175 research outputs found
Blending the Material and Digital World for Hybrid Interfaces
The development of digital technologies in the 21st century is progressing continuously and new device classes such as tablets, smartphones or smartwatches are finding their way into our everyday lives. However, this development also poses problems, as these prevailing touch and gestural interfaces often lack tangibility, take little account of haptic qualities and therefore require full attention from their users. Compared to traditional tools and analog interfaces, the human skills to experience and manipulate material in its natural environment and context remain unexploited. To combine the best of both, a key question is how it is possible to blend the material world and digital world to design and realize novel hybrid interfaces in a meaningful way. Research on Tangible User Interfaces (TUIs) investigates the coupling between physical objects and virtual data. In contrast, hybrid interfaces, which specifically aim to digitally enrich analog artifacts of everyday work, have not yet been sufficiently researched and systematically discussed.
Therefore, this doctoral thesis rethinks how user interfaces can provide useful digital functionality while maintaining their physical properties and familiar patterns of use in the real world. However, the development of such hybrid interfaces raises overarching research questions about the design: Which kind of physical interfaces are worth exploring? What type of digital enhancement will improve existing interfaces? How can hybrid interfaces retain their physical properties while enabling new digital functions? What are suitable methods to explore different design? And how to support technology-enthusiast users in prototyping?
For a systematic investigation, the thesis builds on a design-oriented, exploratory and iterative development process using digital fabrication methods and novel materials. As a main contribution, four specific research projects are presented that apply and discuss different visual and interactive augmentation principles along real-world applications. The applications range from digitally-enhanced paper, interactive cords over visual watch strap extensions to novel prototyping tools for smart garments. While almost all of them integrate visual feedback and haptic input, none of them are built on rigid, rectangular pixel screens or use standard input modalities, as they all aim to reveal new design approaches. The dissertation shows how valuable it can be to rethink familiar, analog applications while thoughtfully extending them digitally. Finally, this thesis’ extensive work of engineering versatile research platforms is accompanied by overarching conceptual work, user evaluations and technical experiments, as well as literature reviews.Die Durchdringung digitaler Technologien im 21. Jahrhundert schreitet stetig voran und neue Geräteklassen wie Tablets, Smartphones oder Smartwatches erobern unseren Alltag. Diese Entwicklung birgt aber auch Probleme, denn die vorherrschenden berührungsempfindlichen Oberflächen berücksichtigen kaum haptische Qualitäten und erfordern daher die volle Aufmerksamkeit ihrer Nutzer:innen. Im Vergleich zu traditionellen Werkzeugen und analogen Schnittstellen bleiben die menschlichen Fähigkeiten ungenutzt, die Umwelt mit allen Sinnen zu begreifen und wahrzunehmen. Um das Beste aus beiden Welten zu vereinen, stellt sich daher die Frage, wie neuartige hybride Schnittstellen sinnvoll gestaltet und realisiert werden können, um die materielle und die digitale Welt zu verschmelzen. In der Forschung zu Tangible User Interfaces (TUIs) wird die Verbindung zwischen physischen Objekten und virtuellen Daten untersucht. Noch nicht ausreichend erforscht wurden hingegen hybride Schnittstellen, die speziell darauf abzielen, physische Gegenstände des Alltags digital zu erweitern und anhand geeigneter Designparameter und Entwurfsräume systematisch zu untersuchen.
In dieser Dissertation wird daher untersucht, wie Materialität und Digitalität nahtlos ineinander übergehen können. Es soll erforscht werden, wie künftige Benutzungsschnittstellen nützliche digitale Funktionen bereitstellen können, ohne ihre physischen Eigenschaften und vertrauten Nutzungsmuster in der realen Welt zu verlieren. Die Entwicklung solcher hybriden Ansätze wirft jedoch übergreifende Forschungsfragen zum Design auf: Welche Arten von physischen Schnittstellen sind es wert, betrachtet zu werden? Welche Art von digitaler Erweiterung verbessert das Bestehende? Wie können hybride Konzepte ihre physischen Eigenschaften beibehalten und gleichzeitig neue digitale Funktionen ermöglichen? Was sind geeignete Methoden, um verschiedene Designs zu erforschen? Wie kann man Technologiebegeisterte bei der Erstellung von Prototypen unterstützen?
Für eine systematische Untersuchung stützt sich die Arbeit auf einen designorientierten, explorativen und iterativen Entwicklungsprozess unter Verwendung digitaler Fabrikationsmethoden und neuartiger Materialien. Im Hauptteil werden vier Forschungsprojekte vorgestellt, die verschiedene visuelle und interaktive Prinzipien entlang realer Anwendungen diskutieren. Die Szenarien reichen von digital angereichertem Papier, interaktiven Kordeln über visuelle Erweiterungen von Uhrarmbändern bis hin zu neuartigen Prototyping-Tools für intelligente Kleidungsstücke. Um neue Designansätze aufzuzeigen, integrieren nahezu alle visuelles Feedback und haptische Eingaben, um Alternativen zu Standard-Eingabemodalitäten auf starren Pixelbildschirmen zu schaffen. Die Dissertation hat gezeigt, wie wertvoll es sein kann, bekannte, analoge Anwendungen zu überdenken und sie dabei gleichzeitig mit Bedacht digital zu erweitern. Dabei umfasst die vorliegende Arbeit sowohl realisierte technische Forschungsplattformen als auch übergreifende konzeptionelle Arbeiten, Nutzerstudien und technische Experimente sowie die Analyse existierender Forschungsarbeiten
WearPut : Designing Dexterous Wearable Input based on the Characteristics of Human Finger Motions
Department of Biomedical Engineering (Human Factors Engineering)Powerful microchips for computing and networking allow a wide range of wearable devices to be miniaturized with high fidelity and availability. In particular, the commercially successful smartwatches placed on the wrist drive market growth by sharing the role of smartphones and health management. The emerging Head Mounted Displays (HMDs) for Augmented Reality (AR) and Virtual Reality (VR) also impact various application areas in video games, education, simulation, and productivity tools. However, these powerful wearables have challenges in interaction with the inevitably limited space for input and output due to the specialized form factors for fitting the body parts. To complement the constrained interaction experience, many wearable devices still rely on other large form factor devices (e.g., smartphones or hand-held controllers). Despite their usefulness, the additional devices for interaction can constrain the viability of wearable devices in many usage scenarios by tethering users' hands to the physical devices. This thesis argues that developing novel Human-Computer interaction techniques for the specialized wearable form factors is vital for wearables to be reliable standalone products.
This thesis seeks to address the issue of constrained interaction experience with novel interaction techniques by exploring finger motions during input for the specialized form factors of wearable devices. The several characteristics of the finger input motions are promising to enable increases in the expressiveness of input on the physically limited input space of wearable devices. First, the input techniques with fingers are prevalent on many large form factor devices (e.g., touchscreen or physical keyboard) due to fast and accurate performance and high familiarity. Second, many commercial wearable products provide built-in sensors (e.g., touchscreen or hand tracking system) to detect finger motions. This enables the implementation of novel interaction systems without any additional sensors or devices. Third, the specialized form factors of wearable devices can create unique input contexts while the fingers approach their locations, shapes, and components. Finally, the dexterity of fingers with a distinctive appearance, high degrees of freedom, and high sensitivity of joint angle perception have the potential to widen the range of input available with various movement features on the surface and in the air. Accordingly, the general claim of this thesis is that understanding how users move their fingers during input will enable increases in the expressiveness of the interaction techniques we can create for resource-limited wearable devices.
This thesis demonstrates the general claim by providing evidence in various wearable scenarios with smartwatches and HMDs. First, this thesis explored the comfort range of static and dynamic touch input with angles on the touchscreen of smartwatches. The results showed the specific comfort ranges on variations in fingers, finger regions, and poses due to the unique input context that the touching hand approaches a small and fixed touchscreen with a limited range of angles. Then, finger region-aware systems that recognize the flat and side of the finger were constructed based on the contact areas on the touchscreen to enhance the expressiveness of angle-based touch input. In the second scenario, this thesis revealed distinctive touch profiles of different fingers caused by the unique input context for the touchscreen of smartwatches. The results led to the implementation of finger identification systems for distinguishing two or three fingers. Two virtual keyboards with 12 and 16 keys showed the feasibility of touch-based finger identification that enables increases in the expressiveness of touch input techniques. In addition, this thesis supports the general claim with a range of wearable scenarios by exploring the finger input motions in the air. In the third scenario, this thesis investigated the motions of in-air finger stroking during unconstrained in-air typing for HMDs. The results of the observation study revealed details of in-air finger motions during fast sequential input, such as strategies, kinematics, correlated movements, inter-fingerstroke relationship, and individual in-air keys. The in-depth analysis led to a practical guideline for developing robust in-air typing systems with finger stroking. Lastly, this thesis examined the viable locations of in-air thumb touch input to the virtual targets above the palm. It was confirmed that fast and accurate sequential thumb touch can be achieved at a total of 8 key locations with the built-in hand tracking system in a commercial HMD. Final typing studies with a novel in-air thumb typing system verified increases in the expressiveness of virtual target selection on HMDs.
This thesis argues that the objective and subjective results and novel interaction techniques in various wearable scenarios support the general claim that understanding how users move their fingers during input will enable increases in the expressiveness of the interaction techniques we can create for resource-limited wearable devices. Finally, this thesis concludes with thesis contributions, design considerations, and the scope of future research works, for future researchers and developers to implement robust finger-based interaction systems on various types of wearable devices.ope
TouchEditor: Interaction design and evaluation of a flexible touchpad for text editing of head-mounted displays in speech-unfriendly environments
A text editing solution that adapts to speech-unfriendly (inconvenient to speak or difficult to recognize speech) environments is essential for head-mounted displays (HMDs) to work universally. For existing schemes, e.g., touch bar, virtual keyboard and physical keyboard, there are shortcomings such as insufficient speed, uncomfortable experience or restrictions on user location and posture. To mitigate these restrictions, we propose TouchEditor, a novel text editing system for HMDs based on a flexible piezoresistive film sensor, supporting cursor positioning, text selection, text retyping and editing commands (i.e., Copy, Paste, Delete, etc.). Through literature overview and heuristic study, we design a pressure-controlled menu and a shortcut gesture set for entering editing commands, and propose an area-and-pressure-based method for cursor positioning and text selection that skillfully maps gestures in different areas and with different strengths to cursor movements with different directions and granularities. The evaluation results show that TouchEditor i) adapts to various contents and scenes well with a stable correction speed of 0.075 corrections per second; ii) achieves 95.4% gesture recognition accuracy; iii) reaches a considerable level with a mobile phone in text selection tasks. The comparison results with the speech-dependent EYEditor and the built-in touch bar further prove the flexibility and robustness of TouchEditor in speech-unfriendly environments
Sensitive and Makeable Computational Materials for the Creation of Smart Everyday Objects
The vision of computational materials is to create smart everyday objects using the materi- als that have sensing and computational capabilities embedded into them. However, today’s development of computational materials is limited because its interfaces (i.e. sensors) are unable to support wide ranges of human interactions , and withstand the fabrication meth- ods of everyday objects (e.g. cutting and assembling). These barriers hinder citizens from creating smart every day objects using computational materials on a large scale.
To overcome the barriers, this dissertation presents the approaches to develop compu- tational materials to be 1) sensitive to a wide variety of user interactions, including explicit interactions (e.g. user inputs) and implicit interactions (e.g. user contexts), and 2) makeable against a wide range of fabrication operations, such cutting and assembling. I exemplify the approaches through five research projects on two common materials, textile and wood. For each project, I explore how a material interface can be made to sense user inputs or activities, and how it can be optimized to balance sensitivity and fabrication complexity. I discuss the sensing algorithms and machine learning model to interpret the sensor data as high-level abstraction and interaction. I show the practical applications of developed computational materials. I demonstrate the evaluation study to validate their performance and robustness.
In the end of this dissertation, I summarize the contributions of my thesis and discuss future directions for the vision of computational materials
Parametric active learning techniques for 3D hand pose estimation
Active learning (AL) has recently gained popularity for deep learning (DL) models due to efficient and informative sampling, especially when the models
require large-scale datasets. The DL models designed for 3D-HPE demand
accurate and diverse large-scale datasets that are time-consuming, costly and
require experts. This thesis aims to explore AL primarily for the 3D hand
pose estimation (3D-HPE) task for the first time.
The thesis delves directly into an AL methodology customised for 3D-HPE learners to address this. Because predominantly the learners are regression-based algorithms, a Bayesian approximation of a DL architecture is presented to model uncertainties. This approximation generates data and model-
dependent uncertainties that are further combined with the data representativeness AL function, CoreSet, for sampling. Despite being the first work, it
creates informative samples and minimal joint errors with less training data
on three well-known depth datasets.
The second AL algorithm continues to improve the selection following a
new trend of parametric samplers. Precisely, this is proceeded task-agnostic with a Graph Convolutional Network (GCN) to offer higher order of representations between labelled and unlabelled data. The newly selected unlabelled
images are ranked based on uncertainty or GCN feature distribution.
Another novel sampler extends this idea, and tackles encountered AL issues,
like cold-start and distribution shift, by training in a self-supervised way with
contrastive learning. It shows leveraging the visual concepts from labelled
and unlabelled images while attaining state-of-the-art results.
The last part of the thesis brings prior AL insights and achievements in a
unified parametric-based sampler proposal for the multi-modal 3D-HPE task.
This sampler trains multi-variational auto-encoders to align the modalities
and provide better selection representation. Several query functions are
studied to open a new direction in deep AL sampling.Open Acces
Machine learning approaches to video activity recognition: from computer vision to signal processing
244 p.La investigación presentada se centra en técnicas de clasificación para dos tareas diferentes, aunque relacionadas, de tal forma que la segunda puede ser considerada parte de la primera: el reconocimiento de acciones humanas en vídeos y el reconocimiento de lengua de signos.En la primera parte, la hipótesis de partida es que la transformación de las señales de un vídeo mediante el algoritmo de Patrones Espaciales Comunes (CSP por sus siglas en inglés, comúnmente utilizado en sistemas de Electroencefalografía) puede dar lugar a nuevas características que serán útiles para la posterior clasificación de los vídeos mediante clasificadores supervisados. Se han realizado diferentes experimentos en varias bases de datos, incluyendo una creada durante esta investigación desde el punto de vista de un robot humanoide, con la intención de implementar el sistema de reconocimiento desarrollado para mejorar la interacción humano-robot.En la segunda parte, las técnicas desarrolladas anteriormente se han aplicado al reconocimiento de lengua de signos, pero además de ello se propone un método basado en la descomposición de los signos para realizar el reconocimiento de los mismos, añadiendo la posibilidad de una mejor explicabilidad. El objetivo final es desarrollar un tutor de lengua de signos capaz de guiar a los usuarios en el proceso de aprendizaje, dándoles a conocer los errores que cometen y el motivo de dichos errores
Investigating New Forms of Single-handed Physical Phone Interaction with Finger Dexterity
With phones becoming more powerful and such an essential part of our lives, manufacturers are creating new device forms and interactions to better support even more diverse functions. A common goal is to enable a larger input space and expand the input vocabulary using new physical phone interactions other than touchscreen input. This thesis explores how utilizing our hand and finger dexterity can expand physical phone interactions. To understand how we can physically manipulate a phone using the fine motor skills of finger, we identify and evaluate single-handed "dexterous gestures". Four manipulations are defined: shift, spin (yaw axis), rotate (roll axis) and flip (pitch axis), with a formative survey showing all except flip have been performed for various reasons. A controlled experiment examines the speed, behaviour, and preference of manipulations in the form of dexterous gestures, by considering two directions and two movement magnitudes. Using a heuristic recognizer for spin, rotate, and flip, a one-week usability experiment finds increased practice and familiarity improve the speed and comfort of dexterous gestures. With the confirmation that users can loosen their grip and perform gestures with finger dexterity, we investigate the performance of one-handed touch input on the side of a mobile phone. An experiment examines grip change and subjective preference when reaching for side targets using different fingers. Two following experiments examine taps and flicks using the thumb and index finger in a new two-dimensional input space. We simulate a side-touch sensor with a combination of capacitive sensing and motion tracking to distinguish touches on the lower, middle, or upper edges. We further focus on physical phone interaction with a new phone form factor by exploring and evaluating single-handed folding interactions suitable for "modern flip phones": smartphones with a bendable full screen touch display. Three categories of interactions are identified: only-fold, touch-enhanced fold, and fold-enhanced touch; in which gestures are created using fold direction, fold magnitude, and touch position. A prototype evaluation device is built to resemble current flip phones, but with a modified spring system to enable folding in both directions. A study investigates performance and preference for 30 fold gestures, revealing which are most promising. Overall, our exploration shows that users can loosen their grip to physically interact with phones in new ways, and these interactions could be practically integrated into daily phone applications
Multisensory integration: does haptics improve tumour delineation?
The ability to use touch in addition to vision when searching for anomalies and
differences in texture is well known to be beneficial to human perception in general. The aim of this thesis is to evaluate the potential benefit of using a haptic
signal in conjunction with visual images to improve detection and delineation of
tumours in medical imaging data. One of the key issues with tumour delineation in
the field today is the interclinician variance in delineating tumours for diagnostics
and treatment, where even clinicians who have similar sensitivity and precision
levels tend to delineate widely different underlying shapes. Through three experiments we investigate whether the ability to touch a medical image improves
tumour delineation. In the first experiment, we show that combined visuohaptic cues significantly improves performance for signal detection of a 2D Gaussian
embedded in a noisy background. In the second experiment, we found that the
relative dissimilarity of different images per modality did not systematically decrease precision in a two-alternative forced choice (2AFC) slant discrimination
task, in a spatially coaligned visuohaptic rig. In the third and final experiment
we successfully found that observers are significantly better at delineating generated ‘tumours’ in synthetic ‘medical images’ when the haptic representation of the
image is present compared to drawing on a flat surface, in a spatially coaligned
visuohaptic rig
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