We present RESi (Resistive tExtile Sensor Interfaces), a novel sensing approach enabling a new kind of yarn-based, resistive pressure sensing. The core of RESi builds on a newly designed yarn, which features conductive and resistive properties. We run a technical study to characterize the behaviour of the yarn and to determine the sensing principle. We demonstrate how the yarn can be used as a pressure sensor and discuss how specific issues, such as connecting the soft textile sensor with the rigid electronics can be solved. In addition, we present a platform-independent API that allows rapid prototyping. To show its versatility, we present applications developed with different textile manufacturing techniques, including hand sewing, machine sewing, and weaving. RESi is a novel technology, enabling textile pressure sensing to augment everyday objects with interactive capabilities.

The increased interest in interactive soft materials, such as smart clothing and responsive furniture, means that there is a need for flexible and deformable electronics. In this paper, we focus on stitch-based elastic sensors, which have the benefit of being manufacturable with textile craft tools that have been used in homes for centuries. We contribute to the understanding of stitch-based stretch sensors through four experiments and one user study that investigate conductive yarns from textile and technical perspectives, and analyze the impact of different stitch types and parameters. The insights informed our design of new stretch-based interaction techniques that emphasize eyes-free or causal interactions. We demonstrate with StretchEBand how soft, continuous sensors can be rapidly fabricated with different parameters and capabilities to support interaction with a wide range of performance requirements across wearables, mobile devices, clothing, furniture, and toys.

Over the last decades, there have been numerous efforts in wearable computing research to enable interactive textiles. Most work focus, however, on integrating sensors for planar touch gestures, and thus do not fully take advantage of the flexible, deformable and tangible material properties of textile. In this work, we introduce SmartSleeve, a deformable textile sensor, which can sense both surface and deformation gestures in real-time. It expands the gesture vocabulary with a range of expressive interaction techniques, and we explore new opportunities using advanced deformation gestures, such as, Twirl, Twist, Fold, Push and Stretch. We describe our sensor design, hardware implementation and its novel non-rigid connector architecture. We provide a detailed description of our hybrid gesture detection pipeline that uses learning-based algorithms and heuristics to enable real-time gesture detection and tracking. Its modular architecture allows us to derive new gestures through the combination with continuous properties like pressure, location, and direction. Finally, we report on the promising results from our evaluations which demonstrate real-time classification.

Today's commercially available prosthetic limbs lack tactile sensation and feedback. Recent research in this domain focuses on sensor technologies designed to be directly embedded into future prostheses. We present a novel concept and prototype of a prosthetic-sensing wearable that offers a non-invasive, self-applicable and customizable approach for the sensory augmentation of present-day and future low to mid-range priced lower-limb prosthetics. From consultation with eight lower-limb amputees, we investigated the design space for prosthetic sensing wearables and developed novel interaction methods for dynamic, user-driven creation and mapping of sensing regions on the foot to wearable haptic feedback actuators. Based on a pilot-study with amputees, we assessed the utility of our design in scenarios brought up by the amputees and we summarize our findings to establish future directions for research into using smart textiles for the sensory enhancement of prosthetic limbs.

In this paper we evaluated the possible application of a passive, optical sensor as an interface for human-smart glasses interactions. The designed proximity sensor is composed of set of photodiodes and the appropriate hardware and software components. First, experiments were performed for the estimations of such parameters as distance to an object, its width and velocity. Achieved results were satisfactory. Therefore, next, a set of static and dynamic hand gestures was proposed together with the related recognition method. The method was verified during experiments with volunteers. Experiments have shown that in appropriate lighting conditions it is possible to detect static and dynamic simple hand gestures using inexpensive and computationally efficient sensor. These features enable the use of such a sensor as one of the smart glasses interfaces.

Early research on head-worn computers (HWCs) has focused on hardware and specific applications. However, there is little research about the everyday usage of head-worn computers in particular aspects such as: context of use, social acceptance across different activities, audiences and interaction techniques. This paper provides insights into the use of head-worn computers by capturing the opinions of novice and expert users through a survey, a three-week diary study, and interviews. The overarching finding is that the context of use is critical, either due to the need to support micro-interactions, or because the interaction paradigm itself should depend on the context of use.

We present Tracs, a dual-sided see-through display system with controllable transparency. Traditional displays are a constant visual and communication barrier, hindering fast and efficient collaboration of spatially close or facing co-workers. Transparent displays could potentially remove these barriers, but introduce new issues of personal privacy, screen content privacy and visual interference. We therefore propose a solution with controllable transparency to overcome these problems. Tracs consists of two see-through displays, with a transparency-control layer, a backlight layer and a polarization adjustment layer in-between. The transparency-control layer is built as a grid of individually addressable transparency-controlled patches, allowing users to control the transparency overall or just locally. Additionally, the locally switchable backlight layer improves the contrast of LCD screen content. Tracs allows users to switch between personal and collaborative work fast and easily and gives them full control of transparent regions on their display.

Using affinity diagramming as an example, we investigate reality-based interfaces for supporting creative group work. Based on an observational study grounded in the reality-based interaction framework, we identified power vs. reality tradeoffs that can be addressed to find a close fit to embodied practice. Using this knowledge, we designed and implemented a digital workspace for supporting affinity diagramming. Its hybrid interaction techniques combine digital pen & paper with an interactive table and tangible tokens. An additional vertical display is used to support reflection-in-action and for enhancing discussion and coordination. A preliminary user study confirmed the applicability of our tradeoffs and the general acceptance of the tool design.