Augmented Reality (AR) provides real-time information by superimposing virtual information onto users' view of the real world. Our work is the first to explore how peripheral vision, instead of central vision, can be used to read text on AR and smart glasses. We present Peritext, a multiword reading interface using rapid serial visual presentation (RSVP). This enables users to observe the real world using central vision, while using peripheral vision to read virtual information. We first conducted a lab-based study to determine the effect of different text transformation by comparing reading efficiency among 3 capitalization schemes, 2 font faces, 2 text animation methods, and 3 different numbers of words for RSVP paradigm. We found that title case capitalization, sans-serif font and word-wise typewriter animation with multiword RSVP display resulted in better reading efficiency, which together formed our Peritext design. Another lab-based study followed, investigating the performance of the Peritext against control text, and the results showed significant better performance. Finally, we conducted a field study to collect user feedback while using Peritext in real-world walking scenarios, and all users reported a preference of 5° eccentricity over 8°.

Augmented Reality (AR) provides real-time information by superimposing virtual information onto users' view of the real world. Our work is the first to explore how peripheral vision, instead of central vision, can be used to read text on AR and smart glasses. We present PeriTextAR, a multiword reading interface using rapid serial visual presentation (RSVP)[5]. This enables users to observe the real world using central vision, while using peripheral vision to read virtual information. We first conducted a lab-based study to determine the effect of different text transformation by comparing reading efficiency among 3 capitalization schemes, 2 font faces, 2 text animation methods, and 3 different numbers of words for RSVP paradigm. Another lab-based study followed, investigating the performance of the PeriTextAR against control text, and the results showed significant better performance.

Electric current and voltage are fundamental to learning, understanding, and debugging circuits. Although both can be measured using tools such as multimeters and oscilloscopes, electric current is much more difficult to measure because users have to unplug parts of a circuit and then insert the measuring tools in serial. Furthermore, users need to restore the circuits back to its original state after measurements have been taken. In practice, this cumbersome process poses a formidable barrier to knowing how current flows throughout a circuit. We present CurrentViz, a system that can sense and visualize the electric current flowing through a circuit, which helps users quickly understand otherwise invisible circuit behavior. It supports fully automatic, ubiquitous, and real-time collection of amperage information of breadboarded circuits. It also supports visualization of the amperage data on a circuit schematic to provide an intuitive view into the current state of a circuit.

The rise of Maker communities and open-source electronic prototyping platforms have made electronic circuit projects increasingly popular around the world. Although there are software tools that support the debugging and sharing of circuits, they require users to manually create the virtual circuits in software, which can be time-consuming and error-prone. We present CircuitSense, a system that automatically recognizes the wires and electronic components placed on breadboards. It uses a combination of passive sensing and active probing to detect and generate the corresponding circuit representation in software in real-time. CircuitSense bridges the gap between the physical and virtual representations of circuits. It enables users to interactively construct and experiment with physical circuits while gaining the benefits of using software tools. It also dramatically simplifies the sharing of circuit designs with online communities.

Augmented Reality (AR) provides real-time information by super-imposing virtual information onto users' view of the real world. Our work is the first to explore how peripheral vision, instead of central vision, can be used to read text on AR and smart glasses. We present PeriText+, a multiword reading interface using rapid serial visual presentation (RSVP). This enables users to observe the real world using central vision, while using peripheral vision to read text. We conducted a lab study to compare reading efficiency among 40 different conditions of text transformation. We also conducted a field study to evaluate the information transfer while using PeriText+ in a real-world walking scenario.

Force sensing has been widely used for bringing the touch from binary to multiple states, creating new abilities on surface interactions. However, prior proposed force sensing techniques mainly focus on enabling force-applied gestures on certain devices. This paper presents Nail+, a technique using fingernail deformation to enable force touch sensing interactions on everyday rigid surfaces. Our prototype, 3x3 0.2mm strain sensor array mounted on a fingernail, was implemented and conducted with a 12-participant study for evaluating the feasibility of this sensing approach. Result showed that the accuracy for sensing normal and force-applied tapping and swiping can achieve 84.67% on average. We finally proposed two example applications using Nail+ prototype for controlling the interfaces of head-mounted display (HMD) devices and remote screens.

The rise of smartwatches calls for efficient, convenient and suitable text input methods for these small computers. The minuscule size of these screens brings many challenges on how to interact with these devices. Keyboard design requires optimization for these small screens to provide a good user experience and fast text entry method on these devices. We introduce SwipeKey, a text input method that uses swipe directions to allow multiple inputs per button and thus allows for an increase in the effective size of input buttons. We have conducted thorough experiments optimizing SwipeKey to create a fast, low-error, and easy to learn soft keyboard for smartwatches. These benefits result from having a keyboard that emphasizes the use of swipe motions. Our user study results show that with a specific combination of swipe directions and corresponding button size, SwipeKey users achieved a speed of 11 in words per minute (WPM), a 53% improvement from baseline (7.2 in WPM) and dramatically decreased character error rate (CER) from the baseline of 10% down to 3.4%.

With the advent of the technological era, Computer Vision Syndrome (CVS) has become a common problem. Due to the small hand-held form of smartphones, many users are not aware of the distance between eyes and the device. This habit may lead to negative impacts on ocular health. Always keeping a safe distance prevents the user from CVS. In this paper, we present a mobile application that utilizes the front camera to estimate the distance between the phone and the user. Once this distance is too short, the system alerts the user. We explore four different types of warnings: Blur, Flashing Border, Spot, and Push Notification. We conducted user studies to measure satisfaction, effectiveness, and distraction of these warning methods. Our results show that our system is effective in reminding users to keep a safe distance.

his study investigates the cognitive processes involved in program comprehension based on eye gaze tracking. Thirty-eight participants were asked to comprehend the test programs. Eye-movement analysis was employed to track the students' gaze paths while they traced the programs for comprehension. Cognitive processes were then obtained by sequential analysis of the gaze data to investigate the significant sequences of attention areas. The mined cognitive processes were compared between high and low comprehenders. The experiment results show that most subjects focused on major part of the program to comprehend the program. However, high comprehenders traced the program in a more logical manner. In addition, low comprehenders needed more manual calculation and also needed to trace back to prior statements for recalling required information, which might be because they had limited working memory capacities for computing and memorizing. Subjects performed better on cognitive processes involved in the working memory (short-term memory, mental arithmetic, and logical thinking) also performed better on program comprehension. Working memory seems to play an important role in program comprehension. These results can provide suggestions for researchers/instructors to develop adaptive instructional strategies for students of different characteristics.