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The trade-off between speed and accuracy in precision tasks is important to evaluate during user interaction with input devices. When different sensory cues are added or altered in such interactions, those cues have an effect on this trade-off, and thus, they affect overall user performance. For instance, adding cues like haptic feedback and stereoscopic viewing will result in more realistic user interaction, thus improving performance in these tasks. Also, adding a noticeable disparity between physical and virtual movements creates a mismatch between visual and proprioceptive systems, which generally has a negative effect on performance. In this study, we investigate the effects of haptic feedback, stereoscopic viewing, and visuo-proprioceptive mismatch on how quickly and accurately users complete a virtual pick-and-place task using the PHANToM OMNI. Through this experiment, we find that in the movement phase of a ring transfer, movement time and user performance are affected by haptic feedback and visuo-proprioceptive mismatch, and the main effects of stereoscopic viewing appears to be limited to the more precise step when the ring is around the target peg.

Effective teaching of concepts related to human computer interaction (HCI) requires introduction of the core paradigms as well as the design and evaluation methodologies to the learners. In this pa...

Design of applications requires proper management of content, interaction elements and space. In web systems flow of interactions is often based on attention catching components in a form of elements of navigation or advertising content. Distance from central part of interface is affecting user behavior, what can be overcome by scaling size of the objects within the interface according to Fitts’s law. Here we examine the effects of flickering elements with different frequency, direction and distance from central elements of webpage on user attention and habituation reduction. The aim of the study was to examine how to overcome users’ resistance to stimuli based on objects flickering with different frequencies located in different directions and distances. We wanted to check if the higher flicker frequency can compensate the larger distance and increase and user focus depending on whether the element is located nearest or farthest, similarly like objects sizes for Fitts’s law. Results showed that flicker increases the attention to objects with higher distance but has no effect on nearest objects. I was possible to improve total time attracted by distance objects by twenty percent, however the higher performance was observed to nearest objects, no matter what frequency was used for them.

The target in an augmented reality (AR) interface is often located in the distance and outside the initial AR viewport, requiring the user to rotate the AR device, instead of translating it, to complete the search and selection of the target. In order to quantitatively analyze rotating the AR device in the AR interface in the selection of a target located outside the initial visual window, we propose and experimentally verify a quantitative model based on angle measurement under two selection techniques: with and without cursor. The results show that the model proposed in this paper can accurately describe the interactive process when a rotating AR device completes the target selection task. With cursor angle measurement achieves a model fitting value of R2 = 0.937, and without cursor angle measurement achieves a model fitting value of R2 = 0.915; hence, good modeling of user performance in AR selection tasks is achieved.

Understanding the endpoint distribution of pointing selection tasks can reveal the underlying patterns on how users tend to acquire a target, which is one of the most essential and pervasive tasks in interactive systems. It could further aid designers to create new graphical user interfaces and interaction techniques that are optimized for accuracy, efficiency, and ease of use. Previous research has explored the modeling of endpoint distribution outside of virtual reality (VR) systems that have shown to be useful in predicting selection accuracy and guide the design of new interactive techniques. This work aims at developing an endpoint distribution of selection tasks for VR systems which has resulted in EDModel , a novel model that can be used to predict endpoint distribution of pointing selection tasks in VR environments. The development of EDModel is based on two users studies that have explored how factors such as target size, movement amplitude, and target depth affect the endpoint distribution. The model is built from the collected data and its generalizability is subsequently tested in complex scenarios with more relaxed conditions. Three applications of EDModel inspired by previous research are evaluated to show the broad applicability and usefulness of the model: correcting the bias in Fitts's law, predicting selection accuracy, and enhancing pointing selection techniques. Overall, EDModel can achieve high prediction accuracy and can be adapted to different types of applications in VR.

Night vision goggles (NVGs) enable aircrew to complete missions in the cover of night, but dramatically increase and alter the distribution of mass borne by the head. Our novel approach to visual target acquisition, based on Fitts’ Law, was used to assess differences across three different performance metrics between low (L) and high (H) head supported mass (HSM) conditions. Fifteen healthy male participants completed time-optimal and reciprocal visual target acquisitions between target pairs arranged in four different movement trajectories. A significant interaction effect was found and subsequent post hoc analysis revealed that participants required more time to acquire the 20 mm target in the H-HSM condition. In the H-HSM condition participants had a higher error index during target acquisition and required more time to move off the target. Our approach demonstrates great promise in distinguishing performance decrements associated with the use of helmeted systems that include NVGs.

In the present era, the use of laptop computer becomes an inseparable part of human life. This throws a challenge to the designers of the computer that the device may be designed keeping in mind the human capability. The human–computer interaction is generally done through the pointing devices such as a mouse, touchpad, joystick, etc. Hence, they should be designed to improve the performance by way of increasing the speed and accuracy during a certain task. In the present research, an analysis was carried out to study the two input pointing devices, namely touchpad and mouse on the basis of throughput and location of the laptop computer. For this, an interface based on ISO 9241, [2000] was designed to study the performance of the subjects. Eighteen subjects were chosen to perform this task to test the accuracy and speed of these two pointing devices. The experiment was performed with five different locations of the laptop. Results are found in terms of throughput using modified Fitts law. From the analyses, it was found that throughput for mouse ranges from 2.86 to 3.27 bits/s, and for touchpad it ranges from 1.89 to 2.16 bits/s. it was also evident from the results that the mouse gave better results at the farther position while the touchpad was proved to be better at closer distances.

In realistic graphical user interfaces, clicking outside a target would require recovery time from an error, e.g., selecting an unintended hyperlink requires reloading the previous webpage. Several studies on target-pointing tasks have examined the effects of a “penalty time” for mis-clicks on movement time and error rate, but the effects on throughput (i.e., a unified metric on pointing performance) have not been thoroughly investigated. We conducted a crowdsourcing study with 127 workers and a lab-based controlled study with 30 university students. The penalty times varied from 0 to 10 s, and the results consistently indicated that the throughput differences were less than 5%, although the error rates were remarkably different when the penalty time was 0 s. This demonstrated the potential of normalization capability of the effective width method of Fitts’ law, and the throughput is considered a valid metric when researchers would like to compare several task conditions in realistic user interfaces in which error operations induce different recovery times. However, because the model fitness using the effective width method was comparatively low when the penalty time was 0 s, comparing throughputs for different conditions is not recommended. We also discussed potential issues related to the effective width method of Fitts’ law, such as endpoints not following a linear relationship to the given target width only under the zero-penalty condition.

Computer game player performance can degrade with delays from both the local system and network. Analytic models and simulations have the potential to enable exploration of player performance with delay as an alternative to time-intensive user studies. This paper presents an analytic model for the distributions of elapsed times for players doing a common game action – selecting a moving target with a mouse with delay – derived from results from prior user studies. We develop and validate our model, then demonstrate the use of our model via simulation, exploring player performance with different game configurations and delays.

This research examined the factors that influence the performance of target-pointing task in virtual reality, and proposed an extended model to incorporate the target depth into the original Fitts’ law, which improved the predictive ability of the model compared with previous methods. The research was carried out through two parts of experiments. The pre-experiment was a priori on the relationship between depth and size perception. The formal experiment mainly discussed the effect of size and depth perception of targets at different depths on the performance of ray-casting interaction when the target retinal image size were same. The experimental results supported the size-distance invariance hypothesis. It has been found that it takes less time to point to a target with a larger depth, that is, a larger size. Our findings confirmed the effect of size and depth perception on ray-casting interactions in virtual reality.

Evaluation of a novel user-performance model’s fitness requires comparison with baseline models, yet it is often time consuming and involves much effort by researchers to collect data from many participants. Crowdsourcing has recently been used for evaluating novel interaction techniques, but its potential for model comparison studies has not been investigated in detail. In this study, we evaluated four existing Fitts’ law models for rectangular targets, as though one of them was a proposed novel model. We recruited 210 crowd workers, who performed 94,080 clicks in total, and confirmed that the result for the best-fit model was consistent with previous studies. We also analyzed whether this conclusion would change depending on the sample size, but even when we randomly sampled data from five workers for 10,000 iterations, the best-fit model changed only once (0.01%). We have thus demonstrated a case in which crowdsourcing is beneficial for comparing performance models.

Assistive robots support people with limited mobility in their everyday life activities and work. However, most of the assistive systems and technologies for supporting eating and drinking require a residual mobility in arms or hands. For people without residual mobility, different hands-free controls have been developed. For hands-free control, the combination of different modalities can lead to great advantages and improved control. The novelty of this work is a new concept to control a robot using a combination of head and eye motions. The control unit is a mobile, compact and low-cost multimodal sensor system. A Magnetic Angular Rate Gravity (MARG)-sensor is used to detect head motion and an eye tracker enables the system to capture the user&rsquo, s gaze. To analyze the performance of the two modalities, an experimental evaluation with ten able-bodied subjects and one subject with tetraplegia was performed. To assess discrete control (event-based control), a button activation task was performed. To assess two-dimensional continuous cursor control, a Fitts&rsquo, s Law task was performed. The usability study was related to a use-case scenario with a collaborative robot assisting a drinking action. The results of the able-bodied subjects show no significant difference between eye motions and head motions for the activation time of the buttons and the throughput, while, using the eye tracker in the Fitts&rsquo, s Law task, the error rate was significantly higher. The subject with tetraplegia showed slightly better performance for button activation when using the eye tracker. In the use-case, all subjects were able to use the control unit successfully to support the drinking action. Due to the limited head motion of the subject with tetraplegia, button activation with the eye tracker was slightly faster than with the MARG-sensor. A further study with more subjects with tetraplegia is planned, in order to verify these results.

In this study, we extend Fitts’ law to enable it to predict the movement time of pointing operations in interfaces, such as those in navigation bars whose items have different clickable and visual widths and intervals between a target and distractors. For this, we conduct two experiments to investigate the effects of distractors on pointing operations and how increasing the interval size changes user performance. We find that the movement time is significantly affected by the clickable width and intervals whereas it is only slightly affected by the visual width. Based on the results, we construct a time prediction model for considering the differences between clickable and visual widths and the intervals between a target and distractors. Our model shows a good fit for not only the data of our two experiments but also for those of three previous studies.

In the graphic design of interaction, multi-task interface design has been a topic of discussion for a long time. There are many kinds of multi-task design methods. As a classic multi-task design, the layout and method of multi task design are constantly updated. In the calculation of Shannon’s formula of one-dimensional motion, the distribution of visual flow is observed by visual movement experiment, and the reasonable layout of stacked multi-task design on mobile devices with interaction on devices with plane surface is discussed. This paper also hopes to provide a useful reference for future multi-task design.

This paper presents the web-based KLM-Form Analyzer (WKLM-FA), a web application that allows the automated estimation of time that a user needs to fill out a web form. Based on feedback from previous studies, this implementation comes to fulfill the need for a cross-platform application of human-computer interaction models, namely the Keystroke Level Model (KLM) and Fitts's Law. WKLM-FA is a new web-based implementation of the KLM-Form Analyzer (KLM-FA), a desktop application that we have developed in our previous work. WKLM-FA also provides additional functionality compared to KLM-FA, such as a user account mechanism, an evaluation tracking feature, and an admin panel to support multiuser functionality. WKLM-FA is the first online KLM-based time estimation tool for web forms and it can be easily used not only by HCI evaluators but also for educational purposes teaching the KLM and the Fitts's law.

This paper describes a technique of gaze-based moving target acquisition achieved by pseudo stopping the target for the time predicted via Fitts' Law, after saccades have been detected. This technique only requires eye-movements for the acquisition of moving targets. The results indicate that participants were able to acquire targets moving at various speeds and with different widths.

A feasibility study was performed to evaluate the control interfaces for a novel trunk support assistive device (Trunk Drive), namely, joystick, force on sternum, force on feet, and electromyography (EMG) to be used by adult men with Duchene muscular dystrophy. The objective of this paper was to evaluate the performance of the different control interfaces during a discrete position tracking task. We built a one degree of freedom flexion-extension active trunk support device that was tested on 10 healthy men. An experiment, based on the Fitts law, was conducted, whereby subjects were asked to steer a cursor representing the angle of the Trunk Drive into a target that was shown on a graphical user interface, using the above-mentioned control interfaces. The users could operate the Trunk Drive via each of the control interfaces. In general, the joystick and force on sternum were the fastest in movement time (more than 40%) without any significant difference between them, but there was a significant difference between force on sternum on the one hand, and EMG and force on feet on the other. All control interfaces proved to be feasible solutions for controlling an active trunk support, each of which had specific advantages.

This study attempted to investigate the effects of the target shape and the movement direction on the pointing time using an eye-gaze input system and extend Fitts' model so that these factors are incorporated into the model and the predictive power of Fitts' model is enhanced. The target shape, the target size, the movement distance, and the direction of target presentation were set as within-subject experimental variables. The target shape included: a circle, and rectangles with an aspect ratio of 1:1, 1:2, 1:3, and 1:4. The movement direction included eight directions: upper, lower, left, right, upper left, upper right, lower left, and lower right. On the basis of the data for identifying the effects of the target shape and the movement direction on the pointing time, an attempt was made to develop a generalized and extended Fitts’ model that took into account the movement direction and the target shape. As a result, the generalized and extended model was found to fit better to the experimental data, and be more effective for predicting the pointing time for a variety of human-computer interaction (HCI) task using an eye-gaze input system.

A head-tracking interface using a mobile device’s front camera was evaluated using two interaction methods: moving the head vs. moving the device. The evaluation used an Apple iPad Air and the multi-directional (MD) target selection test described in ISO 9241-411. Throughput was higher at 1.42 bits per second (bps) using head movement compared to 1.20 bps using device movement. Users also expressed a preference for the head input method in an assessment of comfort questionnaire. In a second user study, input using head movements was tested using a new multi-directional corner (MDC) task with an iPad Air and an Apple iPhone 6. The MDC task has two advantages over the MD task: a wider range of task difficulties is used and target selection is tested over the entire display surface, including corners. Throughputs were similar to those measured in the first user study, thus confirming the utility of the MDC task for evaluations on devices with small displays.

Fitts’ law has been widely used in the human-computer interaction (HCI) field, especially for Graphical User Interface (GUI) design. However, most studies on Fitts’ law were performed with motion control tasks under visual feedback while only a few endeavor to measure human force control behavior. How quickly humans can exert a constant force with a required accuracy and whether this speed-accuracy tradeoff obeys Fitts’ law still needs to be explored. In this paper, human capabilities for controlling absolute magnitudes of fingertip force with discrete visual/audio/haptic feedback cues were observed and compared. Eighteen participants applied constant forces by pressing a force sensor with their index fingers in the three feedback modes respectively. Response time of 24 pairs (4 × 6) of Magnitude-Tolerance conditions were measured. The results showed that the response time obeyed Fitts’ law within a certain range of force accuracy in all the three feedback modes, while the Linear speed-accuracy tradeoff model was almost superior for the force control process than the Meyer formulation and the Shannon formulation. The response time in the audio feedback mode was the shortest among the three feedback conditions. The results may be used as guidelines for applications that rely on accurate and quick force control under different feedback conditions such as fast tapping tasks on a touch screen.

Although many hand exoskeletons have been developed to provide natural hand movements for patients, extraction of motion intents is one of the challenging issues to perform activities of daily living (ADLs). This paper describes a noninvasive electromyography (EMG)-based proportional control for grasping tasks. To perform grasping tasks in ADLs, three degree of freedoms (DOFs) for thumb adduction/abduction, thumb flexion/extension, and four fingers flexion/extension are required at least. In this work, a 2-D Fitts’ Law test is designed as a suitable alternative of real grasping tasks to perform a real-time EMG control for three DOFs required for grasping. The test setup was built to evaluate a user can generate three commands for direct proportional EMG control. Three EMG signals induced by voluntary wrist and thumb movements were recorded to extract users’ intentions, and each signal was used to activate each degree of freedom in Fitts’ law task. A user was asked to move the cursor into the target using three commands such as cursor right, cursor up, and cursor to the initial position. Healthy subjects were performed our developed interface and the results show that the developed interface performed better than that of our previous study using a pattern recognition method. Although there are several issues remain to be resolved, we expect that proportional EMG control could be used to help SCI or stroke patient for controlling a hand exoskeleton.

This study focuses on testing the usability of 3 different sizes of smartphones by children, adults, and the elderly. Forty-seven participants from each age group were recruited. The research consisted of two stages of experiments. In the first experiment, three existing gestures used by the Android system were evaluated: drag, pinch, and double-touch drag. In the second experiment, two additional re-design gestures were tested: multi-long press and slide down. The users' performances were measured based on their overall time, success time, accuracy, Fitts' Law values, and a subjective questionnaire. Among the five gestures, drag and multi-long press were categorized as the drag gesture, and pinch, double-touch drag and slide down were categorized as the enlarging gesture. The results show that children and adults outperformed the elderly in gesture operation. With respect to smartphone size, the subjects had faster response times and better Fitts' Law values on 6-inch phones. When comparing the subjective preference and the objective use measurement values of the two drag gestures and three enlarging gestures among the different age groups, it was found that children and adults were consistent, whereas the elderly were inconsistent. Overall, in operating the original drag and pinch gestures, the elderly exhibited better objective use measurements, but they preferred the improved gestures, such as slide down.

Although several Predetermined Motion time Systems mention the effects of change of path angle during a movement, there does not appear to be any experimental evidence for the quoted effects. Here we report effects of angle changes between zero and 180° during the movement, with and without an intervening target at the end of the first component of the movement. The effects are variable: with ballistic movements without an intervening target there is an increase of MT with path angle change; when there is an intervening target the MT of the first component decreases with change of path angle, while that of the second component increases, so that the total movement time is independent of the change in path angle. When the movements are made under visual control, with no intervening target, MT increases with change of path angle, whereas when there is an intervening target, there is no effect of change of path angle, either on the first or second component of the movement. Thus the occurrence of movement time increments is dependent on the form of motor control and the way in which the path angle change occurs.

Fitts' Law is one of the most robust and well-studied principles in psychology. It holds that movement time (MT) for target-directed aiming movements increases as a function of target distance and decreases as a function of target width. The purpose of this study was to determine whether Fitts' Law is affected not only by the demands of the target on the current trial but also by the requirements for performance on the previous trial. Experiments 1 and 2 examined trial-to-trial effects of varying target width; Experiment 3 examined trial-to-trial effects of varying target distance. The findings from Experiments 1 and 2 showed that moving a finger or cursor towards a large object on a previous trial shortened the movement time on the current trial, whereas the opposite occurred with a small object. In contrast, target distance on the previous trial had no effect on movement time on the current trial. These findings suggest that performance on trial n has a clear and predictable effect on trial n+1 (at least for target width) and that Fitts' Law as it is normally expressed does not accurately predict performance when the width of the target varies from trial to trial.

Unimanual (left and right limbs) and bimanual (in-phase) reciprocal aiming tasks were tested to determine if the control processes used to perform the unimanual aiming tasks were also present in bimanual aiming tasks. Participants were asked to move a cursor as quickly and accurately as possible between the two targets presented in a Lissajous feedback display. The size of the targets created indexes of difficulty (ID) of 3, 4, 5, and 6 and the position of the targets created bimanual and unimanual conditions. The results indicated that, as ID increased, the end-effectors' motion gradually switched from a cyclical to a more discrete motion for both unimanual and bimanual aiming tasks. However, the transition in control processes (i.e., the transition between cyclical and more discrete motions) tended to occur at a lower ID for the bimanual than the unimanual aiming tasks. Results also indicated that at ID6, bimanual aiming tasks were performed slower, more variable, and right limb dwelled at the targets longer than in the unimanual aiming task. No differences in performance were detected between the unimanual (left and right) and bimanual conditions at IDs 3-5. In terms of bimanual coordination, increasing the accuracy requirement resulted in decreased relative phase bias, but not more stable coupling between the two limbs.

The tradeoff between speed and accuracy of human movements has been exploited from many different perspectives, such as experimental psychology, workspace design, human–machine interface. This tradeoff is formalized by Fitts’ law, which states a linear relationship between the duration and the difficulty of the movement. The bigger is the required accuracy in reaching a target or farther is the target, the slower has to be the movement. A variety of computational models of neuromusculoskeletal systems have been proposed to pinpoint the neurobiological mechanisms that are involved in human movement. We introduce a neurocomputational model of spinal cord to unveil how the tradeoff between speed and accuracy elicits from the interaction between neural and musculoskeletal systems. Model simulations showed that the speed–accuracy tradeoff is not an intrinsic property of the neuromuscular system, but it is a behavioral trait that emerges from the strategy adopted by the central nervous system for executing faster movements. In particular, results suggest that the velocity of a previous learned movement is regulated by the monosynaptic connection between cortical cells and alpha motoneurons.

We investigated the performance of 3D pointing using direct touch in a planar surface condition (PC) and a spherical surface condition (SC). In addition, we examined the performance in terms of Fitts’ law. Although the results showed that the performance in SC was slightly worse than PC, SC was higher conformed to Fitts’ law than PC without the conditions involving head rotation (PC’s and SC’s R2 is 0.945 and 0.971, respectively).

The objective of this paper is to explore three different interaction methods in a confirmation task on a head-mounted Augmented Reality (AR) device with a population of children aged 9-11 years. The three interaction methods we look at are voice recognition, gesture recognition, and controller. We conducted a within-subjects study using a Fitts’ Law confirmation task performed by children with a Microsoft HoloLens. We measured elapsed time during the completion of the tasks. Also, we collected usability and fatigue measures using the System Usability Scale and the OMNI RPE (Ratings of Perceived Exertion) scale. We found significant differences between voice and controller for time, fatigue and usability. We also found significant differences between gesture and controller for time, fatigue and usability. We hope to apply the results of this study to improve augmented reality educational tools for children in the future.

A 3D user interface can be adapted in multiple ways according to each user’s needs, skills and preferences. Such adaptation can consist in changing the user interface layout or its interaction techniques. Personalization systems which are based on user models can automatically determine the configuration of a 3D user interface in order to fit a particular user. In this paper, we propose to explore the use of machine learning in order to propose a 3D selection interaction technique adapted to a target user. To do so, we built a dataset with 51 users on a simple selection application in which we recorded each user profile, his/her results to a 2D Fitts Law based pre-test and his/her preferences and performances on this application for three different interaction techniques. Our machine learning algorithm based on Support Vector Machines (SVMs) trained on this dataset proposes the most adapted interaction technique according to the user profile or his/her result to the 2D selection pre-test. Our results suggest the interest of our approach for personalizing a 3D user interface according to the target user but it would require a larger dataset in order to increase the confidence about the proposed adaptations.

We present the performance analysis for the three devices Leap Motion, Myo, and Space Navigator under the framework of Fitts’ law in two and three dimensional applications. One experiment was carry on to evaluate the selection task in a 2D software application, in which is request to the user to select a green rectangle. A second experiment was a 3D game in which an object is displaced until the position of the same object form situated in a different position. The usability of each device is evaluated with the aim of a questionnaire. Based on the results of the conducted experiments, we suggest for which 2D or 3D applications are more suitable the use of these devices: LM and Space Navigator devices can be used in 3D applications; LM is avoided to use it by long periods of time; Myo device can be used in 2D applications.

Although much work has been done and improved solutions have been proposed towards the design and development of keyboard layouts for non-disabled people, very few approaches have addressed the same issue for the physically handicapped group. In this paper, we propose a novel text entry system, namely BADHON, for a specific user base who are unable to use regular keyboards because of limited hand mobility and require a solution to interact with the computer using thumb toe and ankle movement. In order to resolve the inevitable trade-off between faster typing speed acquisition and inconvenience of memorizing a new layout, two different layouts have been proposed. One combines movement time model and linguistic model to ensure good words per minute (WPM) count and other significantly reduces the burden of carrying manual while using the layout by keeping the alphabet’s orientation as easy as possible.

This paper acquaints a head gesture and eye blink controlled human-computer interaction device to obstruct carpal tunnel syndrome (CTS) and making the computer mouse accessible for the differently able individuals. Traditional computer mouse puts a user’s hand for too long in a pronation posture which increases inflammation in the wrist and hand. To solve this problem, in this paper as an alternative to the customary computer mouse is introduced. The system uses three-axis accelerometer and gyroscope to detect the head gesture and translate it into the position of the mouse cursor on the computer screen. The complementary filtering technique obtains a smooth and accurate output from the inertial measurement unit (EMU). To perform the left and right clicking event, the user’s need to shut the left and right eye for a moment while opening another eye. The system usages the deep convolutional neural network (CNN) to classify the individual openness and closeness of both eyes. The implementation details along with the performance evaluation results are delineated in this paper show that the system has extensive control over its performance.

Aimed movement is ubiquitous and has been extensively investigated. However, little research exists when the hand movements are incompatible with eye movements such as when viewing through a mirror or when performing laparoscopic surgery. An experiment was designed to investigate how individuals perform under one-dimensional and two-dimensional inversion with direct viewing as a reference condition. Twenty-four right-handed university students participated in this experiment and completed all aimed movements with a full-factorial design of movement amplitude at three levels and index of difficulty at 10-levels in three visual conditions of direct, viewing through a mirror (1D inversion) and observing through a right-angled mirror (2D inversion). Learning is rather rapid with direct viewing and with 1D inversion. However, participants take a longer time to stabilize their performance in the 2D inversion condition. Fitts' law is robust under all visual conditions. The eye-hand incompatibility increases movement time with 2D inversion taking the longest movement time. Movement time (MT) was split into initiation time (IT), distance covering time (DCT) and acquisition time (AT) based on submovements. The distance covering part is the first submovement that is primarily ballistic and covers around 90% or more of total amplitude. Furthermore, AT allows the aimed movement to be split into two phases: ballistic and visual control. The results show that the transition from ballistic to visual control happens at lower Index of difficulty (ID) values as the level of incompatibility increases. Based on the experiment and prior research, it is appropriate to use the model MT = a + b ID + c√A as it can account for the two phases of ballistic and visual control.

Eye gaze as an input method has been studied since the 1990s, to varied results: some studies found gaze to be more efficient than traditional input methods like a mouse, others far behind. Comparisons are often backed up by Fitts' Law without explicitly acknowledging the ballistic nature of saccadic eye movements. Using a vision science-inspired model, we here show that a Fitts'-like distribution of movement times can arise due to the execution of secondary saccades, especially when targets are small. Study participants selected circular targets using gaze. Seven different target sizes and two saccade distances were used. We then determined performance across target sizes for different sampling windows ("dwell times") and predicted an optimal dwell time range. Best performance was achieved for large targets reachable by a single saccade. Our findings highlight that Fitts' Law, while a suitable approximation in some cases, is an incomplete description of gaze interaction dynamics.

Tables, desks, and counters are often nearby, motivating their use as interactive surfaces. However, they are typically cluttered. As an alternative, we explore touch input along the 'edge' of table-like surfaces. The performance of tapping, crossing, and dragging is tested along the two ridges and front face of a table edge. Results show top ridge movement time is comparable to the top face when tapping or dragging. When crossing, both ridges are at least 11% faster than the top face. Effective width analysis is used to model performance and provide recommended target sizes. Based on observed user behaviour, variations of top and bottom ridge crossing are explored in a second study, and design recommendations with example applications are provided.

Even when in a static position, data acquired from 6 Degrees of Freedom (DoF) trackers is affected by noise, which is typically called jitter. In this study, we analyzed the effects of 3D rotational jitter on Virtual Reality (VR) controllers in a 3D Fitts' law experiment, which explored how such jitter affects user performance. Eight subjects performed a Fitts' law experiment with or without additional jitter on the cursor. Results show that while error rate significantly increased above ±0.5° jitter and subjects' effective throughput started to decrease significantly above ±1° jitter, there was no significant effect on users' movement time. Further, the Fitts's law movement time model was affected when ±2° jitter was applied to the tracker. According to these results, ±0.5° jitter on the controller does not significantly affect user performance for the tasks explored here. The results of our study can guide the design of 3D controller and tracking systems for 3D user interfaces.

This paper presents the first investigation into using the goal-crossing paradigm for object selection with virtual reality (VR) head-mounted displays. Two experiments were carried out to evaluate ray-casting crossing tasks with target discs in 3D space and goal lines on 2D plane respectively in comparison to ray-casting pointing tasks. Five factors, i.e. task difficulty, the direction of movement constraint (collinear vs. orthogonal), the nature of the task (discrete vs. continuous), field of view of VR devices and target depth, were considered in both experiments. Our findings are: (1) crossing generally had shorter or no longer time, and higher or similar accuracy than pointing, indicating crossing can complement or substitute pointing; (2) crossing tasks can be well modelled with Fitts' Law; (3) crossing performance depended on target depth; (4) crossing target discs in 3D space differed from crossing goal lines on 2D plane in many aspects such as time and error performance, the effects of target depth and the parameters of Fitts' models. Based on these findings, we formulate a number of design recommendations for crossing-based interaction in VR.

Objective:The study examines the factors determining the movement time (MT) of positioning an object in an immersive 3D virtual environment.Background:Positioning an object into a prescribed area is a fundamental operation in a 3D space. Although Fitts’s law models the pointing task very well, it does not apply to a positioning task in an immersive 3D virtual environment since it does not consider the effect of object size in the positioning task.Method:Participants were asked to position a ball-shaped object into a spherical area in a virtual space using a handheld or head-tracking controller in the ray-casting technique. We varied object size (OS), movement amplitude (A), and target tolerance (TT). MT was recorded and analyzed in three phases: acceleration, deceleration, and correction.Results:In the acceleration phase, MT was inversely related to object size and positively proportional to movement amplitude. In the deceleration phase, MT was primarily determined by movement amplitude. In the correction phase, MT was affected by all three factors. We observed similar results whether participants used a handheld controller or head-tracking controller. We thus propose a three-phase model with different formulae at each phase. This model fit participants’ performance very well.Conclusion:A three-phase model can successfully predict MT in the positioning task in an immersive 3D virtual environment in the acceleration, deceleration, and correction phases, separately.Application:Our model provides a quantitative framework for researchers and designers to design and evaluate 3D interfaces for the positioning task in a virtual space.

Most AR and VR headsets use stereoscopic displays to show virtual objects in 3D. However, the limitations of current stereo display systems affect depth perception through conflicting depth cues, which then also affect virtual hand interaction in peri-personal space, i.e., within arm's reach. We performed a Fitts' law experiment to better understand the impact of stereo display deficiencies of AR and VR headsets on pointing at close-by targets arranged laterally or along the line of sight. According to our results, the movement direction and the corresponding change in target depth affect pointing time and throughput; subjects' movements towards/away from their head were slower and less accurate than their lateral movements (left/right). However, even though subjects moved faster in AR, we did not observe a significant difference for pointing performance between AR and VR headsets, which means that previously identified differences in depth perception between these platforms seem to have no strong effect on interaction. Our results also help 3D user interface designers understand how changes in target depth affect users' performance in different movement directions in AR and VR.

Contains fulltext : 176656.pdf (Publisher’s version ) (Closed access) Visually guided finger movements include online feedback of current effector position to guide target approach. This visual feedback may be scaled or otherwise distorted by unpredictable perturbations. Although adjustments to visual feedback scaling have been studied before, the underlying brain activation differences between upscaling (visual feedback larger than real movement) and downscaling (feedback smaller than real movement) are currently unknown. Brain activation differences between upscaling and downscaling might be expected because within-trial adjustments during upscaling require corrective backwards accelerations, whereas correcting for downscaling requires forward accelerations. In this behavioural and fMRI study we investigated adjustments during up- and downscaling in a target-directed finger flexion-extension task with real-time visual feedback. We found that subjects made longer and more complete within-trial corrections for downscaling perturbations than for upscaling perturbations. The finger task activated primary motor (M1) and somatosensory (S1) areas, premotor and parietal regions, basal ganglia, and cerebellum. General scaling effects were seen in the right pre-supplementary motor area, dorsal anterior cingulate cortex, inferior parietal lobule, and dorsolateral prefrontal cortex. Stronger activations for down- than for upscaling were observed in M1, supplementary motor area (SMA), S1 and anterior cingulate cortex. We argue that these activation differences may reflect differing online correction for upscaling versus downscaling during finger flexion-extension. 13 p.

Five experiments are reported related to control of arm movement in the sagittal and transverse planes when making paced and unpaced movements. A single group of 12 participants and the same equipment were used in the main experiments to allow comparisons across conditions. As well as the 2 different directions of movement, there were movements that were time-constrained (as in the W. D. A. BeggsC. I. Howarth, 1971, 1972a,b paradigm) and movements that were constrained by the ending tolerance (as in Fitts' paradigm). Results showed that, for movement times as high as 900 ms, the Schmidt and Beggs and Howarth models appeared to describe the time for movements that had time constraint. Fitts' law (P. M. Fitts, 1954 ; P. M. FittsJ. R. Peterson, 1964) applied to movements that were constrained by final accuracy. These results were independent of whether the target was in the aiming or stopping movement direction. A new interpretation of data for movements with time constraint is presented, based on the possible number of accuracy submovements available when near the target. This model suggests that the standard deviation of hits at the target is not dependent on the time spent in reaching the target region, but largely on the time remaining in order to produce final accuracy at the target.

An experiment by Boyle, Kennedy, and Shea (2012) demonstrated that practice tracking a template created from a sine wave results in enhanced performance and transfer on a reciprocal aiming task with an index of difficulty (ID) of 6. An experiment was conducted to determine whether tracking a template constructed from recorded participants' performance with ID = 6 would provide the same benefit. Participants were assigned to one of four groups (Fitts–master, Fitts–yoked, sine–master, and sine–yoked). After acquisition, visual templates were constructed for the Fitts–yoked and sine–yoked conditions. The templates were generated from the unique displacement data of the Fitts– and sine–master participants. These made up the training template for the Fitts– and sine–yoked participants. After acquisition, all participants were asked to perform test trials under their respective acquisition conditions (Test 1) and test trials under ID = 6 reciprocal aiming conditions (Test 2). Results indicated faster movement times in the sine-wave training groups on Test 2 than in both Fitts groups. These results indicate that the presentation of a tracking template can result in lower dwell times in the Fitts–yoked pairing on Test 2. However, the findings indicate the need to use templates that guide the movement in a way that promotes an equal acceleration–deceleration profile paired with smooth target reversal.

A human-computer interface (namely Facial position and expression Mouse system, FM) for the persons with tetraplegia based on a monocular infrared depth camera is presented in this paper. The nose position along with the mouth status (close/open) is detected by the proposed algorithm to control and navigate the cursor as computer user input. The algorithm is based on an improved Randomized Decision Tree, which is capable of detecting the facial information efficiently and accurately. A more comfortable user experience is achieved by mapping the nose motion to the cursor motion via a nonlinear function. The infrared depth camera enables the system to be independent of illumination and color changes both from the background and on human face, which is a critical advantage over RGB camera-based options. Extensive experimental results show that the proposed system outperforms existing assistive technologies in terms of quantitative and qualitative assessments.

Goal: The objective of this study was to evaluate the ability of linear regression models to decode patterns of muscle coactivation from intramuscular electromyogram (EMG) and provide simultaneous myoelectric control of a virtual 3-DOF wrist/hand system. Performance was compared to the simultaneous control of conventional myoelectric prosthesis methods using intramuscular EMG (parallel dual-site control)—an approach that requires users to independently modulate individual muscles in the residual limb, which can be challenging for amputees. Methods: Linear regression control was evaluated in eight able-bodied subjects during a virtual Fitts’ law task and was compared to performance of eight subjects using parallel dual-site control. An offline analysis also evaluated how different types of training data affected prediction accuracy of linear regression control. Results: The two control systems demonstrated similar overall performance; however, the linear regression method demonstrated improved performance for targets requiring use of all three DOFs, whereas parallel dual-site control demonstrated improved performance for targets that required use of only one DOF. Subjects using linear regression control could more easily activate multiple DOFs simultaneously, but often experienced unintended movements when trying to isolate individual DOFs. Offline analyses also suggested that the method used to train linear regression systems may influence controllability. Conclusion and Significance: Linear regression myoelectric control using intramuscular EMG provided an alternative to parallel dual-site control for 3-DOF simultaneous control at the wrist and hand. The two methods demonstrated different strengths in controllability, highlighting the tradeoff between providing simultaneous control and the ability to isolate individual DOFs when desired.

Object selection is the basis of natural user–computer interaction (NUI) in a virtual environment (VE). Among the three-dimensional object selection techniques employed in virtual reality (VR), bare hand-based finger clicking interaction and ray-casting are two convenient approaches with a high level of acceptance. This study involved 14 participants, constructed a virtual laboratory environment in VR, and compared the above two finger-based interaction techniques in terms of aspects of the task performance, including the success rate, total reaction time, operational deviation, and accuracy, at different spatial positions. The results indicated that the applicable distance range of finger clicking interaction and finger ray-casting was 0.2 to 1.4 m and over 0.4 m, respectively. Within the shared applicable distance, the finger clicking interaction achieved a shorter total reaction time and higher clicking accuracy. The performance of finger clicking interaction varied remarkably at the center and edge of the horizontal field of view, while no significant difference was found among ray-casting at various horizontal azimuths. The current findings could be directly applied to the application of bare-hand interaction in VR environments.

We 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. For the hands-free method, we required a tool that can simulate the functionalities of a mouse to point and select without having to touch the device. We used a face tracking software called Camera Mouse in combination with dwell-time selection. This was compared with three hands-on methods, a touchpad with dwell-time selection, a touchpad with tap selection, and face tracking with tap selection. For hands-free input, throughput was 0.65 bps. The other conditions yielded higher throughputs, the highest being 2.30 bps for the touchpad with tap selection. The hands-free condition demonstrated erratic cursor control with frequent target re-entries before selection, particularly for dwell-time selection. Subjective responses were neutral or slightly favourable for hands-free input.

We present Additive Voronoi Cursor (AVC) – a new cursor technique for target selection by dynamically resizing the area cursor based on the analysis of the two different phases of mouse movement: the ballistic and the correction phases during target selection. On-screen Targets can be divided into respective areas dynamically based on both target distribution and cursor velocity. We assumed that to select a target, a user will first perform ballistic/fast cursor movement aiming to the target roughly, then correct the cursor position with slower movement towards the desired target. Therefore, after the ballistic movement, the desired target would locate within the local region closed to the cursor. We defined Additive Weighted Voronoi Diagrams with selectable targets by assigning larger weights to the nearby objects right after the ballistic cursor movement. Therefore, the effective areas of the nearby objects are enlarged, and they can be selected more easily and quickly. We had compared our cursor technique with recent developed area-cursor methods. The results showed that our method performed significantly better on certain configurations.

Participants with motor impairments may not always be available for research or software development testing. To address this, we propose simulation of users with motor impairments interacting with a head-controlled mouse pointer system. Simulation can be used as a stand-in for research participants in preliminary experiments and can serve to raise awareness about ability-based interactions to a wider software development population. We evaluated our prototype system using a Fitts' Law experiment and report on the measured communication rate of our system compared to users without motor impairments and with a previously reported participant with motor impairments.

Disability is a person's condition in the physical, intellectual, mental, and/or sensory limitations in the long term. This study is reserved for those who do not have the lower arm in order to operate the computer normally. This study uses orientation sensor on the smartphone as the main sensor to move the cursor and click. Delivery of data from smartphone to computer is using Bluetooth. This study will compare two gestures from a combination of orientation sensors on the upper arm: gesture 1 using pitch-yaw motion and gesture 2 using pitch-roll motion; to move the cursor on the monitor. Left-click and right-click using ANN is to detect upper arm jerk movements. Evaluation using ISO/TS 9241-411 standard: ergonomics of human-system interaction; which includes performance evaluation and comfort of the gesture. Performance results of throughput, movement time, comfort and fatigue between gestures were not significantly different between those gestures. The result of the effort questionnaire is that gesture 1 has the highest effort on the shoulder and gesture 2 has the highest effort on the hand.