A head mounted augmented reality design practice for maintenance assembly: Toward meeting perceptual and cognitive needs of AR users

Usability evaluation of augmented reality visualizations on an optical see-through head-mounted display for assisting machine operations

This study explores the effect of using different visual information overlays and guiding arrows on a machine operation task with an optical see-through head-mounted display (OST-HMD). Thirty-four participants were recruited in the experiment. The independent variables included visual information mode (text, animation, and mixed text and animation) and the use of guiding arrows (with and without arrows). In addition, gender difference was also an objective of this study. The task performance indicators were determined based on task completion time and error counts as well as subjective measures (system usability scale, NASA task load index, and immersion scale). This study used the mixed analysis of variance design to evaluate the main and interaction effects. The results showed that males performed better when using the mixed text and animation mode. Females performed better when using the text mode. In addition, using the mixed text and animation mode demonstrated the best outcome in system usability scale and NASA task load index. For the use of guiding arrows, the task completion time was reduced and the system usability scale, NASA task load index, and immersion scale showed positive effects.

Effects of error rates and target sizes on neck and shoulder biomechanical loads during augmented reality interactions

Augmented reality (AR) interactions have been associated with increased biomechanical loads on the neck and shoulders. To provide a better understanding of the factors that may impact such biomechanical loads, this repeated-measures laboratory study evaluated the effects of error rates and target sizes on neck and shoulder biomechanical loads during two standardized AR tasks (omni-directional pointing and cube placing). Twenty participants performed the two AR tasks with different error rates and target sizes. During the tasks, angles, moments, and muscle activity in the neck and shoulders were measured. The results showed that the target sizes and error rates significantly affected angles, moments, and muscle activity in the neck and shoulder regions. Specifically, the presence of errors increased neck extension, shoulder flexion angles and associated moments. Muscle activity in the neck (splenius capitis) and shoulder (anterior and medial deltoids) also increased when the errors were introduced. Moreover, interacting with larger targets resulted in greater neck extension moments and shoulder abduction angles along with higher muscle activity in the splenius capitis and upper trapezius muscles. These findings indicate the importance of reducing errors and incorporating appropriate target sizes in the AR interfaces to minimize risks of musculoskeletal discomfort and injuries in the neck and shoulders.

Acceptability of a head-mounted assistive mouse controller for people with upper limb disability: An empirical study using the technology acceptance model

Due to limited motor capabilities, people with upper limb disabilities have trouble utilizing a typical mouse while operating a computer. Different wearable Assistive Mouse Controllers (AMCs) have been developed to overcome their challenges. However, these people may not be able to realize the importance, ease of use, and social approval of these AMCs due to their fear of new technology, lack of confidence, and lack of ingenuity. These may negatively affect their attitude and intention toward accepting AMCs for equitable human-computer interaction. This study presents the development of a sensor-based head-mounted AMC, followed by an empirical analysis of its acceptance using the Technology Acceptance Model (TAM) from the socioeconomic perspective of Bangladesh. In a similar vein, we examined the effects of three additional psychological constructs-technology anxiety, confidence, and innovation, on its acceptance along with the original components of the TAM. A total of 150 individuals with stroke-induced upper limb disability participated in an online survey, and their responses were analyzed using confirmatory factor analysis and structural equation modeling, following the general least square method. Analysis revealed, about 96.44% of the participants had positive attitude towards the AMC, and almost 88.56% of them had positive intentions to accept it. Furthermore, about 68.61% of them expressed signs of anxiety, 96.35% were confident, and 94.16% of them had an innovative mindset in terms of device usage. The findings imply that individuals with an innovative mentality are more capable of comprehending the practical implications of a new technology than those without one. It is also feasible to reduce technological anxiety and boost a user's confidence while using an AMC by combining an innovative mentality with straightforward device interaction techniques. Additionally, peer encouragement and motivation can significantly enhance their positive attitude towards accepting the AMC for facilitating their interaction with a computer.

The effect of information level of digital worker guidance systems on assembly performance, user experience and strain

Worker guidance systems provide product-specific and digital assembly information and can make an important contribution to increasing productivity and quality and relieving employees, especially in flexible variant assembly. However, a critical factor here is the successful design of the systems. While much of the research focuses on aspects of the hardware, this article is dedicated to the question of how the configuration of the level of information, i.e. the amount and depth of information in worker guidance systems, is affected. For this purpose, two studies, a laboratory study at the Technical University of Darmstadt (N = 53) and a field study at a company (N = 30), were conducted and two variants of the information level of a worker guidance system were compared. The study results show that assembly quality in particular is significantly influenced by the level of information; to the advantage of detailed information. No significant differences were found for production times. For the subjective evaluation of the system as well as for the objective and subjectively perceived strain, it can be stated that the high level of information also performs better. The results thus help to design worker guidance systems more precisely so that they fulfill the information needs of the employees as well as possible.

Multimodal interaction: Input-output modality combinations for identification tasks in augmented reality

Multimodal interaction (MMI) is being widely implemented, especially in new technologies such as augmented reality (AR) systems since it is presumed to support a more natural, efficient, and flexible form of interaction. However, limited research has been done to investigate the proper application of MMI in AR. More specifically, the effects of combining different input and output modalities during MMI in AR are still not fully understood. Therefore, this study aims to examine the independent and combined effects of different input and output modalities during a typical AR task. 20 young adults participated in a controlled experiment in which they were asked to perform a simple identification task using an AR device in different input (speech, gesture, multimodal) and output (VV-VA, VV-NA, NV-VA, NV-NA) conditions. Results showed that there were differences in the influence of input and output modalities on task performance, workload, perceived appropriateness, and user preference. Interaction effects between the input and output conditions on the performance metrics were also evident in this study, suggesting that although multimodal input is generally preferred by the users, it should be implemented with caution since its effectiveness is highly influenced by the processing code of the system output. This study, which is the first of its kind, has revealed several new implications regarding the application of MMI in AR systems.

UXO-AID: A New UXO Classification Application Based on Augmented Reality to Assist Deminers

Unexploded ordnance (UXO) is a worldwide problem and a long-term hazard because of its ability to harm humanity by remaining active and destructive decades after a conflict has concluded. In addition, the current UXO clearance methods mainly involve manual clearance and depend on the deminer’s experience. However, this approach has a high misclassification rate, which increases the likelihood of an explosion ending the deminer’s life. This study proposes a new approach to identifying the UXO based on augmented reality technology. The methodology is presented based on two phases. Firstly, a new dataset of UXO samples is created by printing 3D samples and building a 3D model of the object data file with accurate data for 3D printed samples. Secondly, the development of the UXO-AID mobile application prototype, which is based on augmented reality technology, is provided. The proposed prototype was evaluated and tested with different methods. The prototype’s performance was measured at different light intensities and distances for testing. The testing results revealed that the application could successfully perform in excellent and moderate lighting with a distance of 10 to 30 cm. As for recognition accuracy, the overall recognition success rate of reached 82.5%, as the disparity in the number of features of each object affected the accuracy of object recognition. Additionally, the application’s ability to support deminers was assessed through a usability questionnaire submitted by 20 deminers. The questionnaire was based on three factors: satisfaction, effectiveness, and efficiency. The proposed UXO-AID mobile application prototype supports deminers to classify the UXO accurately and in real time, reducing the cognitive load of complex tasks. UXO-AID is simple to use, requires no prior training, and takes advantage of the wide availability of mobile devices.