Hands-Free User Interaction for Accessible Computing

Three experiments were conducted to compare hands-free and hands-on input methods for accessible computing. The first experiment compared hands-free and hands-on text-entry on a smart-phone. EVA Facial Mouse, an Android application, was used for facial tracking for the hands-free phase of the experiment. The second experiment used the Fitts law two-dimensional task in ISO 9241-9 to evaluate hands-free and hands-on point-select tasks on a laptop computer. We used a facial-tracking software called Camera Mouse in combination with dwell-time selection. The third user study compared Camera Mouse with the keyboard and touchpad of a laptop to play a simple yet well known game: Snake. A case study was also conducted with a physically challenged participant for the hands-free phase of the gaming experiment. Our key finding from the three experiments and the case study is that the hands-free methods are not yet as well-performing as the hands-on methods

Performance, Characteristics, and Error Rates of Cursor Control Devices for Aircraft Cockpit Interaction

This document is the Accepted Manuscript version of the following article: Peter R. Thomas, 'Performance, Characteristics, and Error Rates of Cursor Control Devices for Aircraft Cockpit Interaction', International Journal of Human-Computer Studies, Vol. 109: 41-53, available online 31 August 2017. Under embargo. Embargo end date: 31 August 2018. Published by Elsevier. © 2017 Elsevier Ltd. All rights reserved.This paper provides a comparative performance analysis of a hands-on-throttle-and-stick (HOTAS) cursor control device (CCD) with other suitable CCDs for an aircraft cockpit: an isotonic thumbstick, a trackpad, a trackball, and touchscreen input. The performance and characteristics of these five CCDs were investigated in terms of throughput, movement accuracy, and error rate using the ISO 9241-9 standard task. Results show statistically significant differences (p < 0.001) between three groupings of the devices, with the HOTAS having the lowest throughput (0.7 bits/s) and the touchscreen the highest (3.7 bits/s). Errors for all devices were shown to increase with decreasing target size (p < 0.001) and, to a lesser effect, increasing target distance (p < 0.01). The trackpad was found to be the most accurate of the five devices, being significantly better than the HOTAS fingerstick and touchscreen (p < 0.05) with the touchscreen performing poorly on selecting smaller targets (p < 0.05). These results would be useful to cockpit human-machine interface designers and provides evidence of the need to move away from, or significantly augment the capabilities of, this type of HOTAS CCD in order to improve pilot task throughput in increasingly data-rich cockpits.Peer reviewedFinal Accepted Versio

Pointing Devices for Wearable Computers

We present a survey of pointing devices for wearable computers, which are body-mounted devices that users can access at any time. Since traditional pointing devices (i.e., mouse, touchpad, and trackpoint) were designed to be used on a steady and flat surface, they are inappropriate for wearable computers. Just as the advent of laptops resulted in the development of the touchpad and trackpoint, the emergence of wearable computers is leading to the development of pointing devices designed for them. However, unlike laptops, since wearable computers are operated from different body positions under different environmental conditions for different uses, researchers have developed a variety of innovative pointing devices for wearable computers characterized by their sensing mechanism, control mechanism, and form factor. We survey a representative set of pointing devices for wearable computers using an “adaptation of traditional devices” versus “new devices” dichotomy and study devices according to their control and sensing mechanisms and form factor. The objective of this paper is to showcase a variety of pointing devices developed for wearable computers and bring structure to the design space for wearable pointing devices. We conclude that a de facto pointing device for wearable computers, unlike laptops, is not likely to emerge

Evaluation of object attributes to study speed-accuracy trade-off of gloves using ISO 9241-411 standard

Selection of appropriate gloves plays an important role in the overall comfort and productivity of workers. Currently, there are no standards and/or guidelines available to systematically evaluate the glove performance based on speed-accuracy trade-off. The ISO 9241-411 standard which is based on Fitts’ Law has been extensively used in the literature to measure speed-accuracy trade-off in terms of throughput in the virtual environments. This study was aimed at developing guidelines for implementing ISO 9241-411 standard in the physical environment so that it can be used to estimate (and compare) throughputs of safety gloves. Specifically, the various physical attributes of objects used in the target transfer tasks (within the ISO 9241-411 standard) were evaluated using an experimental study. Fifteen healthy subjects performed a series of target transfer tasks using three glove conditions (barehand, glove type 1, glove type 2), three object heights (0.28 , 0.43 , 0.88 ), two object materials (nylon, stainless-steel) and two object shapes (circular, hexagonal). The main effect of glove condition was statistically significant. The mean throughput for the barehand was 3.61 bits/sec, and for glove types 1 and 2, the mean throughputs were 3.36 bits/sec and 3.31 bits/sec, respectively. The interaction effect of object height with object material was statistically significant. The mean throughput for 0.88 stainless-steel objects (2.99 bits/sec) was significantly different from 0.88 nylon objects (3.13 bits/sec), but for 0.28 and 0.43 objects, there was no difference in the mean throughput due to difference in the material. The main effect of object shape was statistically insignificant. Based on the additional analysis of different statistical measures, the stainless-steel 0.88 circular object was found to perform better compared to other objects in terms of its ability to distinguish different glove conditions. In summary, this study concludes that it is possible to use ISO 9241-411 standard in a 3-D physical environment to compare barehanded exertions with gloved exertions. However, it cannot be said conclusively that the standard can be used for comparing different gloves

Evaluation of Fitts’ Throughput as a Possible Performance Measure for Manual Assembly Tasks

Assembly lines are the backbone of the manufacturing sector. Workers at the assembly lines are expected to perform fast pace hand-arm exertions with precision and accuracy. To protect the workers from injuries, OSHA mandates the use of personal protective equipment (PPE) including gloves. Certain assembly operations require the use of special gloves. Some of these gloves can inhibit hand performance, further increasing the task difficulty. The Index of Difficulty (ID) is a metric measured in ‘bits’ quantifies task difficulty through the quotient of target width and target motion, i.e., distance travelled. The time required to complete the target motion is the Movement time (MT). The ratio of ID and MT was defined by Fitts as ‘throughput’ and is measured in bits/s. This study aims to evaluate Fitts’ throughput as a possible performance measure for gloves used in the manual assembly tasks. An experimental study was performed using fifteen healthy participants with three types of gloves which were evaluated using two tests, Fitts’ throughput test and a hand tool dexterity test (HTDT). The Fitts’ throughput test was designed using ISO 9241-411 standard and involved a series of target transfer tasks with varying ID levels. In the HTDT test, participants performed a simulated assembly task with different glove conditions. Statistical analysis revealed that the effect of glove condition was significant for both throughput and assembly time. The mean throughput of 3.91 bits/s for bare hand was higher compared to the three glove conditions. Among the three glove conditions, Glove 2 was found to have a higher throughput of 3.72 bits/s followed by Glove 1 with 3.51 bits/s, and Glove 3 with 3.47 bits/s. The mean assembly times for Gloves 2, 1, 3 were 462.52 sec, 501.88 sec and 558.48 sec, respectively. In general, an inverse relationship between throughput and assembly time was observed, indicating that a glove with higher throughput produces lower assembly time. Thus, the study findings seem to indicate that Fitts’ throughput can serve as a possible performance measure for manual assembly tasks

Virtual Dynamic Tunnel: A Target-Agnostic Assistive User Interface Algorithm for Head-Operated Input Devices

Today the effective use of computers (e.g. those with Internet browsers and graphical interfaces) involves the use of some sort of cursor control like what a mouse provides. However, a standard mouse is not always the best option for all users. There are currently many devices available to provide alternative computer access. These devices may be divided into categories: brain-computer interfaces (BCI), mouth-based controls, camera-based controls, and head-tilt controls. There is no single solution as each device and application has to be tailored to each user\u27s unique preferences and abilities. Furthermore, each device category has certain strengths and weaknesses that need to be considered when making an effective match between a user and a device. One problem that remains is that these alternative input devices do not perform as well when compared to standard mouse devices. To help with this, assistive user interface techniques can be employed. While research shows that these techniques help, most require that modifications be made to the user interfaces or that a user\u27s intended target be known beforehand by the host computer. In this research, a novel target-agnostic assistive user interface algorithm intended to improve usage performance for both head-operated and standard mouse devices is designed, implemented (as a mouse device driver and in host computer software) and experimentally evaluated. In addition, a new wireless head-operated input device requiring no special host computer hardware, is designed, built and evaluated. It was found that the Virtual Dynamic Tunnel algorithm improved performance for a standard mouse in straight tunnel trials and that nearly 60% of users would be willing to use the head-tilt mouse as a hands-free option for cursor control

Ability-Based Methods for Personalized Keyboard Generation

This study introduces an ability-based method for personalized keyboard generation, wherein an individual's own movement and human-computer interaction data are used to automatically compute a personalized virtual keyboard layout. Our approach integrates a multidirectional point-select task to characterize cursor control over time, distance, and direction. The characterization is automatically employed to develop a computationally efficient keyboard layout that prioritizes each user's movement abilities through capturing directional constraints and preferences. We evaluated our approach in a study involving 16 participants using inertial sensing and facial electromyography as an access method, resulting in significantly increased communication rates using the personalized keyboard (52.0 bits/min) when compared to a generically optimized keyboard (47.9 bits/min). Our results demonstrate the ability to effectively characterize an individual's movement abilities to design a personalized keyboard for improved communication. This work underscores the importance of integrating a user's motor abilities when designing virtual interfaces.Comment: 20 pages, 7 figure