Smartwatches support access to a wide range of private information but little is known about the security and usability of existing smartwatch screen lock mechanisms. Prior studies suggest that smartwatch authentication via standard techniques such as 4-digit PINs is challenging and error-prone. We conducted interviews to shed light on current practices, revealing that smartwatch users consider the ten-key keypad required for PIN entry to be hard to use due to its small button sizes. To address this issue, we propose the Personal Identification Chord (PIC), an authentication system based on a four-button chorded keypad that enables users to enter ten different inputs via taps to one or two larger buttons. Two studies assessing usability and security of our technique indicate PICs lead to increases in setup and (modestly) recall time, but can be entered accurately while maintaining high recall rates and may improve guessing entropy compared to PINs.

SmoothMoves is an interaction technique for augmented reality (AR) based on smooth pursuits head movements. It works by computing correlations between the movements of on-screen targets and the user's head while tracking those targets. The paper presents three studies. The first suggests that head based input can act as an easier and more affordable surrogate for eye-based input in many smooth pursuits interface designs. A follow-up study grounds the technique in the domain of augmented reality, and captures the error rates and acquisition times on different types of AR devices: head-mounted (2.6%, 1965ms) and hand-held (4.9%, 2089ms). Finally, the paper presents an interactive lighting system prototype that demonstrates the benefits of using smooth pursuits head movements in interaction with AR interfaces. A final qualitative study reports on positive feedback regarding the technique's suitability for this scenario. Together, these results indicate show SmoothMoves is viable, efficient and immediately available for a wide range of wearable devices that feature embedded motion sensing.

Smartwatches are emerging device category that feature highly limited input and display surfaces. We explore how touch contact areas, such as lines generated by flat fingers, can be used to increase input expressivity in these diminutive systems in three ways. Firstly, we present four design themes that emerged from an ideation workshop in which five designers proposed concepts for smartwatch touch area interaction. Secondly, we describe a sensor unit and study that captured user performance with 31 area touches and contrasted this against standard targeting performance. Finally, we describe three demonstration applications that instantiate ideas from the workshop and deploy the most reliably and rapidly produced area touches. We report generally positive user reactions to these demonstrators: the area touch interactions were perceived as quick, convenient and easy to learn and remember. Together this work characterizes how designers can use area touches in watch UIs, which area touches are most appropriate and how users respond to this interaction style.

Interacting with smartwatches poses new challenges. Although capable of displaying complex content, their extremely small screens poorly match many of the touchscreen interaction techniques dominant on larger mobile devices. Addressing this problem, this paper presents beating gestures, a novel form of input based on pairs of simultaneous or rapidly sequential and overlapping screen taps made by the index and middle finger of one hand. Distinguished simply by their temporal sequence and relative left/right position these gestures are designed explicitly for the very small screens (approx. 40mm square) of smartwatches and to operate without interfering with regular single touch input. This paper presents the design of beating gestures and a rigorous empirical study that characterizes how users perform them -- in a mean of 355ms and with an error rate of 5.5%. We also derive thresholds for reliably distinguishing between simultaneous (under 30ms) and sequential (under 400ms) pairs of screen touches or releases. We then present five interface designs and evaluate them in a qualitative study in which users report valuing the speed and ready availability of beating gestures.