage a ...
- research-articleMarch 2020
Using Self-Determination Theory in Social Robots to Increase Motivation in L2 Word Learning
- Peggy van Minkelen,
- Carmen Gruson,
- Pleun van Hees,
- Mirle Willems,
- Jan de Wit,
- Rian Aarts,
- Jaap Denissen,
- Paul Vogt
HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot InteractionPages 369–377https://doi.org/10.1145/3319502.3374828This study presents a second language word learning experiment using a social robot with motivational strategies. These strategies were implemented in a social robot tutor to stimulate preschool children's intrinsic motivation. Subsequently, we ...
- research-articleOctober 2018
Multimodal approach for cognitive task performance prediction from body postures, facial expressions and EEG signal
MCPMD '18: Proceedings of the Workshop on Modeling Cognitive Processes from Multimodal DataArticle No.: 14, Pages 1–7https://doi.org/10.1145/3279810.3279849Recent developments in computer vision and the emergence of wearable sensors have opened opportunities for the development of advanced and sophisticated techniques to enable multi-modal user assessment and personalized training which is important in ...
- research-articleApril 2018
Monitoring task engagement using facial expressions and body postures
IWISC '18: Proceedings of the 3rd International Workshop on Interactive and Spatial ComputingPages 103–108https://doi.org/10.1145/3191801.3191816As more industries adopt the use of robots to increase productivity, there is an increased need for effective human-robot interaction training, especially in the case of heavy and high precision robots. This implies the need for easy assessment methods ...
- research-articleMay 2017Best Paper
Designing Gamified Applications that Make Safe Driving More Engaging
CHI '17: Proceedings of the 2017 CHI Conference on Human Factors in Computing SystemsPages 2826–2839https://doi.org/10.1145/3025453.3025511Low levels of engagement while driving can pose road safety risks, e.g., inattention during low traffic or routine trips. Interactive technologies that increase task engagement could therefore offer safety benefits, e.g., through performance feedback, ...