Controlling smart homes via vendor-specific apps on smartphones is cumbersome. Augmented Reality (AR) offers a promising alternative by enabling direct interactions with Internet of Things (IoT) devices. However, using AR for smart home control requires knowledge of each device’s 3D position. In this paper, we introduce and evaluate three concepts for identifying IoT device positions with varying degrees of automation. Our mixed-methods laboratory study with 28 participants revealed that, despite being recognized as the most efficient option, the majority of participants opted against a fast, fully automated detection, favoring a balance between efficiency and perceived autonomy and control. We link this decision to psychological needs grounded in self-determination theory and discuss the strengths and weaknesses of each alternative, motivating a user-adaptive solution. Additionally, we observed a “wow-effect” in response to AR interaction for smart homes, suggesting potential benefits of a human-centric approach to the smart home of the future.

Running is a widely popular physical activity that offers many health benefits. As runners progress with their training, understanding one’s own body becomes a key concern in achieving wellbeing through running. While extensive bodily sensing opportunities exist for runners, understanding complex sensor data is a challenge. In this paper, we investigate how data from shoe-worn sensors can be visualised to empower runners to improve their technique. We designed GraFeet—an augmented running shoe that visualises kinesiological data about the runner’s feet and gait. We compared our prototype with a standard sensor dashboard in a user study where users ran with the sensor and analysed the generated data after the run. GraFeet was perceived as more usable; producing more insights and less confusion in the users. Based on our inquiry, we contribute findings about using data from body-worn sensors to support physically active individuals.

Body movements, from a short smile to a marathon run, are driven by muscle activity. Despite the fact that measuring muscle activity with electromyography (EMG) is technically well established, it is highly complex and its use in interfaces has been limited. Easy access to muscle sensing can offer new opportunities to Human-Computer Interaction (HCI) research. Off-the-shelf sensors often only provide low-level access, hence requiring expertise in signal processing and widening the gulf of execution for users without engineering skills. To address this challenge, we introduce EMBody, a data-centric toolkit for EMG-based interface prototyping and experimentation. EMBody offers multiple levels of prototyping fidelity for EMG sensing, signal processing, and data interpretation. Our data-centric toolkit encapsulates the different data representation stages, offering a wide range of customization opportunities to experts while also allowing non-technical designers to focus on creating new interaction techniques. EMBody features a lightweight form factor and wireless connectivity. Additionally, the system leverages an exploration-centered workflow by allowing rapid access to measurement data via the accompanying software. Users define a set of motions to be recognized and interactively provide example data points. The toolkit then handles signal processing and classification. The recognized movements are streamed on the local network, ready to be used by interactive applications. This paper reports on how to use EMBody and its implementation. We iteratively developed the toolkit in a series of workshops and example applications. Users who had none or very limited knowledge of EMG could rapidly create engaging functional prototypes, while experts appreciated the modularity of the software component allowing for a high degree of customization. We contribute the software and hardware components of EMBody as a tool for the research community to stimulate creative exploration of EMG systems.

The more people commute by bicycle, the higher is the number of cyclists using their smartphones while cycling and compromising traffic safety. We have designed, implemented and evaluated two prototypes for smartphone control devices that do not require the cyclists to remove their hands from the handlebars—the three-button device Tribike and the rotation-controlled Brotate. The devices were the result of a user-centred design process where we identified the key features needed for a on-bike smartphone control device. We evaluated the devices in a biking exercise with 19 participants, where users completed a series of common smartphone tasks. The study showed that Brotate allowed for significantly more lateral control of the bicycle and both devices reduced the cognitive load required to use the smartphone. Our work contributes insights into designing interfaces for cycling.

Augmented Reality (AR) and wearable sensors offer new possibilities to expand our senses and change how we interact with the world. Sensory augmentation can be integrated into everyday activities, but controls remain a challenge for user experience. In this paper, we investigate how users can control a futuristic interface that enables in-situ magnification. We designed an interactive system to enable users to zoom in on objects up to a microscopic level and implemented a prototype using the Microsoft Hololens. In a user-study, we compared full-screen to windowed visualizations and four interaction techniques for zooming: a clicker, two types of gestures, and voice. Our results indicate that the clicker enabled users to zoom at the fastest rate and lowered cognitive load. We also found a preference for windowed views. With our work, we provide insights for future augmented vision systems.

Augmented Reality (AR) is gaining increasing importance in science, education, and entertainment. A fundamental characteristic of AR is blending the virtual and physical world into a coherent environment. In this paper, we examine the effect of substituting the physical components of lab experiments with tangible replicas and virtual representations. We conducted a user study with thirty participants who carried out the experiment in three different abstraction levels (original lab equipment, non-functional tangible props, virtual representation). We compared the users’ performance regarding setup time, experienced workload, quality of measurements, and concept comprehension of the learning task. We found no effect on comprehension but significant differences in setup time and quality of measures. The results indicate that substitution reduces the experiment setup duration without affecting knowledge transfer. These results help to shape future AR learning environments, and we offer insights for creating complex mixed reality learning materials.

While we usually have no trouble with orientation, our sense of direction frequently fails in the absence of a frame of reference. Open-water swimmers raise their heads to look for a reference point, since disorientation might result in exhaustion or even drowning. In this paper, we report on Clairbuoyance - a system that provides feedback about the swimmer's orientation through lights mounted on swimming goggles. We conducted an experiment with two versions of Clairbuoyance: Discrete signals relative to a chosen direction, and continuous signals providing a sense of absolute direction. Participants swam to a series of targets. Proficient swimmers preferred the discrete mode; novice users the continuous one. We determined that both versions of Clairbuoyance enabled reaching the target faster than without the help of the system, although the discrete mode increased error. Based on the results, we contribute insights for designing directional guidance feedback for swimmers.

Current navigation systems for motor cyclists use visual or auditory cues for guidance. However, this poses a challenge to the motorcyclists since their visual and auditory channels are already occupied with controlling the motorbike, paying attention to other road users, and planing the next turn. In this work, we explore how tactile feedback can be used to guide motorcyclists. We present MOVING (MOtorbike VIbrational Navigation Guidance), a smart kidney belt that presents navigation cues through 12 vibration motors. In addition, we report on the design process of this wearable and on an evaluation with 16 participants in a real world riding setting. We show that MOVING outperforms off-the-shelf navigation systems in terms of turn errors and distraction.

Although interaction with computing systems has become remarkably diverse in recent years, the computer mouse remained the primary pointing device for daily computer use. Being solely an input device, the classical mouse decouples input from output. In this paper, we propose to extend the mouse to a device that can be actuated by the user and the computer. We developed a mouse that allows its position and button state to be actuated. In a technical evaluation, we test the spatial resolution of our system and how effectively feedback is communicated to the user. In a subjective assessment, we explore users' reactions to four use cases including games and office applications, highlighting the potential of the device. Through a quantitative assessment, we investigate whether perceiving the movement of the mouse helps to learn gestures. Finally, we discuss how a mouse providing feedback can be used to build novel interaction techniques.