papers.bib

@INPROCEEDINGS{Di_Pirro_2024,
title = "Characterizing Cultural Differences in Naturalistic Driving Interactions",
author = "Di Pirro, Rachel and Sandhaus, Hauke and Goedicke, David and Calderone, Dan and Oishi, Meeko and Ju, Wendy",
booktitle = "2024 IEEE Intelligent Transportation Systems Conference (ITSC)",
year = 2024,
month = sep,
day = {24-27},
address = {Edmonton, Canada},
url = {https://its.papercept.net/conferences/scripts/abstract.pl?ConfID=87&Number=874},
pdf = {ITSC_2024_Characterizing_Cultural_Differences_in_Naturalistic_Driving_Interactions.pdf},
abstract = {The characterization of driver interactions is important for a variety of problems associated with the design of autonomy for vehicles. We consider the role of cultural context in driver interactions, by evaluating the differences in driving interactions in simulated driving experiments conducted in New York City, New York, USA, and in Haifa, Israel. The same experiment was conducted in both locations, and focused on naturalistic driving interactions at unsigned intersections, in which interaction with another vehicle was required for safe navigation through the intersection. We employ conditional distribution embeddings, a nonparametric machine learning technique, to empirically characterize differences in the distribution of trajectories that characterize driver interactions, across both locations. We show that cultural variability outweighs individual variability in intersections that require turning maneuvers, and that clear distinctions amongst driving strategies are evident between populations. Our approach facilitates a data-driven analysis that is amenable to rigorous statistical testing, in a manner that minimizes filtering, pre-processing, and other manipulations that could inadvertently bias the data and obscure important findings.},
bibtex_show = {true},
selected = {true},
preview = {driving_characteristics.png},
abbr = {ITSC},
tldr = {This study compares driver interactions at unsigned intersections in New York City and Haifa, using MMD in Hilbert space, revealing that cultural differences significantly influence driving strategies, especially during turns.}
}


@misc{sandhaus2024studentreflectionsselfinitiatedgenai,
  title         = {Student Reflections on Self-Initiated GenAI Use in HCI Education},
  author        = {Hauke Sandhaus and Quiquan Gu and Maria Teresa Parreira and Wendy Ju},
  year          = 2024,
  url           = {https://arxiv.org/abs/2410.14048},
  eprint        = {2410.14048},
  arxiv         = {2410.14048},
  archiveprefix = {arXiv},
  primaryclass  = {cs.HC},
  selected      = {true},
  tldr          = {Students in an HCI course extensively used GenAI tools for their design work, which showed improvements in creativity and productivity. However, this also brought up ethical concerns related to design reflection and the risk of shallow learning.},
  abstract      = {Generative Artificial Intelligence's (GenAI) impact on Human-Computer Interaction (HCI) education and technology design is pervasive but poorly understood. This study examines how graduate students in an applied HCI course utilized GenAI tools across various stages of interactive device design. Although the course policy neither explicitly encouraged nor prohibited using GenAI, students independently integrated these tools into their work. Through conducting 12 post-class group interviews, we reveal the dual nature of GenAI: while it stimulates creativity and accelerates design iterations, it also raises concerns about shallow learning and over-reliance. Our findings indicate that GenAI's benefits are most pronounced in the Execution phase of the design process, particularly for rapid prototyping and ideation. In contrast, its use in the Discover phase and design reflection may compromise depth. This study underscores the complex role of GenAI in HCI education and offers recommendations for curriculum improvements to better prepare future designers for effectively integrating GenAI into their creative processes.},
  preview       = {LLMsInHCI.png},
  bibtex_show   = {true},
  abbr          = {Pre-print}
}
misc{sandhaus2024crashdata,
  title       = {My Precious Crash Data: Barriers and Opportunities in Encouraging Autonomous Driving Companies to Share Safety-Critical Data},
  author      = {Hauke Sandhaus and Angel Wang and Qian Yang and Wendy Ju},
  year        = 2024,
  pdf         = {PreciousCrashData.pdf},
  abstract    = {Safety-critical data, such as crash and near-crash records, are crucial to improving autonomous vehicle (AV) design and development. Sharing such data across AV companies, academic researchers, regulators, and the public can help make all AVs safer. However, AV companies rarely share safety-critical data externally. This paper aims to pinpoint why AV companies are reluctant to share safety-critical data, with an eye on how these barriers can inform new approaches to promote sharing. We interviewed twelve AV company employees who actively work with such data in their day-to-day work. Findings suggest two key, previously unknown barriers to data sharing: (1) Datasets inherently embed salient knowledge that is key to improving AV safety and are resource intensive. Therefore, data sharing, even within a company, is political and fraught. (2) Interviewees believed AV safety knowledge is private knowledge that brings competitive edges to their companies, rather than public knowledge for social good. We discuss the implications of these findings for incentivizing and enabling safety-critical AV data sharing, specifically, implications for new approaches to (1) debating and stratifying public and private AV safety knowledge, (2) innovating data tools and data sharing pipelines that enable easier sharing of public AV safety data and knowledge; (3) offsetting costs of curating safety-critical data and incentivizing data sharing.},
  bibtex_show = {true},
  selected    = {true},
  preview     = {precious_crash.png},
  abbr        = {Under review},
  tldr        = {Insider interviews reveal that autonomous vehicle companies share minimal safety-critical data due to the difficulties it brings in resisting market competition. We suggest new approaches to untangle data from intellectual property, and emphasize need for new incentive schemes.}
}
@inproceedings{10.1145/3640792.3675717,
  title       = {Modeling Social Situation Awareness in Driving Interactions},
  author      = {Klein, Navit and Sandhaus, Hauke and Goedicke, David and Ju, Wendy and Parush, Avi},
  year        = 2024,
  booktitle   = {Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications},
  location    = {Stanford, CA, USA},
  publisher   = {Association for Computing Machinery},
  address     = {New York, NY, USA},
  series      = {AutomotiveUI '24},
  pages       = 1,
  doi         = {10.1145/3640792.3675717},
  isbn        = 9798400705106,
  url         = {https://doi.org/10.1145/3640792.3675717},
  html        = {https://doi.org/10.1145/3640792.3675717},
  abstract    = {The design of self-driving vehicles requires an understanding of the social interactions between drivers in resolving vague encounters, such as at un-signalized intersections. In this paper, we make the case for social situation awareness as a model for understanding everyday driving interaction. Using a dual-participant VR driving simulator, we collected data from driving encounter scenarios to understand how (N=170) participant drivers behave with respect to one another. Using a social situation awareness questionnaire we developed, we assessed the participants’ social awareness of other driver’s direction of approach to the intersection, and also logged signaling, speed and speed change, and heading of the vehicle. Drawing upon the statistically significant relationships in the variables in the study data, we propose a Social Situation Awareness model based on the approach, speed, change of speed, heading and explicit signaling from drivers.},
  numpages    = 1,
  keywords    = {Driving encounters, autonomous vehicles, social situational awareness (SA), unsignaled intersections, virtual reality (VR)},
  preview     = {VR_cars.png},
  bibtex_show = {true},
  abbr        = {AutoUI},
  selected    = {true},
  video       = {https://files.osf.io/v1/resources/bz8vq/providers/osfstorage/66f34b9559795b5d21a852cc?direct=&mode=render},
  tldr        = {Proposes a Social Situation Awareness model for better understanding driver negotiation at un-signalized intersections.}
}



@inproceedings{10.1145/3640792.3675730,
  title       = {Changing Lanes Toward Open Science: Openness and Transparency in Automotive User Research},
  author      = {Ebel, Patrick and Bazilinskyy, Pavlo and Colley, Mark and Goodridge, Courtney Michael and Hock, Philipp and Janssen, Christian P. and Sandhaus, Hauke and Srinivasan, Aravinda Ramakrishnan and Wintersberger, Philipp},
  year        = 2024,
  booktitle   = {Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications},
  location    = {Stanford, CA, USA},
  publisher   = {Association for Computing Machinery},
  address     = {New York, NY, USA},
  series      = {AutomotiveUI '24},
  pages       = {94–105},
  doi         = {10.1145/3640792.3675730},
  isbn        = 9798400705106,
  url         = {https://doi.org/10.1145/3640792.3675730},
  html        = {https://osf.io/zdpek/},
  abstract    = {We review the state of open science and the perspectives on open data sharing within the automotive user research community. Openness and transparency are critical not only for judging the quality of empirical research, but also for accelerating scientific progress and promoting an inclusive scientific community. However, there is little documentation of these aspects within the automotive user research community. To address this, we report two studies that identify (1) community perspectives on motivators and barriers to data sharing, and (2) how openness and transparency have changed in papers published at AutomotiveUI over the past 5 years. We show that while open science is valued by the community and openness and transparency have improved, overall compliance is low. The most common barriers are legal constraints and confidentiality concerns. Although research published at AutomotiveUI relies more on quantitative methods than research published at CHI, openness and transparency are not as well established. Based on our findings, we provide suggestions for improving openness and transparency, arguing that the motivators for open science must outweigh the barriers. All supporting materials are freely available at: https://osf.io/zdpek/},
  numpages    = 12,
  keywords    = {AutomotiveUI, open data, open science, openness, reproducibility, transparency},
  pdf         = {https://files.osf.io/v1/resources/tmkc2/providers/osfstorage/668666c81960ff034f58e10f?format=pdf&action=download&direct&version=2},
  preview     = {OpenCar.png},
  selected    = {true},
  bibtex_show = {true},
  abbr        = {AutoUI},
  tldr        = {Analyzes how openness and transparency have evolved in automotive user research and suggests steps for improving data sharing.}
}


@inproceedings{sandhaus2024regainingtrustimpacttransparent,
  title         = {Regaining Trust: Impact of Transparent User Interface Design on Acceptance of Camera-Based In-Car Health Monitoring Systems},
  author        = {Sandhaus, Hauke and Choksi, Madiha Zahrah and Ju, Wendy},
  year          = 2024,
  booktitle     = {Adjunct Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications},
  location      = {Stanford, CA, USA},
  publisher     = {Association for Computing Machinery},
  address       = {New York, NY, USA},
  series        = {AutomotiveUI '24 Adjunct},
  pages         = {203–208},
  doi           = {10.1145/3641308.3685048},
  isbn          = 9798400705205,
  url           = {https://doi.org/10.1145/3641308.3685048},
  html          = {https://doi.org/10.1145/3641308.3685048},
  abstract      = {Introducing in-car health monitoring systems offers substantial potential to improve driver safety. However, camera-based sensing technologies introduce significant privacy concerns. This study investigates the impact of transparent user interface design on user acceptance of these systems. We conducted an online study with 42 participants using prototypes varying in transparency, choice, and deception levels. The prototypes included three onboarding designs: (1) a traditional Terms and Conditions text, (2) a Business Nudge design that subtly encouraged users to accept default data-sharing options, and (3) a Transparent Walk-Through that provided clear, step-by-step explanations of data use and privacy policies. Our findings indicate that transparent design significantly affects user experience measures, including perceived creepiness, trust in data use, and trustworthiness of content. Transparent onboarding processes enhanced user experience and trust without significantly increasing onboarding time. These findings offer practical guidance for designing user-friendly and privacy-respecting in-car health monitoring systems.},
  numpages      = 6,
  keywords      = {Creepiness, In-Car Health Monitoring, Online Study, Pervasive Sensing, Privacy, Technology Acceptance, Transparent Design, Trustworthiness, User Experience, Vehicle},
  arxiv         = {2408.15177},
  archiveprefix = {arXiv},
  primaryclass  = {cs.HC},
  bibtex_show   = {true},
  selected      = {true},
  preview       = {InCabin_Privacy.png},
  abbr          = {AutoUI WiP},
  tldr          = {Transparently designed privacy onboarding can enhance user trust in camera-based in-car health monitoring systems.}
}

@article{sandhaus_student_2024,
  title         = {Student Reflections on Self-Initiated GenAI Use in HCI Education},
  author        = {Sandhaus, Hauke and Parreira, Maria Teresa and Ju, Wendy},
  year          = 2024,
  month         = may,
  journal       = {LLMs as Research Tools Workshop at CHI Conference},
  location      = {Honolulu, Hawaii, USA},
  abstract      = {
                   This study explores students' self-initiated use of Generative Artificial Intelligence (GenAI) tools in an interactive systems design class. Through 12 group interviews, students revealed the dual nature of GenAI in (1) stimulating creativity and (2) speeding up design iterations, alongside concerns over its potential to cause shallow learning and reliance. GenAI's benefits were pronounced in the execution phase of design, aiding rapid prototyping and ideation, while its use in initial insight generation posed risks to depth and reflective practice. This reflection highlights the complex role of GenAI in Human-Computer Interaction education, emphasizing the need for balanced integration to leverage its advantages without compromising fundamental learning outcomes.
                   },
  language      = {en},
  primaryclass  = {cs.HC},
  preview       = {GenAI_Device.png},
  arxiv         = {2405.01467},
  archiveprefix = {arXiv},
  bibtex_show   = {false},
  html          = {https://sites.google.com/view/llmsindatawork/accepted-papers},
  pdf           = {Sandhaus_2024_CHI_WS_LLMs_in_HCI_Research.pdf},
  selected      = {true},
  abbr          = {CHI Workshop},
  url           = {https://arxiv.org/abs/2405.01467},
  eprint        = {2405.01467},
  url           = {https://arxiv.org/abs/2405.01467},
  tldr          = {Generative AI tools in HCI design can accelerate iterations, but also raise concerns among students about shallow learning.}
}

@article{rhomberg_towards_2024,
  title       = {Towards Quantifying Ethical User Experience: Evaluating User Perceptions of Dark Patterns in Social Media},
  author      = {Rhomberg*, Doris Maria and Sandhaus*, Hauke},
  year        = 2024,
  month       = may,
  journal     = {
                 Mobilizing Research and Regulatory Action on Dark Patterns and Deceptive Design Practices Workshop at CHI Conference on Human Factors in Computing Systems
                 },
  location    = {Honolulu, Hawaii, USA},
  abstract    = {
                 No standardized questionnaire currently incorporates an ethical dimension for assessing User Experience (UX). We explored how the ethicality of interface design is reflected in current UX metrics and how they could be extended. To this end, we adapted the User Experience Questionnaire (UEQ) and enriched it with supplementary items specifically designed to capture user responses on social media to unethical interface designs, commonly referred to as 'dark patterns'. Through an exploratory analysis of a survey involving 120 participants who evaluated a selection of 15 social media dark patterns, we found preliminary evidence that (1) an aggregated UX score using items from the User Experience Questionnaire does not effectively indicate unethical user interface design. Instead, (2) subscale measures from the questionnaire show a relationship with unethical design. Furthermore, extending the User Experience Questionnaire seems promising, as (3) users can identify interfaces with addictive and pressuring properties, and (4) evaluations demonstrate consistency within groups of unethical design strategies.
                 },
  language    = {en},
  pdf         = {https://ceur-ws.org/Vol-3720/paper11.pdf},
  bibtex_show = {true},
  html        = {https://ceur-ws.org/Vol-3720/},
  preview     = {Ethical_UEQ.png},
  selected    = {true},
  abbr        = {CHI Workshop},
  note        = {* = equal contribution},
  tldr        = {Only a modified User Experience Questionnaire can explicate unethical aspects of social media interfaces.}
}

@article{Harvey2024-gn,
  title         = {The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology},
  author        = {Harvey, Emma and Sandhaus, Hauke and Jacobs, Abigail Z and Moss, Emanuel and Sloane, Mona},
  year          = 2024,
  month         = jan,
  journal       = {Proceedings of the CHI Conference on Human Factors in Computing Systems},
  arxiv         = {2401.10877},
  archiveprefix = {arXiv},
  primaryclass  = {cs.CY},
  bibtex_show   = {true},
  publisher     = {Association for Computing Machinery},
  address       = {New York, NY, USA},
  articleno     = {768},
  numpages      = {23},
  keywords      = {anthropometry, measurement, motion capture, social practices, validation},
  location      = {Honolulu, HI, USA},
  series        = {CHI '24},
  doi           = {10.1145/3613904.3642004},
  url           = {https://doi.org/10.1145/3613904.3642004},
  html          = {https://doi.org/10.1145/3613904.3642004},
  howpublished  = {CHI '24: Proceedings of the CHI Conference on Human Factors in Computing Systems},
  preview       = {Cadaver.png},
  selected      = {true},
  note          = {Best Paper Honorable Mention at CHI '24},
  abstract      = {
                   Motion capture systems, used across various domains, make body representations concrete through technical processes. We argue that the measurement of bodies and the validation of measurements for motion capture systems can be understood as social practices. By analyzing the findings of a systematic literature review (N=278) through the lens of social practice theory, we show how these practices, and their varying attention to errors, become ingrained in motion capture design and innovation over time. Moreover, we show how contemporary motion capture systems perpetuate assumptions about human bodies and their movements. We suggest that social practices of measurement and validation are ubiquitous in the development of data- and sensor-driven systems more broadly, and provide this work as a basis for investigating hidden design assumptions and their potential negative consequences in human-computer interaction.
                   },
  abbr          = {🏆 CHI},
  tldr          = {Motion capture systems are built and validated on old assumptions as a literature review using social practice theory shows.}
}


@inproceedings{Kim2023-no,
  title         = {VR Job Interview Using a Gender-Swapped Avatar},
  author        = {Kim*, Jieun and Sandhaus*, Hauke and Fussell, Susan R},
  year          = 2023,
  month         = oct,
  booktitle     = {Computer Supported Cooperative Work and Social Computing},
  publisher     = {ACM},
  address       = {New York, NY, USA},
  doi           = {10.1145/3584931.3606976},
  url           = {https://doi.org/10.1145/3584931.3606976},
  html          = {https://doi.org/10.1145/3584931.3606976},
  language      = {en},
  arxiv         = {2307.04247},
  eprint        = {2307.04247},
  archiveprefix = {arXiv},
  primaryclass  = {cs.HC},
  howpublished  = {CSCW '23 Companion},
  bibtex_show   = {true},
  preview       = {VR_Interview.png},
  selected      = {true},
  abstract      = {
                   Virtual Reality (VR) has emerged as a potential solution for mitigating bias in a job interview by hiding the applicants' demographic features. The current study examines the use of a gender-swapped avatar in a virtual job interview that affects the applicants' perceptions and their performance evaluated by recruiters. With a mixed-method approach, we first conducted a lab experiment (N=8) exploring how using a gender-swapped avatar in a virtual job interview impacts perceived anxiety, confidence, competence, and ability to perform. Then, a semi-structured interview investigated the participants' VR interview experiences using an avatar. Our findings suggest that using gender-swapped avatars may reduce the anxiety that job applicants will experience during the interview. Also, the affinity diagram produced seven key themes highlighting the advantages and limitations of VR as an interview platform. These findings contribute to the emerging field of VR-based recruitment and have practical implications for promoting diversity and inclusion in the hiring process.
                   },
  abbr          = {CSCW},
  note          = {* = equal contribution},
  tldr          = {Gender-swapped avatars in virtual job interviews influences applicant's perception of performance.}
}

@misc{sandhaus2023promoting,
  title         = {Promoting Bright Patterns},
  author        = {Hauke Sandhaus},
  year          = 2023,
  website       = {https://brightpatterns.org/},
  arxiv         = {2304.01157},
  eprint        = {2304.01157},
  archiveprefix = {arXiv},
  primaryclass  = {cs.HC},
  howpublished  = {CHI '23 Workshop: Designing Technology and Policy Simultaneously},
  bibtex_show   = {true},
  preview       = {Patterns.png},
  selected      = {true},
  note          = {This paper started the <a href="https://brightpatterns.org/" target="_blank">brightpatterns.org</a> website},
  abstract      = {
                   User experience designers are facing increasing scrutiny and criticism for creating harmful technologies, leading to a pushback against unethical design practices. While clear-cut harmful practices such as dark patterns have received attention, trends towards automation, personalization, and recommendation present more ambiguous ethical challenges. To address potential harm in these "gray" instances, we propose the concept of "bright patterns" - persuasive design solutions that prioritize user goals and well-being over their desires and business objectives. The ambition of this paper is threefold: to define the term "bright patterns", to provide examples of such patterns, and to advocate for the adoption of bright patterns through policymaking.
                   },
  abbr          = {CHI Workshop},
  tldr          = {The first definition of "bright patterns" is accompanied by examples that illustrate corporate use of persuasive design in support of user goals over their desires and business objectives.}
}

@misc{sandhaus2023prototyping,
  title         = {Towards Prototyping Driverless Vehicle Behaviors, City Design, and Policies Simultaneously},
  author        = {Hauke Sandhaus and Wendy Ju and Qian Yang},
  year          = 2023,
  arxiv         = {2304.06639},
  eprint        = {2304.06639},
  archiveprefix = {arXiv},
  primaryclass  = {cs.HC},
  howpublished  = {CHI '23 Workshop: Designing Technology and Policy Simultaneously},
  bibtex_show   = {true},
  preview       = {AV_Policy_Design.png},
  selected      = {true},
  abstract      = {
                   Autonomous Vehicles (AVs) can potentially improve urban living by reducing accidents, increasing transportation accessibility and equity, and decreasing emissions. Realizing these promises requires the innovations of AV driving behaviors, city plans and infrastructure, and traffic and transportation policies to join forces. However, the complex interdependencies among AV, city, and policy design issues can hinder their innovation. We argue the path towards better AV cities is not a process of matching city designs and policies with AVs' technological innovations, but a process of iterative prototyping of all three simultaneously: Innovations can happen step-wise as the knot of AV, city, and policy design loosens and tightens, unwinds and reties. In this paper, we ask: How can innovators innovate AVs, city environments, and policies simultaneously and productively toward better AV cities? The paper has two parts. First, we map out the interconnections among the many AV, city, and policy design decisions, based on a literature review spanning HCI/HRI, transportation science, urban studies, law and policy, operations research, economy, and philosophy. This map can help innovators identify design constraints and opportunities across the traditional AV/city/policy design disciplinary bounds. Second, we review the respective methods for AV, city, and policy design, and identify key barriers in combining them: (1) Organizational barriers to AV-city-policy design collaboration, (2) computational barriers to multi-granularity AV-city-policy simulation, and (3) different assumptions and goals in joint AV-city-policy optimization. We discuss two broad approaches that can potentially address these challenges, namely, "low-fidelity integrative City-AV-Policy Simulation (iCAPS)" and "participatory design optimization".
                   },
  abbr          = {CHI Workshop},
  tldr          = {Maps out the interdependencies between AV, city, and policy design and discusses methods for iteratively prototyping all three simultaneously.}
}

@inproceedings{Sandhaus2018-el,
  title       = {A WOZ Study of Feedforward Information on an Ambient Display in Autonomous Cars},
  author      = {Sandhaus, Hauke and Hornecker, Eva},
  year        = 2018,
  month       = oct,
  booktitle   = {The 31st Annual {ACM} Symposium on User Interface Software and Technology Adjunct Proceedings},
  location    = {Berlin, Germany},
  publisher   = {Association for Computing Machinery},
  address     = {New York, NY, USA},
  series      = {UIST '18 Adjunct},
  pages       = {90--92},
  doi         = {10.1145/3266037.3266111},
  isbn        = {9781450359498},
  url         = {https://doi.org/10.1145/3266037.3266111},
  abstract    = {
                 We describe the development and user testing of an ambient display for autonomous vehicles. Instead of providing feedback about driving actions, once executed, it communicates driving decisions in advance, via light signals in passengers' peripheral vision. This ambient display was tested in a WoZ-based on-the-road-driving simulation of a fully autonomous vehicle. Findings from a preliminary study with 14 participants suggest that such a display might be particularly useful to communicate upcoming inertia changes for passengers.
                 },
  keywords    = {on-road simulation, autonomous vehicle interfaces, methodology, ambient display},
  bibtex_show = {true},
  preview     = {AV_ceiling.png},
  html        = {https://dl.acm.org/doi/10.1145/3266037.3266111},
  selected    = {false},
  abbr        = {UIST},
  tldr        = {Ambient displays in autonomous vehicles can subtly communicate driving decisions to passengers (Master Thesis).}
}

@article{Martinez2018-xc,
  title       = {Smart Textiles in the Performing Arts},
  author      = {Martinez, Aline and Honauer, Michaela and Sandhaus, Hauke and Hornecker, Eva},
  year        = 2018,
  journal     = {Textiles, Identity and Innovation: Design the Future},
  publisher   = {Taylor & Francis},
  url         = {https://www.taylorfrancis.com/chapters/edit/10.1201/9781315100210-57/smart-textiles-performing-arts-aline-martinez-michaela-honauer-hauke-sandhaus-eva-hornecker},
  abstract    = {
                 We present the Sonification Costume, an interactive costume created for modern dance performances, that makes movements perceivable through sound. We created it in the context of studying textile-based sensors, and here describe the exploration of different production techniques, which led to a knitted whole-body suit with seamlessly integrated stretch sensors. Self-reflection and a user study reveal that the costume concept is interesting to dancers and how we can further improve textile-integrated sensors.
                 },
  bibtex_show = {true},
  preview     = {dancer.png},
  html        = {https://www.taylorfrancis.com/chapters/edit/10.1201/9781315100210-57/smart-textiles-performing-arts-aline-martinez-michaela-honauer-hauke-sandhaus-eva-hornecker},
  selected    = {false},
  abbr        = {D TEX},
  tldr        = {Our dance costume using smart textiles makes movements perceivable through sound.}
}

@mastersthesis{Sandhaus2015-in,
  title       = {Development of a {3D} Navigable Interface for a Touchless Showcase},
  author      = {Sandhaus, Hauke},
  year        = 2015,
  school      = {University of Twente},
  abstract    = {
                 Due to widespread usage of touchscreens, users have accepted interaction without haptic feedback. Commercial game consoles have introduced users to touchless input and natural user interfaces. Only recently it has become technically possible to track human hand skeleton in high detail, precision, and low latency contactless. This report describes the design process for the user experience, user interface, and interaction interface of a touchless showcase using skeletal hand tracking. The project extends on existing hardware, compares current approaches, researches on the user group, and rebuilds the software, based on these findings, from scratch. To allow input, multiple interactions and 3D buttons were developed. In a user experiment, these were tested. A final prototype was implemented on two showcases for a month and compared to the existing software. The findings suggest that users want more natural and direct interactions. Missing physical feedback, non-existent depth perception on traditional screens, and unfamiliar gesture language are hindrances but can be overcome with the use of good visual cues. Future work on the software is solely on refinement. Some of the interactions investigated in this thesis will prevail, while some might appear in other contexts.
                 },
  bibtex_show = {true},
  preview     = {hand_gesture.png},
  html        = {https://essay.utwente.nl/70885/},
  selected    = {false},
  abbr        = {UT},
  tldr        = {An intuitive 3D navigable interface for a touchless showcase using skeletal hand tracking (Bachelor Thesis).}
}