論文アブストラクト： The small screens of smartwatches provide limited space for input tasks. Finger identification is a promising technique to address this problem by associating different functions with different fingers. However, current technologies for finger identification are unavailable or unsuitable for smartwatches. To address this problem, this paper observes that normal smartwatch use takes places with a relatively static pose between the two hands. In this situation, we argue that the touch and angle profiles generated by different fingers on a standard smartwatch touch screen will differ sufficiently to support reliable identification. The viability of this idea is explored in two studies that capture touches in natural and exaggerated poses during tapping and swiping tasks. Machine learning models report accuracies of up to 93% and 98% respectively, figures that are sufficient for many common interaction tasks. Furthermore, the exaggerated poses show modest costs (in terms of time/errors) compared to the natural touches. We conclude by presenting examples and discussing how interaction designs using finger identification can be adapted to the smartwatch form factor.
論文アブストラクト： This paper contributes a novel sensing approach to support on- and above-skin finger input for interaction on the move. WatchSense uses a depth sensor embedded in a wearable device to expand the input space to neighboring areas of skin and the space above it. Our approach addresses challenging camera-based tracking conditions, such as oblique viewing angles and occlusions. It can accurately detect fingertips, their locations, and whether they are touching the skin or hovering above it. It extends previous work that supported either mid-air or multitouch input by simultaneously supporting both. We demonstrate feasibility with a compact, wearable prototype attached to a user's forearm (simulating an integrated depth sensor). Our prototype---which runs in real-time on consumer mobile devices---enables a 3D input space on the back of the hand. We evaluated the accuracy and robustness of the approach in a user study. We also show how WatchSense increases the expressiveness of input by interweaving mid-air and multitouch for several interactive applications.
論文アブストラクト： While most rehabilitation technologies target situated exercise sessions and associated performance metrics, physiotherapists recommend physical activities that are integrated with everyday functioning. We conducted a 1-2 week home study to explore how people with chronic pain use wearable technology that senses and sonifies movement (i.e., movement mapped to sound in real-time) to do functional activity (e.g., loading the dishwasher). Our results show that real-time movement sonification led to an increased sense of control during challenging everyday tasks. Sonification calibrated to functional activity facilitated application of pain management techniques such as pacing. When calibrated to individual needs, sonification enabled serendipitous discovery of physical capabilities otherwise obscured by a focus on pain or a dysfunctional proprioceptive system. A physiotherapist was invited to comment on the implications of our findings. We conclude by discussing opportunities provided by wearable sensing technology to enable better functioning, the ultimate goal of physical rehabilitation.
論文アブストラクト： Physiotherapists are increasingly using video conferencing tools for their teleconsultations. Yet, the assessment of subtle differences in body movements remains a challenge. To support lower limb assessment in video consultations, we present SoPhy, a wearable technology consisting of a pair of socks with embedded sensors for patients to wear; and a web interface that displays information about range of weight distribution, foot movement, and foot orientation for physiotherapists in real-time. We conducted a laboratory study of 40 video consultations, in which postgraduate physiotherapy students assessed lower limb function. We compare assessment with and without SoPhy. Findings show that SoPhy increased the confidence in assessing squats exercise and fewer repetitions were required to assess patients when using SoPhy. We discuss the significance of SoPhy to address the challenges of assessing bodily information over video, and present considerations for its integration with clinical practices and tools.