Klen Čopič Pucihar

Jens Grubert

Matjaž Kljun
email: matjaz.kljun@famnit.upr.si

Dual Camera Magic Lens for Handheld AR Sketching

Keywords: Magic-lens, dual-camera, sketching, trace-drawing, virtualtracing

de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Sketching is an important ancient human skill stimulating creative, visual and spatial thinking. Computer systems that support sketching have been studied since the early days of computer science [START_REF] Sutherland | Sketchpad: A Man-Machine Graphical Communication System[END_REF]. Through the development of mobile computing devices, such as smartphones, Magic Lens (ML) became a popular interface to support user sketching (e.g. [START_REF] Hagbi | In-Place Sketching for Content Authoring in Augmented Reality Games[END_REF][START_REF] Čopič Pucihar | The use of surrounding visual context in handheld AR: device vs. user perspective rendering[END_REF][START_REF] Seichter | Sketchand+[END_REF][START_REF] Xin | Napkin sketch: handheld mixed reality 3D sketching[END_REF][START_REF] Yee | Augmented Reality In-Situ 3D Sketching of Physical Objects[END_REF]). ML acts as filter augmenting the scene with additional digital content, for example, by adding 3D models based on a recognized paper sketch [START_REF] Hagbi | In-Place Sketching for Content Authoring in Augmented Reality Games[END_REF] or by allowing the creation of new 3D content [START_REF] Seichter | Sketchand+[END_REF][START_REF] Yee | Augmented Reality In-Situ 3D Sketching of Physical Objects[END_REF]. In this paper we explore how novice users can be supported in creating physical sketches through virtual tracing, i.e. creating a physical sketch on paper given a virtual image on the handheld device. The core challenge for this (and other sketching) tasks, which involve a physical pen and paper, is to provide accurate and robust pose tracking without disrupting the sketching process. So far, AR sketching systems focused on authoring digital objects and relied on external tracking systems (e.g. [START_REF] Seichter | Sketchand+[END_REF]) or on marker based tracking (e.g. [START_REF] Xin | Napkin sketch: handheld mixed reality 3D sketching[END_REF]). Here we focus on utilizing AR as a crafting tool for curtain of real objects (e.g. pen drawings). While marker based tracking would allow in-situ sketching on physical paper in otherwise unprepared environments (Fig 1b .), it limits the sketching experience in a fundamental way: the marker has to be in the camera view taking away valuable space for sketching. While approaches, such as contour tracking [START_REF] Hagbi | Shape Recognition and Pose Estimation for Mobile Augmented Reality[END_REF][START_REF] Hagbi | In-Place Sketching for Content Authoring in Augmented Reality Games[END_REF] circumvent the use of a marker, they are prone to failure as they cannot be occluded during interaction.

An alternative is to eliminate the need for pose tracking by placing the device and drawing surface at fixed position, such as in the case of a virtual mirror 1 or camera sketcher 2 . In both situations the user has to manually position the graphical content into the real world using traditional handheld interfaces such as static peephole (SP). Hence, if the drawing format does not fit into camera's field-of-view (FOV), the user is required to manually realign the graphic every time the device is moved.

In this paper we address the challenge of pose tracking while mitigating the effects on in-situ sketching experiences. Specifically, we evaluate how utilizing both front and back facing cameras concurrently could improve the utility of ML as a sketching aid tool. In order to do so, we: (i) design and build a Dual Camera Magic Lens (D-ML) system utilizing the front camera for pose tracking and the back camera for scene capture and rendering; (ii) evaluate the proposed solution on a commercially available handheld device by conducting a preliminary user study with 6 participants performing virtual tracing task. We compare 3 interaction methods: Static Peephole (SP), Magic Lens (ML) with fiducial marker and Dual Camera Magic Lens (D-ML).

Dual Camera Magic Lens

In contrast to using the back facing camera as in standard handheld AR applications we propose to utilize the front facing camera for pose tracking while providing the view of the scene through the back facing camera.

We do this in order to mitigate the effects on in-situ sketching experiences.

In order to enable front camera pose tracking, a marker is placed above the drawing surface in parallel orientation (in our case ca. 60cm, see Figure 1c.). As the tracking and rendering camera are not the same, a set of additional transformations (Figure 1d.) needs to be added to the tracked pose result (on Figure 2a. denoted as RT FC->TM ). However, as the two cameras on the phone are fixed and the top marker is rigidly attached above the drawing area, the only two transformations that change are RT FC->TM and RT BC->DS . Hence, as long as the front camera tracking is successful and the two constant transformations are known, RT BC->DS can be calculated (Figure 1d.).

User Study

The preliminary user study asked participants to perform a virtual tracing task on A3 paper. Participants were instructed to sit at a table and draw a cartoon character as quickly and as accurately as possible. To estimate participants' perceived satisfaction we are utilizing the "overall reactions" part of the Questionnaire for User Interaction Satisfaction (QUIS). In addition, we asked participants to rank interaction modes and to justify their choice. As objective measure we recorded task completion time.

We used a within-subjects design. Each participant drew three different contours with each interaction method: SP, ML, D-ML (see Fig. 1.). In SP manual alignment is required each time the phone is moved. In ML the drawing is possible whilst holding the phone in hand, whereas in SP it is mandatory to place the phone on the stand. In case of the D-ML, the stand was included because contrary to the tracker used in ML implementation, the tracker used in D-ML did not provide sufficiently robust and accurate orientation tracking results. By placing the phone on stand, we locked two degrees of freedom (Rx and Ry) improving tracking quality. We recognize this as a limitation. However, this decision was mandatory as poor tracking quality is bound to undermine performance of the proposed interaction paradigm. Additionally, as it should be possible to improve tracking performance of future D-ML systems, this does not undermine the proposed interaction concept per say, but rather affects the direct comparability of captured results. Yet, within the context of this study which is of exploratory nature and predominantly based on qualitative data, we consider our study design as appropriate.

( The study was completed by six participants. All were male, aged between 24 and 45 years. Due to the small number of participants nullhypothesis significance testing would result in poor statistical power. Hence, we present solely descriptive statistics. By overlaying drawn contours with template contours, two researchers independently and subjectively compared the quality of all three drawings for each participant and ranked drawings from best to worst. As shown in Figure 2.e, the comparison did not highlight any obvious deviations in obtained rankings. The results in Figure 2 also suggest that D-ML has the potential to (i) be the fastest mode; (ii) have the highest QUIS score across all properties; and (iii) have best rank. Again those results could not be reliably tested for statistical difference. Five participants that ranked D-ML as the best method justified their ranking choice by highlighting the advantage of automatic alignment and the fact that marker was not in their way.

Discussion and Conclusion

The results show that the utility of handheld AR as an in-situ sketching tool has the potential to be improved utilizing the D-ML approach. The designed and implemented system demonstrates such a solution is feasible on commercially available mobile devices. The preliminary study indicated that whilst achieving comparable quality of drawing, compared to SP and ML, D-ML is: potentially faster, users perceived higher satisfaction, and is preferred by participants. We believe the main reason for such a results is the fact the camera tracking did not interfere with user sketching. As underlined by participants themselves, the main benefit is automatic alignment of virtual image with the real word. Even though, until the user moves the marker, automatic alignment is also present in case of ML, in D-ML the user did not have to put up with the marker and avoid occluding the marker whilst trace drawing onto the paper. Although one could argue that the stand ambiguity increased the divide between the ML and D-ML, none of participants highlighted the stand as the factor influencing their ranking choice, suggesting the importance of the stand might be limited. However, in future work we will explore the effects of stand vs. handheld mode in more detail. Additionally, due to the small sample size our results are of preliminary nature and hence should be verified with a larger number of users. Finally, future research should look at less intrusive ways of placing a marker above the user.

Fig. 1 .

 1 Fig. 1. (a), (b) ,(c) Mobile device sketching aid tools on the study; (d) D-ML transformations;

Fig. 2 .

 2 Fig. 2. (a) Drawing quality ranking results (smaller is better); (b) "Overall reactions" part of QUIS scores [1-9]. (c) Preference ranking results (smaller is better); (d) Task time in minutes;

https://www.playosmo.com/en/

https://play.google.com/store/apps/details?id=com.aku.drawissimo(d)


Junia Anacleto

Sidney Fels
email: ssfels@ece.ubc.caroberto@robertocalderon.ca

Roberto Calderon

Junia 3p

Anacleto

Tutorial on Human Computer Interaction for Third Places -THCI-3P

Keywords: third place, thirdplaceness, pervasiveness, ubiquitousness, socialization 1

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

In his seminal book Ray Oldenburg [START_REF] Churchill | Cafe life in the digital age: augmenting information flow in a cafe-work-entertainment space[END_REF] defined "third places" as places where people come together as individuals to socialize and where communities are formed and shaped. These places are low profile, inclusive, accessible, accommodating, filled with regulars and a neutral ground for stimulating playful conversation. These properties can be found in urban third places such as coffee houses, bars, barber shops or community gardens. There is a growing interest in understanding the roles that pervasive technologies play on places where people interact with each other. Some of these places are "third places", or places that are neither home nor work -but are instead places like coffee shops and bars -where people deliberately come together to socialize. Third places are essential to social life because they provide a common ground where people with different interests and backgrounds can interact with each other and create the interpersonal ties that keep communities together. New location based technologies and ever increasing pervasive technologies such as situated displays, mobile devices, passive sensing, or geo-location, enhance such places and affect how we interact with other people. The need to understand how such technologies affect third places has been previously recognized by the HCI community. Yet, we believe that we are at a critical stage wherein it would be beneficial to the research community to discuss a common research agenda tackling common questions regarding human computer interaction in third places. The first Tutorial on Human Computer Interaction in Third Places (THCI-3P) will explore the intersection between different types of third places and human computer interaction. The tutorial will present to participants the theoretical basis of third place concepts as well as methods, techniques and tools to support developing current research and, through a field activity taking place within some of Bamberg third places, provide a common ground to build a research discussion agenda that can lead to collaborative research efforts.

Motivation and Expected Audience

Over the past decade, computing in public places that are dedicated for sociability has gained a growing interest from the research community [START_REF] Brignull | Enticing people to interact with large public displays in public spaces[END_REF][START_REF] O'hara | Understanding collective play in an urban screen game[END_REF][START_REF] Churchill | Cafe life in the digital age: augmenting information flow in a cafe-work-entertainment space[END_REF]. The challenges of collaborative and public interaction within such places, and the benefits of leveraging social technologies within third places, have been outlined by several researchers [START_REF] Hosio | Leveraging social networking services to encourage interaction in public spaces[END_REF][START_REF] Scheible | Story mashup: design and evaluation of novel interactive storytelling game for mobile and web users[END_REF]. Yet, with the increasing number of mobile devices with access to geo-location services, pervasive sensing and place-dependent services, new societal and technical challenges have begun to arise. This has sparked a growing interest from both industry and academia to better understand how humans interact with technologies in third places [START_REF] Mccarthy | Supporting community in third places with situated social software[END_REF][START_REF] Karnik | Social aspects of music and interactive technologies in facilitating face-to-face interactions in third places[END_REF][START_REF] Holopainen | Social and privacy aspects of a system for collaborative public expression[END_REF]. We believe that INTERACT2015 is scheduled at an ideal time and possesses an ideal venue to hold a Tutorial on Human Computer Interaction in Third Places. Not only is there a growing interest from the HCI community to understand the role of computing in third places, but there is also a recognition of the challenges that arise when designing third place interactions in novel settings; for example, online communities, non-technical communities, or communities in developing countries. We believe that a forum to introduce theoretical basis to discuss the questions arising from said challenges would not only be beneficial to the community, but would also be indispensible in consolidating a research agenda that reaches into the future of human computer interaction in places promoting the shaping of communities. In particular, the proposed tutorial will focus on the following questions: In what ways have ICT already altered existing third places or created new third places? (ix) How can ICT create the sense of thirdplaceness independent of architectural and temporal constrains?

Topics of Interest

HCI-3P will focus on the following topics, but similar topics and discussions will be welcomed for discussion during the tutorial.

• Novel interfaces to support human interaction in third places

Proposed Program

The structure of the tutorial is in four modules:

  (i) What are the roles of pervasive computing and sensing in third places? (ii) What are the paradigms to provide crowd interaction within third places? (iii) How can we design technologies that are natural and unobtrusive to existent third places? (iv) How does ICT affect the functioning of existing third places in the long term? (v) What defines a successful technological intervention of third places? (vi) How should ICT adapt to different types of third place communities? (vii) What defines the third place of the future and how should ICT support it? (viii)

Module 1 :

 1 Introduction, Concepts, Methods, Tools, Design for Third places. (2 hours) Module 2: Field Study, Exploratory research on thirdplaceness. (2 hours) Module 3: Compilation of observations, Discussions on third places' properties evolution into thirdplaceness, methods of evaluation. (3 hours) Module 4: Conclusions on how to apply the principles of thirdplaceness to define our next steps to keep the participants connected and engaged as a community that would meet from time to time at INTERACT or other venues, to continue evolving the concept of thirdplaceness, independent of architectural and temporal constrains. (1 hour)

5 Presenters

 5 Dr. Junia Anacleto, Professor, Ph.D. degree in Computational Physics, from the University of São Paulo USP, Brazil. She was a Visiting Researcher at the MediaLab MIT, Massachusetts Institute of Technology in 2006-2007. She is currently an International Visiting Research Scholar from Peter Wall Institute for Advanced Studies at University of British Columbia. She is a Professor at the Federal University of São Carlos, Department of Computing, Brazil. She is also the Coordinator of LIA -Advanced Interaction Laboratory. She has experience in the area of Computer Science, with emphasis on Human Computer Interaction focused on: Natural interactions, Culture, Education, Healthcare, Urban Computing, wearable technologies. Dr. Sidney Fels, Professor, Electrical & Computer Engineering. Ph.D., Toronto. Sid has worked in HCI, neural networks, intelligent agents and interactive arts for over ten years. He was visiting researcher at ATR Media Integration & Communications Research Laboratories (1996/7). His multimedia interactive artwork, the Iamascope, was exhibited world-wide. Sid created Glove-Talk II that maps hand gestures to speech. He was co-chair of Graphics Interface 2000. He leads the Human Communications Technology Laboratory and is Director of the Media and Graphics Interdisciplinary Centre. Roberto Calderon is a Ph.D. student at The University of British Columbia. His research focuses on the use of situated computing to support the forming of communities in urban third places. His approach brings together Architectural Design and Human Computer Interaction to the problem of third places. He has previously served on the organizing committee of the Interdisciplinary Workshop on Communication for Sustainable Communities collocated with SIGDOC'2010. All the presenters have previously served on the organizing committee of The First Workshop on Human Computer Interaction for Third Places HCI3P collocated with CHI'2013 and The Second Workshop on Human Computer Interaction for Third Places (HCI3P) collocated with DIS'2014.


Elaine Farrow
email: elaine.farrow@ed.ac.uk

Thomas Dickinson
email: thomas.dickinson@open.ac.uk

Matthew P Aylett
email: matthewa@inf.ed.ac.uk

Generating Narratives from Personal Digital Data: Using Sentiment, Themes, and Named Entities to Construct Stories

Keywords: social media, narrative, triptych, multi-media

As the quantity and variety of personal digital data shared on social media continues to grow, how can users make sense of it? There is growing interest among HCI researchers in using narrative techniques to support interpretation and understanding. This work describes our prototype application, ReelOut, which uses narrative techniques to allow users to understand their data as more than just a database. The online service extracts data from multiple social media sources and augments it with semantic information such as sentiment, themes, and named entities. The interactive editor automatically constructs a story by using unit selection to fit data units to a simple narrative structure. It allows the user to change the story interactively by rejecting certain units or selecting a new narrative target. Finally, images from the story can be exported as a video clip or a collage.

Introduction

Social media use has led to such an explosion in personal digital data that users can easily become lost and overwhelmed, and a common challenge for HCI researchers is to help users cope. Selection and summarization tasks (such as identifying a list of hashtags which are currently popular or reporting which Facebook posts got the most 'likes') represent a typical approach to improving understandingtreating it as a database to be queried.

In contrast, we often interpret our own experiences, desires, and motivations using stories not statistics. Both in the commercial world and in academia, interest is growing in bridging the gap between viewing personal digital data as a database, and viewing the data as (elements of) personal narratives. The use of narrative to make sense of our everyday lives is considered to be a fundamental human behavior [START_REF] Sarbin | Narrative psychology: The storied nature of human conduct[END_REF], and the exploration of narrative formats for data presentation can help HCI researchers understand how meaning is constructed through stories and how stories can be used to interpret data. There have been some recent popular examples of automatic narrative generation from social media data. For example, Facebook's A Look Back1 compiles users' most popular posts into a short film. However, as noted in previous research [START_REF] Schwanda Sosik | See friendship, sort of: How conversation and digital traces might support reflection on friendships[END_REF][START_REF] Thiry | Authoring personal histories: Exploring the timeline as a framework for meaning making[END_REF][START_REF] Zhao | Curation through use: Understanding the personal value of social media[END_REF], the resulting film is very much a finished product. Users can replace chosen posts with others from a limited selection, but have very little overall control.

The ReelOut application is part of a wider project in which we seek to build a novel text-driven software system that can automatically generate film-like life documentaries from personal digital data, and to explore the human experience and response to such systems. We aim to empower users by allowing them to interpret their data to suit their own vision of the narratives they see within their lives. ReelOut allows users to build stories from primitive units (such as tweets and Facebook posts) with reference to a particular narrative target: as a simple example for illustration, consider a story on the theme of 'food and drink' that starts with a negative sentiment and ends with a positive sentiment.

Our process is illustrated in Fig. 1. We extract text and metadata from a user's social media posts and augment it with semantic tags. Next, we employ a unit selection process borrowed from speech synthesis to fit the data to the desired narrative target. The user can change the story by rejecting certain units or selecting a new narrative target. Finally, the images associated with the generated story can be exported as a short movie clip or a collage of images. At the time of writing, our online service can extract data from Twitter and Facebook, with limited support for Instagram. We intend to add further platforms to this list in the near future. The sentiment of each post is calculated using Sentistrength,2 a popular sentiment analysis tool for short web texts. Entities such as locations are extracted using AlchemyAPI's3 entity extraction endpoint, while themes are identified using AlchemyAPI's taxonomy endpoint. Some social media posts, such as comments and replies, form a conversational thread. For these, we note which other units come before and after them in the thread. Finally, the data is passed to the interactive editor as a series of RLUnits, an XML format consisting of marked-up text and semantic tags (Fig. 2).

<rlunit id="15028" src="facebook" time="20091101:190400"> <image>...</image> <messagetext>Happy after dinner face</messagetext> <sentiment>positive</sentiment> <theme>food and drink</theme> </rlunit> Fig. 2. An RLUnit representing a Facebook post with a positive sentiment and a theme of 'food and drink' (the image URL is omitted due to space constraints).

The interactive editor (Fig. 3) provides a graphical user interface for story creation. By default, generated stories are sequences of three linked units (a triptych), corresponding to the classic 3-act structure of setup, confrontation, and resolution. The generated picture sequence can be exported as a short movie clip or saved as a collage of images. Our story generation algorithm is inspired by the unit selection process in speech synthesis, where many thousands of units are fitted to an utterance structure. We use dynamic programming to fit the marked-up data units (RLUnits) to a predefined narrative target, represented as an ordered collection of slots with associated semantic tags which constrain their contents.

Two cost functions are optimized to produce the output. The first, target cost, represents the fit with the narrative target: units which share semantic tags with the target slot will have a low target cost. The second, join cost, represents how connected two adjacent RLUnits are: units which have a similar set of semantic tags and appear in the correct order will have a low join cost.

The editor allows the user to set the target for each story slot interactively, using the semantic tags found in the extracted data. It also offers unit reselectionrejecting a particular unit and automatically selecting the next-best unit to fit that slota powerful method borrowed from speech synthesis, where it enables users to modify auto-matically synthesized utterances without requiring an understanding of the linguistic or phonetic structure of speech.

Conclusion and Future Work

Our novel end-to-end automatic narrative generation application, ReelOut, augments personal digital data from social media sites with semantic tags such as sentiment, themes, and named entities. It uses unit selection to build a story that fits a specified narrative target, and allows users to change the story interactively by rejecting particular units or selecting a new narrative target. It is extensible for further research and development.

We have run an initial evaluation of the story-generation algorithm by asking participants to look at picture sequences generated from public data (not their own), some generated by our system and others chosen at random [START_REF] Aylett | Generating narratives from personal digital data: Triptychs[END_REF]. We found that our system produced output which users rated significantly higher than random when asked "How much does this sequence of pictures tell a story?" We are currently working towards a user trial of the full system, allowing people to create and evaluate stories using their own personal digital data.

Our future plans include developing a data-driven event detection algorithm which will allow us to classify individual units as belonging to a larger event, such as 'starting school' or 'getting married'. We are also experimenting with ways to represent units which have text but no associated image, such as rendering the text itself as an image or sourcing a new image from an external source.

Our application demonstrates one important way HCI researchers can use narrative to help users to make sense of the growing mass of personal digital data which threatens to overwhelm themby automatically constructing stories.

Fig. 1 .

 1 Fig. 1. The processing pipeline

Fig. 3 .

 3 Fig. 3. The interactive editor, showing a story on the theme of 'food and drink' that starts with a negative sentiment and ends with a positive sentiment.

facebook.com/lookback

sentistrength.wlv.ac.uk

www.alchemyapi.com

Acknowledgments. This work was supported by EPSRC grant EP/L004062/1.


Helen Petrie
email: helen.petrie@york.ac.uk

Blaithin Gallagher
email: blaithing@gmail.com

Jenny Darzentas
email: jennyd@aegean.gr

Methods for undertaking research on technology with older and disabled people

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Developing interactive systems for people with disabilities and older people is becoming an important topic within HCI research and practice. As the population is aging [START_REF] Giannakouris | Ageing characterizes the demographic perspectives of the European societies[END_REF], the pressure to use technology to support people to live independently is increasing. But as yet, little attention has been paid to the methods used to conduct research on mainstream or assistive technologies for disabled or older people. A small number of published papers directly address these issues [e.g. 2, 3] and some papers mention challenges of working with these user groups in passing.

Objectives and Topics to be Addressed in the Workshop

The workshop will provide an opportunity for researchers and practitioners to discuss the advantages and disadvantages of existing research methods used in HCI when applied to working with older and disabled people for the elicitation of user needs, evaluation of technologies and understanding of the uses of technologies by these important user groups. It will also provide an opportunity to discuss innovations to methods and completely new methods that might have been developed in working with older and disabled people.

Topics to be addressed will include: advantages and disadvantages of methods of undertaking research on technology with older and disabled people, for mainstream or assistive technologies; practical problems of using existing methods; adaptations that need to be made for particular user groups; limitations in the application of particular methods; innovations in research methods to meet the requirements of particular user groups and innovative research methods; theories and application of inclusive design, design for all and universal design philosophies. Finally, the workshop is open to discussion of all methods, whether qualitative or quantitative, from participatory design to experimentation, and will include inclusive design approaches.

Organizers

This Workshop is organized on behalf of IFIP WG 13.

Target audience

Researchers and practitioners interested in working with disabled or older people in the design and development of mainstream or assistive technologies.

Expected outcomes

The workshop will contribute to the development of a better understanding of research methods for working with older and disabled people. In addition, the workshop will plan for further events, including a tutorial for new researchers in the field and a handbook on methods for working with older and disabled people.

  3 HCI and Disabilities by: Helen Petrie, Professor of HCI at the University of York and current chair of IFIP WG 13.3. Her research focuses on the design and evaluation of technology for disabled and older people. Dr Blaithin Gallagher, Head of Research and Projects at NCBI. She is Vice President of the European Network for Vision Impairment Training Education and Research (ENVITER) and on the Executive Committee of the European Society for Low vision Research and Rehabilitation (ESLRR). Dr Jenny Darzentas from the University of the Aegean. Her research focuses on the design of accessible and usable content.


Gregorio Convertino

Nancy Frishberg
email: nancyf@acm.org

Jettie Hoonhout
email: jettie.hoonhout@philips.com

Rosa Lanzilotti
email: rosa.lanzilotti@uniba.it

Marta Kristín Larusdottir

Effie Lai-Chong

Marta Kristín Lárusdóttir

Lai-Chong Law
email: elaw@mcs.le.ac.uk

The Landscape of UX Requirements Practices

Keywords: Requirements specification, usability, UX practices

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Workshop topic and rationale

The primary motivation for this workshop is the need for systematic methods, based on empirical research, to define and confirm statements of usability and UX requirements for software systems. The problem of omission or poor formalization of UX requirements is limiting the success of projects in the public and private sectors. For example, too many companies have not yet integrated usability and UX methods and approaches as part of the software development process. For the public sector, studies of ICT companies that work with public authorities in Europe suggest that a critical problem is the lack of formal UX requirements in the Call for Tenders or CfT (cf. Request for Proposals or RFP). In fact, during the implementation, the company that obtained the contract from the public authority is likely to focus only on the requirements agreed upon as part of the CfT. Thus, the contracting company has no incentives to consider additional requirements.

For the private sector, perhaps the hallmark of a successful UX professional is flexibility, due to the recurrent need for negotiation, tighter time constraints and multiple stakeholders. The post-hoc narratives of UX contributions to products often sound like the idealized exploratory phase followed by a narrowing of the scope with a steady progress toward a product that meets the requirements expressed by users. In practice, however, the real story often is of projects with processes and methods that differ widely across development projects but follow common principles and lead to similar artifacts, such as personas, story mapping, and prototypes. Some projects may never create a formal requirements document, but will reveal the increasingly formalized UX requirements through a sequence of prototypes and product versions. This is a challenge for requirement formalization methodsi.e., a workshop topic.

For both public and private endeavors, the problem of formalizing requirements is a balancing act among various factors, such as identifying the user classes and competing requirements for such user classes, satisfying the buyer, driving innovation, and keeping consistency among products from the same organization.

As the agile and lean software development processes become pervasive, renewed attention is necessary on defining more suitable methods to build and preserve highquality UX designs along the development process.

Target audience and expected outcomes

The workshop aims at bringing together researchers and practitioners who face the problem of formalizing usability or UX requirements and have tried effective methods to resolve it. The expected outcome of the workshop is a descriptive framework that helps to organize the current best practices and a set of recommendations for formalizing and verifying usability/UX requirements in specific contexts.

Workshop organizers

Gregorio Convertino, PhD, is a Senior User Researcher at Informatica. His research focuses on UX, information visualization, collaborative and social computing.

Nancy Frishberg, PhD, heads the User Research Program at Financial Engines, Inc. Her research interests include harnessing the creativity of groups, accessibility (for aging or Deaf populations), and successful UX in agile projects.

Jettie Hoonhout is a Senior Scientist at Philips Research. Her research interest is in methodologies, methods and tools that address the UX of products, and that support the development process of products and product-service concepts.

Rosa Lanzilotti is a researcher at the University of Bari (IT). Her research interests include usability and UX, accessibility, UX practices in industry and public institutions.

Marta Kristín Lárusdóttir is an assistant professor at Reykjavik University (IS). Her main research area is the interplay between usability and UX activities and software development processes.

Effie Lai-Chong Law is Reader at the University of Leicester (UK). Her research focuses are usability and UX methodologies and their applications in various contexts including education, health, law, and cultural heritage.


Martin Murer

Alexander Meschtscherjakov

Verena Fuchsberger

Manuel Giuliani

Katja Neureiter

Christiane Moser

Ilhan Aslan

Manfred Tscheligi

Contextual Interaction Design Research: Enabling HCI

scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

1

Contextual.Interaction.Design.Research

In our research activities (e.g., a seven-year basic research project on "Contextual Interfaces", focusing on contextual qualities and interaction in factories and cars) we acknowledge that interactions are heavily dependent on the concrete, situated characteristics of the context in which they take place. This understanding results in a methodological viewpoint, which we entitle 'contextual.interaction.design.research'. Contextual research expresses our devotion to rich ethnomethodologically informed studies as well as the development and refinement of according methods. Our interaction designs are on one hand informed by those studies, aiming for user experiences that reflect the situated qualities of the context we address. On the other hand, we consider design methods and processes as legitimate mode of inquiry, as means of critical reflection and exploration. With interaction design research we investigate and discuss the according methodological challenges and opportunities.

Enabling HCI -The Case of six Research Groups

The Center is organized in six research groups that address particular aspects of HCI in its relation to specific areas of human life. While the respective epistemologies differ, Enabling HCI guides all of them. With Contextual Persuasion we seek to enable individuals and groups to change their attitude and behavior by means of interactive technologies. Research includes fieldwork in persuasive potentials, design of behavior change systems, and in-situ studies of persuasive technologies. With research on Human-Robot Interaction we study how multimodal and natural interaction can enable social interaction with robots in challenging contexts such as industrial production, tele-operated medicine, and robots in public spaces.

We aim to enable new qualities of interaction through enhancing the knowledge about experiential and material use and design practices. This includes theoretical framings of the materiality of interactions, user experience, and constructive design research (Material & Experiential Foundations). By Embodied Interaction Design we explore sensorimotor skills and couplings to enable extended bodily perception and experiences. Through reflective design, engineering, and craft we seek to understand the material qualities of novel technologies.

The group on Cooperation Experience aims to enable and understand meaningful computer mediated cooperation by investigating needs for successful cooperative processes (e.g., social presence) as well as identifying the nature of resources within social cooperation (social capital). Enhancing Life Experiences seeks to enable and promote social interaction and health/well-being of selected user groups in the (extended) home by creating valuable technical solutions in a user-centered design approach. The respective focus lies on enhancing peoples' life experiences.

The different research topics are bridged with at the moment two dedicated contextual laboratories (Car Interaction Lab and Fabrication Experience Lab) that allow our researchers to design, prototype, and study contextual interactions.

Conclusion

The variety of viewpoints has allowed us to design new experiences through different HCI lenses with a particular focus on the context in which the interaction takes place, emphasizing the essence of interaction through making and reflection processes in our research. It enables us to focus our research on different core topics in HCI and at the same time use dedicated contexts as enabling design and research spaces. By building an environment in which researchers from different HCI domains can collaboratively create meaningful and tangible interaction designs in an atmosphere that is charged with experiential qualities of the contexts we address, we enrich both the design process, as well as the outcome of our research efforts. With contextual.interaction.design.research we have been able to identify relevant aspects of the constant, situated interplay between users and artifacts in order to create artifacts that enable humans to experience novel, exceptional, or disruptive interactions, aiming to go beyond current trends and imaginations.


André Schmidt

Mads Kleemann
email: madskleemann@me.com

Timothy Merritt
email: timothy.merritt@aarch.dk

Ted Selker
email: ted.selker@gmail.com

Tactile Communication in Extreme Contexts: Exploring the Design Space Through Kiteboarding

Keywords: Tactile communication, research through design, extreme sports, kiteboarding 1

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

This study explores communication modalities to provide feedback using kiteboarding as a platform to examine the design space and better understand the experience. Kiteboarding (also referred to as kitesurfing) is a water-sport, inspired by wakeboarding, windsurfing, and paragliding. The kite pulls a person standing on a special purpose surfboard or a kiteboard across the surface of the water. It requires expert control of a 6-17 square meter kite producing considerable pulling power and speed similar to a ski boat. The kite is connected to the rider typically by four lines 20 meters in length, which are controlled through a hand-held control bar and a harness worn around the waist. The activity is commonly described as one of the most complex coordinated activities people engage in. Common to all kiteboarding skills is that kite and board control and timing of maneuvers is crucial to success. Giving and receiving feedback on technique is challenging as the rider is separated from others on a windy day during the activity. Hand-over-hand training is inappropriate and post session reviews do not provide real-time feedback. Fig. 1. Kiteboarding --a rider is sailing on the water surface using a kite as the power source.

Discrete signals can be effectively communicated with voice and tactile means, for example the instructor can yell, "Let go of the bar!" and a student will drop the control bar. In a similar way, a sharp tactile pulse might be used to carry the same meaning. This would seem to be a natural feedback, aligned with and transmitted through the control bar. In the context of scuba diving, instructors often carry a metal rod to tap against an air tank propagating a sharp noise through the water, an effective blunt communication for alerting student divers to attend to the instructor. We are only beginning to understand the impact to human performance and experience when multimodal communication technologies support performance and skill acquisition [START_REF] Jensen | Design Sensitivities for Interactive Sporttraining Games[END_REF]. There is similar interest in exploring directional control and communicating continuous values, as well as directional guidance in real-time tasks of navigation using a mix of tactile and visual cues [START_REF] Cao | Evaluating informative auditory and tactile cues for in-vehicle information systems[END_REF][START_REF] Ege | Vibrotactile feedback in steering wheel reduces navigation errors during gps-guided car driving[END_REF][START_REF] Prasad | Haptimoto: turn-by-turn haptic route guidance interface for motorcyclists[END_REF].

It is an interesting direction for research to explore how communication channels impact cognitive resources and experiential effects of activities. Existing research often involves building of prototypes with isolated tests of individual modalities. In this paper we explore the language of multimodal interactions to support performance and experience in the extreme sport of kiteboarding by focusing on the modes of voice and tactile feedback.

We present an augmented kiteboarding control bar prototype that provides tactile communication between the rider and the instructor. It will be used in studies that examine the performance of steering a kite with the help of three different types of feedback including vibrotactile feedback alone, vibrotactile feedback combined with voice feedback, and voice feedback alone.

The rest of this paper is organised as follows. First we describe the sport of kiteboarding to provide a better understanding of the disciplines, demands on the rider, experiential goals and identify opportunities for technology to support the experience. We identify communication as an area to explore further and describe the development of a prototype control bar that facilitates communication. We then describe two user evaluations that explore the usefulness and experiences of voice and vibrotactile feedback separately and combined. We then relate the results of the evaluations to the existing research to provide insights for designers focused on the context of extreme sports.

Kiteboarding

In this section kiteboarding will be described; this emerged from expert and instructor interviews, observations and the authors' combined experience of more than 20 years in the sport. Kites are usually between 6m 2 and 17m 2 depending on the wind speed and rider weight. It is controlled through lines between 10-30m long (see Figure 1). Steering left is done by pulling the left side of the control bar, same for right. Some novices think turning the bar like a steering wheel will cause the kite to turnthis is not the case, tension on the steering line must be applied. Power is controlled by either pushing the whole bar away, which depowers the kite, or by pulling the bar towards the body, which powers up the kite. Board control including edging and balance are also crucial skills for kitesurfing.

Communication

While kite instructors might demonstrate their skills next to a student, interviews with 5 kiteboarding instructors revealed the preferred method of communication between students and instructors is through voice. However, during training and riding, the athletes are quickly separated. In these situations, hand signals are used to communicate commands and requests. Radio communication helmets are used by some kiteschools, however, they are expensive and delicate, and students often become overwhelmed with the water noise and poor sound. Instructors reported to us that students stop responding to voice commands during high levels of excitement. Perhaps the overloaded audio channel leads to confusion, change blindness, or that instructions blend in with environmental noise.

Progression

There are different ways a rider typically progresses in training depending on their skill level. Kitesurfing is very difficult to learn without taking a beginner's course [16], while an intermediate rider or expert typically learns through watching others, viewing instructional videos, and through much practice. For feedback, riders often return to shore for critique from others. Kite control is a crucial component for the progression of riders at all levels. Training could involve moving the kite to a position in the sky requested by the instructor, holding it steady at one position, or moving it through various positions in a sequence. The kite position is typically explained according to the positions of a clock face as shown in Figure 2. The entire face is referred to as the wind window as shown in Figure 3. Holding at 12 o'clock is directly overhead, while a kite positioned at 9 or 3 is nearly touching the ground.

Neutral zone

Power zone

Wind direction

Technology for Kiteboarding

Already within the sport of kiteboarding there are various technologies used including a personal video documentation camera (e.g. GoPro) to capture video, GPS or a smartphone to map a route. Other products promise to track and replay kite board movements in virtual replay [33]. This enables riders to evaluate height, length and speed of jumps etc. We recognized the challenges and needs for communicating guidance and suggestions for skill improvement, yet we find few examples of technology to support this. Furthermore, there has not been sufficient attention given to the physical equipment including control bar, board, harness, which provide opportunities for contact to the body and capacity for holding embedded technology.

Related Work

Work that has examined technologies supporting physical activities include research focused on technologies in sports and physical activities, technologies supporting navigation, and research exploring the limits of human perception in various modalities. Of particular interest is the research that involves embedding communication technologies into activities to better understand the context and to explore the performance and responses to the technology-based interventions.

Technologies in Sports and Physical Activity

Research has gone into exploring interactive technologies and how it can support physical activities by improving performance, experience and motivating physical activity. Much research has focused on exertion interfaces which examine technologies to foster exercise interactions [START_REF] Mueller | Exertion Interfaces: Sports over a Distance for Social Bonding and Fun[END_REF], enhancing social play through familiar activities, using elements from computer games to motivate physical activity and new forms of expression and performance. Various examples of research explore how technology can improve the performance and technique of athletes [START_REF] Baca | Rapid Feedback Systems for Elite Sports Training[END_REF][START_REF] Van Erp | Application of tactile displays in sports: where to, how and when to move[END_REF][START_REF] Solomon | Ultimate trainer: Instructional feedback for ultimate frisbee players[END_REF], the experience of performing the exertion activities [START_REF] Mueller | Designing Sports: A Framework for Exertion Games[END_REF][START_REF] Pijnappel | 4 Design Themes for Skateboarding[END_REF], and designing for such interac-Fig. 2. A clock face is used to describe the kite position in the wind window. tions [START_REF] Graether | Joggobot: A Flying Robot As Jogging Companion[END_REF][START_REF] Pijnappel | Designing Interactive Technology for Skateboarding[END_REF]. Research has distinguished between interactive sport-training games and integrated systems [START_REF] Jensen | Design Sensitivities for Interactive Sporttraining Games[END_REF]. These games refer to systems that train activities that could translate back into the sport activity. These systems include technologies that embed directly into the activity and seek to improve performance and training. Training systems have been studied using tactile instructions to give athletes cues on navigation, timing and posture in different sports [START_REF] Van Erp | Application of tactile displays in sports: where to, how and when to move[END_REF][START_REF] Spelmezan | An investigation into the use of tactile instructions in snowboarding[END_REF].

Technologies for Navigation

We examine research involving audio, tactile, and/or haptic means of delivering feedback, as these modalities might free the rider's visual sense that is generally focused on their equipment, spotting and avoiding obstacles. Navigational cues are delivered using simple, symbolic, ambient and spatial representations of directions. Various examples of research using audio technologies for navigation include simple directional voice commands for visually impaired [START_REF] Loomis | Navigation system for the blind: Auditory display modes and guidance[END_REF], and spatial sounds presenting general directions [START_REF] Holland | Audiogps: Spatial audio navigation with a minimal attention interface[END_REF][START_REF] Zwinderman | Oh music, where art thou?[END_REF]. Research projects have focused on aiding navigation and orientation through the use of tactile feedback as described in [START_REF] Van Erp | Waypoint Navigation with a Vibrotactile Waist Belt[END_REF] including tactile feedback delivered to various parts of the body through wearable and mobile devices. Research explored smartphones [START_REF] Pielot | Pocketnavigator: studying tactile navigation systems in-situ[END_REF], tactile belts [START_REF] Heuten | Tactile Wayfinder: A Non-visual Support System for Wayfinding[END_REF][START_REF] Tsukada | Activebelt: Belt-type wearable tactile display for directional navigation[END_REF] and shoes [21] to give simple directional cues, as well as symbolic cues for communicating direction [START_REF] Velazquez | A shoe-integrated tactile display for directional navigation[END_REF] and ambient guidance [START_REF] Frey | CabBoots: Shoes with Integrated Guidance System[END_REF][START_REF] Takeuchi | Gilded Gait: Reshaping the Urban Experience with Augmented Footsteps[END_REF]. In terms of haptic research, simple directional signals have been explored for guiding pedestrians [START_REF] Maeda | Shaking the world: galvanic vestibular stimulation as a novel sensation interface[END_REF] and navigation through symbolic haptic means in the form of shape and weight shifting technologies [START_REF] Hemmert | Take Me by the Hand: Haptic Compasses in Mobile Devices Through Shape Change and Weight Shift[END_REF]. More direct forms of guidance are also relevant including examples of actually pulling the user's body [START_REF] Amemiya | Lead-me Interface for a Pulling Sensation from Handheld Devices[END_REF][START_REF] Kojima | Pull-navi: a novel tactile navigation interface by pulling the ears[END_REF] or providing guidance through shape-changing mobile devices that simulate a physical guide or handrail [START_REF] Imamura | HAPMAP: Haptic Walking Navigation System with Support by the Sense of Handrail[END_REF].

Human Factors in Multimodal Interfaces

The capacity and limits of human perception and attention in a high cognitive workload environment have been explored through research focused on human modalities, attention and processing resources, as well as insights about mapping the modality to the appropriate information. Multiple Resource Theory proposes that humans can process information from multiple sensory channels simultaneously, and that in some situations it can be more effective to divide attention between visual and auditory channels rather than loading a single sensory channel [START_REF] Wickens | Multiple resources and performance prediction[END_REF]. Changes in modalities can be easily overlooked due to lack of attention. [START_REF] Rensink | To see or not to see: The need for attention to perceive changes in scenes[END_REF]. Change blindness can occur in vision, in the audition (change deafness), or even within the tactile modality [START_REF] Gallace | The failure to detect tactile change: A tactile analogue of visual change blindness[END_REF]. There are also attempts at providing overall guidance in selection of communication modality and task [START_REF] Van Erp | Multimodal interfaces: a framework based on modality appropriateness[END_REF].

Research Problem

While there is much work focused on technologies to support various activities, there has been less focus on communication in the demanding context of extreme sports. With kiteboarding as a platform for exploration of high demands on the user, we examine the use of voice and tactile communication technology to support the needs of kiteboarders. How does choice of modality (voice or tactile) impact the effectiveness of control guidance? Are there any interactions or complimentary effects of using voice and tactile feedback together? Aside from objective measurements of performance, are there subjective measures that reveal any preferences and experiential differences?

Design and implementation

When a student is learning how to sail a boat, an instructor is sitting beside the student and is able to assert direct control and manipulate the same controls as the student. This is known as hand-over-hand training through a shared object. However in the context of kiteboarding this is not possible due to the separation of instructor and student/rider. This is problematic for both the beginner but also for the intermediate or expert rider who wants direct feedback on his technique. The overall vision with our design has been to capture the benefits of hand-over-hand instructions. We present the current prototype that aims to capture this vision followed by details about the issues we explored during the design process.

Current Implementation

By adopting haptic feedback technologies in a "shared object" model as illustrated in the inTouch system [START_REF] Brave | inTouch. In: SIGGRAPH'98[END_REF], the design vision is a control bar that connects two people through vibrotactile feedback. In Figure 4A, both the instructor and the student are holding a control bar, however the instructor bar is not attached to a kite. When the instructor moves the bar to a new position the student bar will vibrate in the corresponding side of the bar, indicating the direction to move, and thereby which side to pull as shown in Figure 4B. This mapping is similar to the metaphor of "tapping on one's shoulder" [START_REF] Prasad | Haptigo: A navigational "tap on the shoulder[END_REF]. When the student bar is at the same position as the instructor bar, the directional vibrotactile signal will stop and a short tactile confirmation cue could be given. For testing purposes, only the student bar is part of the current implementation. It consists of the tactile kite control bar and a Java-based test control system on a PC for facilitating evaluations and logging of performance data. The tactile bar prototype is shown in Figure 5, and consists of (A) a waist harness for holding an Arduino Leonardo microcontroller inside a box (B), a kite control bar equipped with two large mass Eccentric Rotating Mass (ERM) vibrotactile actuators from a Playstation controller at each end of the bar (C and E), (D) a Sparkfun MMA7361 3-axis accelerometer and a 6mm ERM vibrotactile actuator in the middle of the bar. The bar is attached to the harness using a leash (G) ensuring that the kite cannot fly away accidentally. A signal wire along the leash (F) is attached making communication between the bar and micro controller possible. Based on accelerometer readings, the prototype is able to provide tactile feedback in the right and left hand side, or both, simultaneously. A smoothing algorithm provides stable accelerometer readings. Further, a small center-mounted vibrator can distribute stimuli all over the bar. The prototype can be used as a research platform to study teaching different kinds of feedback for a variety of kiting skills (like "Let go of the bar!") and even multi-kite coordination (like kiting in formation).

Design Exploration

The current prototype is a result of several iterations, where different technologies for feedback were considered. During the process the design has been evaluated by 5 instructors, 2 kiteboarding equipment designers from the CrazyFly kiteboarding company and various kiteboarders including the authors of this paper. The process has been centered around four factors: placement, number of actuators, intensity as identified in [START_REF] Gallace | Numerosity judgments for tactile stimuli distributed over the body surface[END_REF] and mapping of the system logic to the actuation events. Regarding intensity, two different types of vibrotactile actuators have been considered, the ERM type and the Linear Resonant Actuator (LRA) type. The ERM feedback is often bigger and more intense than the smaller, more precise and faster LRA feedback. Figure 6 illustrates different options regarding the placement and number of vibrotactile actuators. Adding small LRA vibrators inside the control bar (Figure 6A) will cause the stimuli to resonate all over the bar, because of tight contact to the material. This challenge is also faced when mounting LRA's outside the bar (Figure 6B). Isolating the actuators from the bar is possible with an insulating material such as foam (Figure 6B), but when applying pressure, contact will again be present. This is problematic if trying to create an animated stimulus for example from the middle of the bar to the ends of the bar. The overall result of adding more actuators inside or outside the bar is that one can not tell the difference in where the stimulus is active. It reflects the phenomenon of "apparent location", which is when two separated vibrations are active at the same time on the skin, they can be perceived as one single vibration from somewhere in between the two [START_REF] Gallace | Numerosity judgments for tactile stimuli distributed over the body surface[END_REF]. That suggests an approach of choosing simple rather than complex and high positional fidelity when it comes to communicating tactile stimuli through the control bar. Mounting vibrotactile actuators directly on the lines (Figure 6C) results in isolation from the bar. Mounting powerful large-mass ERM actuators at each end of the bar turned out to be very effective (Figure 6D). With this setup it is easy to discern which side is vibrating, therefore this setup is part of the current design. Initial studies explored the options of mapping. Evaluations with instructors, kiteboarding equipment designers, and others showed that pulling in the side that is vibrating seemed the most intuitive. This is also similar to the metaphor of "tapping on one's shoulder" [START_REF] Prasad | Haptigo: A navigational "tap on the shoulder[END_REF] or steering a motorcycle to the same side as the active tactile stimuli [START_REF] Prasad | Haptimoto: turn-by-turn haptic route guidance interface for motorcyclists[END_REF]. Some use the opposite analogy when steering a car, but here the driver must steer away from the cue felt [START_REF] Sucu | Haptic Interface for Non-visual Steering[END_REF]. In the case of driving, that approach seems optimal, because the driver would steer away from the road barrier.

Evaluation

The evaluation of the system is aimed at performance in kite control. In order to examine this, two study sessions were conducted. To avoid the learning effect, each session was conducted with a new set of 10 participants. In each session participants performed a kite control task involving three conditions providing different modes of guidance including tactile feedback only (tactile only), voice feedback only (voice only), and voice commands with tactile feedback (tactile + voice). The order presented to the subjects was balanced and randomized. In each of these the participant should steer the kite to 7 different positions. The sessions took place at the beach in order to provide a context that is as close to the real world scenario as possible. From the results of session I, opportunities for improvements were identified and implemented in session II and evaluated with a different set of participants.

Participants and Task

As mentioned, 10 participants took part in each session including 3 females and 17 males between the ages of 19 and 41 with an average age of 25.9 years. This included 3 novices and 17 proficient kiteboarders. Participants were briefed on the kite control task and were asked to fill out a consent form and a questionnaire before and after the study session. The participants completed a kite control task in each of the three conditions. The task is based on a typical kite control exercise. Participants must orient the control bar to the 12 o'clock position in order to begin the session. The participant is then guided through a series of 7 target positions mapped to positions on the clock face. Upon reaching each target position, one is required to hold the position for 5 seconds, after which they are guided to the next position in the task sequence. This sequence was provided to the participants, always beginning and ending with the 12 o'clock position. Half of the participants proceeded through the positions of 2, 10, 1, 12, 11, 2, and the other half proceeded in reverse order. This was balanced and randomized.

Study Session Protocol and Measures

The participants were asked to answer a demographic questionnaire. Participants were then asked to hold and orient the control bar to explore the tactile sensations in order to understand the mapping between the position of the bar and the vibrotactile sensations. When the participant was satisfied with their control abilities and were able to maintain an indicated position, the specific tasks for the study were introduced. After completing the tasks in all conditions, a second questionnaire about the experience was given. The participant performance and response to the tasks was measured through logged system events and self-reported feedback. Performance data was logged by the test control system running on a PC connected to the control bar microcontroller. The log includes events for when the target range is achieved, number of times the position deviates from the target range (drift), and when the position has been held steady within the target range for 5 seconds. During the study sessions the wind speed was tracked using an anemometer to ensure similar conditions across participants. Both before and after the session, participants were asked to answer forced selection questions and provide additional open ended feedback. Q1-2: Preferences. In order to explore which condition the participant preferred the most and least, they were asked to indicate by circling the words, "tactile only", "voice+tactile", or "voice only". Participants were permitted to provide supporting details about their choice if they desired. Q3: Reflection on Performance. In order to explore the self-reported belief about their performance, participants were asked to indicate in which of the three conditions they believed their performance was best. Again, they could choose tactile only, voice+tactile, or voice only and provide additional supporting details if desired. Q4: Improvements and Suggestions. In order to better understand the impressions of the system, the participants were asked to provide suggestions for improvements.

Session I: Controlling a Kite

Both sessions were conducted at the beach with a 3m 2 trainer kite on land with average windspeed of 8m/sec. The settings of the system in session I are illustrated in Figure 7. Here the clock face is shown, with 12 o'clock as an example target position. There are 4 layers on the figure including the clock positions, the vibration events, logged events, and angle in degrees. In the tactile only and tactile + voice conditions the tactile feedback was provided as indicated "vibration events". If the kite is steered away from the example target of 12 o'clock to 2 o'clock, full vibration will be active in the left side (L), and when passing 1 o'clock it transforms to weak vibration. When within 18° of the target, vibration stops. When giving voice commands in the tactile + voice and voice only conditions the logging remains the same. The facilitator calls out the position, e.g. "move the kite to 2 o'clock", then uses the voice commands equivalent to the vibration signals (strong/weak) to give guidance -"more left/right", "a little more left/right" and "hold it". The system alerts the facilitator when, and which command to verbalize.

Results of Session I

While all of the experienced kiteboarders completed the study session successfully, 3 novice participants were not able to complete the kite control task and their partial results have been withheld. Insights gathered from their behavior revealed a mismatch in the mental model for how to control a kite which we discuss in more detail later in the paper. While participants were able to quickly complete the control task in all conditions, the tactile only condition resulted in longer average times to achieve a target as shown in Figure 9 and moved outside the target range more as shown in Figure 10. The results are summarized in Table 1 and explained in more detail in the coming sections.

Self-reported Feedback from Session I. Q1-2 explored the participant preferences for the three conditions. Three participants preferred tactile only, while two preferred it the least. Two participants preferred voice + tactile and three indicated this as least preferred. Results from Q3 revealed that four participants believed they did best in the voice only condition. Two participants believed they did best in voice + tactile.

A review of the open-ended feedback suggests various motivations for their answers. Those who least preferred voice + tactile said that they only relied on one modality in the condition, as participant 3, 4 and 5 stated:

P3: "Too much information." P4: "Not using the vibrations because I concentrate on the voice instructions." P5: "It was a bit confusing to both be listening and feeling simultaneously." Fig. 7. Session I system settings, with 12 o'clock as example target. Vibration layer shows when full, weak and no vibration is present. Logging layer shows when inside/outside target range is logged (B), and where the 5 seconds countdown becomes active (A).

Session II: Vibrotactile refinements

From the results of session I, we recognized that participants responded differently to voice and tactile feedback not only in the amount of time to complete the tasks, but their steering behavior varied noticeably. When tactile cues alone were provided, participants hovered near the target range or oscillated between the boundaries of the range, yet when tactile was combined with voice and when guided by voice alone, participants did not engage in these wandering behaviors. We discuss this in more detail in the discussion section. Feedback suggested that additional guidance was needed. Therefore, we developed a tighter range of guidance signals as shown in Figure 8B and a vibrotactile confirmation cue to alert when the target position was reached, yet we maintained the previous target range. This was intended to guide the participant closer to the center of the target. The confirmation cue was delivered by the middle vibrotactile actuator as indicated in Figure 5D & 8C. The enhancements to the new settings were evaluated with new participants at the beach, following the same study protocol as in study session I.

Fig. 8. Session II settings, with 12 o'clock as example target. Vibration layer shows when full, weak, and confirmation cue is given. Logging layer shows when inside/outside target range is logged (B), and where the 5 seconds countdown becomes active (A). (C) Middle actuator delivers confirmation cue.

Results of Session II

Analysis of variance (ANOVA) within subjects did not reveal differences to be significant. However independent samples t-test between session I and session II, suggest that the improvements made to the prototype resulted in improvements to the performance and these differences were not due to chance. Comparing sessions I & II, there were improvements across all conditions in session II. This includes the time to reach a target position in the tactile only condition for session I (M=17.86sec, SD=5.68sec) and session II (M=12.57sec, SD=2.57sec), t(15)=2.618, p=0.019. For the tactile + voice condition there is significant difference between session I (M=12.33sec, SD=1.57sec) and the improved settings in session II (M=10.36sec, SD=1.07sec), t(15)=3.084, p=0.008. Differences with "voice only" cues were not found to be significant p=0.555. With "tactile only" cues, kiters had statistically fewer average drifts from target (M=1.1, SD=0.69) with refined tactile cues compared to original thresholds (M=2.67, SD=1.63), t(15)=2.755, p=0.015. With "tactile + voice" cues, kiters had statistically fewer average drifts from target (M=0.56, SD=0.31) with refined tactile cues compared to original thresholds (M=0.94, SD=0.28), t(15)=2.572, p=0.021. Differences with "voice only" cues were not found to be significant p=0.974. These results suggest that voice can be more effective than haptic feedback for planning tasks when it provides a model (such as "move the kite to 2 o'clock") for the user to test their actions against, and that the refinements to feedback with confirmation of target acquisition can lead to better performance. Self-reported Feedback from Session II. In session II the majority (7 out of 10) preferred the condition with tactile and voice combined, and none preferred voice feedback alone. Those who prefer tactile + voice, mention they like that voice gives a precise idea of where the target is, while the tactile feedback supports with precise information for final adjustments. The remaining 3 out of 10 preferred the tactile only condition claiming to notice a sense of control, quick response time and precise feedback.

Session I Session II

The least preferred condition (7 out of 10) was voice only. The open-ended feedback indicated that the 2 out of 10 participants that least preferred the tactile only condition, claimed they needed guidance on what position they were going to, and felt like they were exploring to find the right position. The 1 out of 10 that preferred tactile + voice least, indicated that they did not like the redundancy in the feedback and 7 out of 10 expressed claims that the voice feedback was too slow and imprecise. Every participant reported they did the best in the condition they preferred the most. The majority (7 out of 10) preferred tactile + voice, none preferred the session with voice only. In contrast to the self-reported feedback in session II, the logged data shows that there were no statistically significant differences between the average time it took the participant to achieve the desired target in the tactile + voice condition compared to the tactile only condition. Surprisingly, in session I, the open-ended feedback indicated that participants did not like the additional feedback in the tactile + voice condition, however, it was the most preferred condition in session II. Various participants noted the confirmation signal from the center of the bar helped them understand when they achieved the target.

Discussion

Both sessions indicated that participants were able to perceive and understand the tactile cues. Surprisingly the results indicate that participants claim to prefer tactile combined with voice over voice alone, while objectively the performance is better with voice alone. Feedback from participants suggests that they appreciate the real time feedback and confirmation of achieving the target position. The negative sentiment for voice might be related to additional perceived effort in decoding the utterance, translating that into guidance, and then taking action. Perhaps voice activates social rules that compete with the intended experience. This deserves exploration in future studies.

Even though results have been improved in session II, our observations suggests that in extreme sportsand likely in other extreme contextsusers may adopt a mental model that is poorly suited to facilitating their success in the activity, which can be difficult to change. We provide further explanation of these findings in this section and discuss the limitations of our work.

Improvements to Tactile Communication

Voice feedback resulted in better performance, compared to tactile cues alone, as participants quickly adopt the semantic map and move to the target position, and upon reaching it, they were told to stop. This is challenging for tactile feedback, as it is not well suited in communicating the angle in clock positions. Instead, simple guidance (left/right) has been provided, which is not always enough as some participants were stopping right at the acceptable boundary, or oscillating between the 2 edges of the target range. The reason for this was identified as 1) a missing confirmation, and 2) guidance that stops too soon. By adding a tactile confirmation cue and by moving the weak vibration inside the acceptable target range, guiding the participants away from the edge (Figure 8), improved the results. Even tough tactile feedback can communicate basic guidance, mental models of novices for how a kite is controlled can be mismatched, making guidance difficult.

Mental Models

In session I, 2 people were not able to complete the tasks. The main obstacle was typical for beginnersthey failed to adopt an effective mental model for how the kite responds to the control bar movements, leading to inability to maintain a stable position. In order to control the position of the kite, the rider shortens the line connected to one side of the kite in the desired direction of travel. Experienced kiters adopt a habit of holding the control bar parallel to the leading edge of the kite, so that pulling on one side of the bar maps to the direction the kite will move. Skilled riders on the water usually follow the same practice adjusting the orientation of the bar while riding. It is possible to control the kite without holding the bar like this, however, it becomes much more difficult to control and predict movements.

7.3

Limitations

Our work provides some initial steps towards developing technologies to support participants in kiteboarding, however, there are possible limitations to this work which are worthwhile to discuss. In terms of the prototype design and evaluation, there may be concerns about the nature of the evaluation task and its relation to the real world experience of kiteboarding. While the choice of logged data for the evaluations has been useful in highlighting the differences in response to voice and tactile feedbackwe would like to expand to more measures including tension of the lines, position of the body, orientation of the board, and bar to identify bad habits.

Conclusion and Future Work

Designers have explored technologies to support physical activities, however, there is less research focused on technologies supporting communication in physically and mentally demanding contexts such as extreme sports. We explore kiteboarding as an experimental platform to find ways in which technologies can support communication needs. Kiteboarding is a complex dynamic activity with intense demands of control and diminished opportunities for communication. We developed a kite control bar with embedded sensors and actuators to communicate instructions through voice or tactile cues to explore how technology can facilitate communication for control guidance. Evaluations suggest that familiar voice communication is effective, yet may negatively impact the experience. We show that tactile cues can also be effective at changing behavior. However, tactile feedback was not as flexible as voice for presenting a mental model. Our work demonstrates the value of voice commands providing quick, high level semantic models. We found that tactile cues can provide effective feedback that might be preferred in contexts that place extreme demands on the user. Evaluations reveal how small changes in tactile feedback can yield significant improvements. This work is a celebration of the capacities of human performance and signals opportunities for computer controlled feedback across modalities. There is a need for continued exploration of cyber-physical systems to examine signals for appropriateness and capacity to support interactions. This paper calls for building an understanding of how to explore scenarios and contexts using multimodal feedback systems. We encourage the continued investigation into exploring languages of various modalities and interactions among them. This seems to be an area ripe for exploration in the challenge of designing for extreme sports or other contexts in which people are pushed to their limits.

Aside from the existing goals of kiteboarders, it would be interesting to explore other forms of play that can be supported through the use of digital augmentations along the lines of work involving augmentations to expand the experience of a game platform [START_REF] Ishii | PingPongPlus: Design of an Athletic-tangible Interface for Computer-supported Cooperative Play[END_REF] and new forms of social expression through an exertion interfaces approach [START_REF] Pijnappel | 4 Design Themes for Skateboarding[END_REF], perhaps exploring opportunities for social interaction among participants and even spectators [START_REF] Ludvigsen | Designing Technology for Active Spectator Experiences at Sporting Events[END_REF].

Fig. 3 .

 3 Fig. 3. The wind window that shows where the kite can fly.

Fig. 4 .

 4 Fig. 4. Design vision: A) Instructor and student have the control bars in the same orientation thus no vibrotactile signals are sent. B) When the instructor moves the control bar to a new position, the student control bar vibrates on the side of the bar indicating direction to move. C) The student matches the instructed position and the vibrotactile signals cease.

Fig. 5 .

 5 Fig. 5. (Left) Elements of prototype: A) harness, B) microcontroller enclosure, C) left vibrotactile actuator, D) accelerometer and center vibrotactile actuator, E) right vibrotactile actuator, G) safety leash, F) signal wire. (Right) Control bar prototype in use during study session.

Fig. 6 .

 6 Fig. 6. Different stimuli explored in number and placement. A) LRA actuators inside the bar. B) LRA actuators outside the bar, both isolated with fabric and direct mount. C) Vibrotactile actuators on the lines, both with ERM and LRA type. D) ERM actuators on bar ends

Fig. 9 .

 9 Fig. 9. Average time in seconds to reach each target session I (left), II (right).

Fig. 10 .

 10 Fig. 10. Average number of times participant moved the bar position outside of each target range in session I (left), II (right).

Table 1 .

 1 Summary of results from session I & II.

	Time to target (tactile only) (sec)	17.86	12.57
	Time to target (voice + tactile) (sec)	12.33	10.36
	Time to target (voice) (sec)	12.23	11.68
	Drift events (tactile only)	2.67	1.10
	Drift events (voice + tactile)	0.94	0.56
	Drift events (voice only)	1.06	1.07
	Preferred most	tactile only tactile + voice
	Preferred least	voice only tactile only


Jutta Fortmann

Janko Timmermann

Bengt Lüers

Marius Wybrands

Wilko Heuten

Susanne Boll

LightWatch: A wearable light display for personal exertion

Keywords: wristwatch, digital jewellery, LED, pressure sensitive, heart rate

Wearable devices need to seamlessly integrate into everyday life and meet a user's aesthetic needs. In this paper, we present LightWatch, a wearable light display integrated into a common analogue wristwatch without interfering with the functionality of the watch itself. Input is enabled through a pressuresensitive bezel mounted beneath the light display. LightWatch shall raise body awareness by enabling sensor-based measurement, adjustment and display of a user's personal exertion level. We see LightWatch as a promising approach for an unobtrusive everyday companion that can be used for various applications.

Introduction and Background

In the last years, wearable devices have been widely disseminated. A body-worn device needs to integrate seamlessly into everyday life and to meet a user's aesthetic needs. Thus, the latest trend on the wearable market is towards good-looking solutions, often referred to as digital jewellery.

In this work, we present a wearable light display for personal exertion. Our aim was to develop a wearable system that is integrated into a common wristwatch and seamlessly integrates into everyday life. We expanded an off-the-shelf analogue wristwatch by a pressure-sensitive light display and a heart rate sensor. LightWatch serves as a proof of concept that the integration of a pressure-sensitive light display into a common analogue watch is possible without interfering with the functionality of the watch itself. We see LightWatch as a promising approach for a useful everyday companion that meets a user's aesthetic needs and can be used for various use cases. One scenario is the raise of body awareness. We implemented this by enabling the user to measure her or his heart rate and to adjust a measured value whenever he or she thinks it does not match his or her perception. This way, a user is trained to assess his or her perceived exertion level.

Some research has investigated light displays that present information on wrist-worn digital jewellery, such as watches [START_REF] Xu | Shimmering Smartwatches: Exploring the Smartwatch Design Space[END_REF] or bracelets [START_REF] Fortmann | WaterJewel: design and evaluation of a bracelet to promote a better drinking behaviour[END_REF]. Besides, different input meth-ods have been researched. These were e.g. mechanical pan, twist, tilt and click on the bezel [START_REF] Xiao | Expanding the input expressivity of smartwatches with mechanical pan, twist, tilt and click[END_REF], and touch gestures performed on the wristband [START_REF] Simon | Watchit: simple gestures and eyes-free interaction for wristwatches and bracelets[END_REF]. In contrast to previous work, we integrate a point light display into a common analogue wristwatch without interfering with the functionality of the watch itself. Further, our light display can be intuitively operated via pressure that a user applies directly to the surface of the light display.

LightWatch

The idea of LightWatch is to present information about a user's exertion level on a common wristwatch. It was developed in an iterative design process. During the process, we repeatedly tested the hardware elements in our lab, both, separately, and when integrated into the watch. We tested technical functionality and usability. In the following, we describe the conceptual design and the implementation of the final prototype of LightWatch.

Conceptual Design

The requirements on the system are, that, it must provide the function to measure, adjust, and display a user's exertion level. It must be integrated into a common wristwatch, everyday suitable, and easily usable while being worn. The conceptual design of Light Watch is as in the following. A user can measure his or her exertion level with a heart rate sensor. The exertion level is displayed by circular arranged LEDs on the bezel of the watch. The lowest exertion level is indicated by the first LED on the 12 o`clock position. The mapping of LEDs to exertion levels goes clockwise from low to high. The higher the exertion level, the more LEDs are illuminated clockwise.

A user can adjust the measured value by pressing the LED that represents his or her perceived value.

In the following, we describe the interaction concept. After switched on, the watch is in idle state. The user can open the menu by pressing the bottom area of the LED ring, i.e. about the six o'clock position, for at least 2 seconds. Three different areas of 4 LEDs each light up in red, green, or blue (see Fig. 1). Within the next 7 seconds, the user can press one of the three areas to choose between the options measure heart rate (red), show latest value (green), or quit menu (blue). The system confirms a user input by switching off the LEDs in the not-chosen areas. After a user has chosen the red area, he or she can place a finger onto the heart rate sensor. For each measured pulse beat, an LED lights up red. If 12 pulse beats have been measured, the calculated exertion level is displayed in that the according LEDs light up white. Within the next 4 seconds, the user can adjust the value if he or she perceived the exertion differently. If he or she does not react, the value will be saved after 4 seconds. To adjust the value, the user presses the according LED. The input is confirmed in that the LEDs representing the entered value light up white. After 2 seconds the input is saved. If the user chooses the green area, the latest value that was captured will be displayed through white illuminated LEDs. Whenever a user does not react for 7 seconds after opening the menu, the watch will return to idle state. The blue option offers a quick exit in case the user does not want to wait for 7 seconds.

Implementation

For the implementation of LightWatch, we used an off-the-shelf analogue plastic wristwatch. Following, we describe the design of LightWatch from top to bottom. On the top of the watch there is a cover made from a 6mm thick pane of acrylic glass that we cut with a laser cutter. Indentations for the underlying LEDs and circuit board were laser etched and the glass was cut to round shape. It protects the underlying delicate electronics from forces of the user when he or she makes inputs by pressing the surface of the watch. Beneath the cover glass we mounted an Adafruit NeoPixel 12 RGB LED ring. It carries 12 serially addressable RGB LEDs on a common circuit board. When the LEDs are illuminated, the etched glass atop the LEDs diffuses their light. A ring of 2mm thin foam rubber flexibly connects the LED ring to the underlying HotPot rotary potentiometer. It encodes the position of pressure that a user puts on the glass to an analogue resistance.

The rotary potentiometer is taped down to a ring of pressboard by double-sided adhesive tape. The pressboard was laser cut and glued to the watch case. The pressboard ring provides a stable base to the rotary potentiometer and transfers applied forces to the watch case. The watch case and watchstrap were modified from a common analogue plastic wristwatch. We drilled and grinded holes to fit a connector and to route cables to the outside. The watchstrap carries a 1000mAh LiPo battery and a heart rate sensor, the Sparkfun Pulse Sensor Amped. In lab tests we found that the heart rate sensor does not provide reliable measurements on the wrist, but on fingers. Therefore, we mounted the sensor on the watchstrap. The heart rate sensor is attached to the lower watchstrap by a cable tie, and faces upwards. It measures the user's heart rate when a finger is applied (see Fig. 1). The watch case houses the original clockwork and an ATtiny85V-10SU microcontroller. We soldered all connections directly or via stranded wire to the microcontroller. The microcontroller processes data provided by all sensors and drives the LED ring. Embedded into the side of the watch case is a female pin strip with 0.1 inch (2.54 mm) pitch. It leads out the connections needed for in system programming (ISP) the microcontroller. Via the pin strip the watch can be programmed and the collected data can be downloaded to a computer.

Discussion and Conclusion

In this paper, we presented LightWatch, a light information display for personal exertion that is integrated into a common analogue wristwatch. Our prototype serves as a proof of concept that the integration of a pressure-sensitive light display into a common wristwatch is possible without interfering with the functionality of the analogue watch itself. The major advantage is that a user can keep using his or her preferred watch, that is enhanced by further digital functionality. Wearing another device like a technically looking smart watch that does not meet the user's fashionable requirements is not needed. We think that a regular wristwatch that is expanded in a way like LightWatch is a promising approach for a useful everyday companion that can be used for various applications. These could e.g. be a display for physical activity, fluid intake, or medicine, as well as a reminder for dates.

The LightWatch prototype we presented in this paper is limited in that it is in an early development status. In the next step, we want to conduct user studies to investigate the user experience and practicality of LightWatch in real life. Therefore, we need to technically refine the prototype, i.e. to thin it, to hide all cables and the battery, and to improve its visual appeal.

Fig. 1 .

 1 Fig. 1. A user wears LightWatch: Light menu is opened and heart rate sensor is enabled.