David Bethge

schoolMetabar_chart#2633 Global Rank

Total Papers

HCI Rank

#2633

Research Areas

Years Active

Recent Publications

Can AI Route You to Happiness? A Technical Study on Affective Automotive Navigation Interfaces

Conventional navigation systems, fixated on metrics such as time and distance, neglect the driver's emotional well-being, despite driving routes being inherent emotional triggers. This raises a critical question for the Intelligent User Interface community: How can intelligent systems successfully route information ba…

CHI '253rd AuthorSocial & Collaborative VR +2

A Multimodal Approach for Targeting Error Detection in Virtual Reality Using Implicit User Behavior

Although the point-and-select interaction method has been shown to lead to user and system-initiated errors, it is still prevalent in VR scenarios. Current solutions to facilitate selection interactions exist, however they do not address the challenges caused by targeting inaccuracy. To reduce the effort required to t…

UBICOMP '231st AuthorAutomated Driving Interface & Takeover Design +2

Technical Design Space Analysis for Unobtrusive Driver Emotion Assessment Using Multi-Domain Context

Driver emotions play a vital role in driving safety and performance. Consequently, regulating driver emotions through empathic interfaces have been investigated thoroughly. However, the prerequisite - driver emotion sensing - is a challenging endeavor: Body-worn physiological sensors are intrusive, while facial and sp…

AUTO_UI '21CorrespondingHead-Up Display (HUD) & Advanced Driver Assistance Systems (ADAS) +1

HMInference: Inferring Multimodal HMI Interactions in Automotive Screens

Driving requires high cognitive capabilities in which drivers need to be able to focus on first-level driving tasks. However, each interaction with the User Interface (UI) system presents a potential distraction. Designing UIs based on insights from field-collected user interaction logs, as well as real-time estimatio…

UIST '211st AuthorHead-Up Display (HUD) & Advanced Driver Assistance Systems (ADAS) +1

VEmotion: Using Driving Context for Indirect Emotion Prediction in Real-Time

Detecting emotions while driving remains a challenge in Human-Computer Interaction. Current methods to estimate the driver's experienced emotions use physiological sensing (e.g., skin-conductance, electroencephalography), speech, or facial expressions. However, drivers need to use wearable devices, perform explicit vo…

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