Human-computer Interaction Approaches Research Articles

Human-computer Interaction (HCI) Approach to Artificial Intelligence in Education (AIEd) in Architectural Design

The field of artificial intelligence (AI) in architectural design (AIEd) has experienced significant growth, and there is great potential for the application of Generative AI (GAI) in architectural design education. However, addressing challenges associated with AI is important. These include overhyped speculation, hidden inherent drawbacks such as fairness and ethics, and a trend of lacking human interaction when AI is involved. To tackle these issues, this paper introduces a triangulated research framework encompassing three key perspectives: vision, technology, and user acceptance. This framework aligns with Human-computer Interaction (HCI) principles, AI technology development, and past experiences in AIEd. By adopting this multi-perspective analysis approach, the paper aims to comprehensively understand the phenomena surrounding AI in architectural design. Furthermore, the research presented in this paper goes beyond theoretical discussions and illustrates how the research findings are applied in practice. It showcases the design of an ongoing architectural design course that incorporates the insights gained from the research. Three key observations from the ongoing designed modules indicate the need to shift the focus towards integrating multi-modal AIs and existing parametric tools. Secondly, it is essential to emphasise AIs as design partners rather than making assumptions about AIs’ specific uses at different stages. Lastly, providing user-friendly tools and theoretical foundations motivates students to explore beyond the design process, expanding their research and design boundaries.

Human-computer intra-action: a relational approach to digital media and technologies

The growing pervasiveness of digital technologies has exposed the entanglements of Human-Computer Interaction (HCI) with its surrounding context, from the immediate vicinity of interfaces to global issues. While often providing solutions to societal issues, interactive technologies also many times contribute to them. They impact and are impacted by the world, in a process of continuous mutual influence and co-constitution that raises important implications not only to user experience, effectiveness and efficiency, but also to ethics, social responsibility and environmental health. In this article, I draw on the new materialism notion of intra-action to propose a conceptual shift to a relational approach for HCI, which I refer to as Human-Computer Intra-Action (HCIA), capable of capturing from the outset the inherent relationships with the world that inform the design of interactive technology. To that end, I propose the notion of relationalities to reflect the synergies and antagonisms around those relationships, and discuss emerging notions of spatiality and temporality by considering the increasing hybridity of socio-technical engagements both in space (local vs. remote) and in time (immediate vs. stretched). Based on that, I propose a preliminary method for mapping intra-actions associated to interactive technologies, envisaged as a starting point to a relational take on their design process.

Digital Alternative Communication for Individuals with Amyotrophic Lateral Sclerosis: What We Have.

Amyotrophic Lateral Sclerosis is a disease that compromises the motor system and the functional abilities of the person in an irreversible way, causing the progressive loss of the ability to communicate. Tools based on Augmentative and Alternative Communication are essential for promoting autonomy and improving communication, life quality, and survival. This Systematic Literature Review aimed to provide evidence on eye-image-based Human-Computer Interaction approaches for the Augmentative and Alternative Communication of people with Amyotrophic Lateral Sclerosis. The Systematic Literature Review was conducted and guided following a protocol consisting of search questions, inclusion and exclusion criteria, and quality assessment, to select primary studies published between 2010 and 2021 in six repositories: Science Direct, Web of Science, Springer, IEEE Xplore, ACM Digital Library, and PubMed. After the screening, 25 primary studies were evaluated. These studies showcased four low-cost, non-invasive Human-Computer Interaction strategies employed for Augmentative and Alternative Communication in people with Amyotrophic Lateral Sclerosis. The strategies included Eye-Gaze, which featured in 36% of the studies; Eye-Blink and Eye-Tracking, each accounting for 28% of the approaches; and the Hybrid strategy, employed in 8% of the studies. For these approaches, several computational techniques were identified. For a better understanding, a workflow containing the development phases and the respective methods used by each strategy was generated. The results indicate the possibility and feasibility of developing Human-Computer Interaction resources based on eye images for Augmentative and Alternative Communication in a control group. The absence of experimental testing in people with Amyotrophic Lateral Sclerosis reiterates the challenges related to the scalability, efficiency, and usability of these technologies for people with the disease. Although challenges still exist, the findings represent important advances in the fields of health sciences and technology, promoting a promising future with possibilities for better life quality.

Enhancing User Experience through Adaptive Human-Computer Interaction

Human-Computer Interaction (HCI) plays a crucial role in designing intuitive and user-friendly interfaces, ensuring efficient and effective interaction between humans and computer systems. Traditional HCI approaches focus on general usability criteria, but with the increasing complexity of modern computer systems and the diverse needs of users, a more personalized and contextually relevant approach is necessary. This research paper explores adaptive approaches in HCI and their impact on enhancing the user experience. The paper begins by providing a background on HCI, emphasizing its significance in today's technology-driven society. It highlights the importance of designing interfaces that meet user expectations and discusses the evolution of HCI from usability- focused approaches to the need for adaptive strategies that cater to individual user needs and preferences. The research objectives are outlined, focusing on investigating the benefits and challenges of adaptive HCI in enhancing user satisfaction and engagement. The paper addresses specific research questions, including the impact of adaptive HCI strategies on user satisfaction, the accommodation of diverse user needs and preferences, and the technical and implementation challenges associated with adaptive HCI

Exploring Students' Experiences and Problems in Online Teaching and Learning During Covid-19 and Improvement of Current LMS through Human-Computer Interaction (HCI) Approaches

This study tried to explore students’ experiences and problems with online teaching and learning during COVID-19 and the improvement of current LMS through Human-Computer Interaction (HCI) approaches. A mixed-method approach was used in this project. A triangulation design was used in this study. This study was held at the university level and from Baltistan University; researchers took 12 students through a purposive sampling method. After thematic analysis, a survey was conducted. There are 2000 students at Baltistan University. 200 university students were randomly selected as the sample of this study. Semi-structured interviews and self-developed questionnaires were used as research tools. Thematic analysis and descriptive statistics were used to analyse the data. This study concluded that self-learning, family and teacher issues, financial, internet and light issues, IT assistance, and training needs at the students, teachers, and parental level were collectively described as a human-computer interface in the online teaching-learning process during COVID-19. All the students believed that when their family and teachers’ issues; financial, internet, and light issues, information technological assistance, and parents, students, and teachers’ training are improved then improvement of current LMS through Human-Computer Interaction approaches has occurred in Baltistan university.

System Development and Evaluation of Human–Computer Interaction Approach for Assessing Functional Impairment for People with Mild Cognitive Impairment: A Pilot Study

Non-pharmacological treatments have gained significant attention in the field of cognitive impairment. Among them, human–computer interaction-based (HCI) methods have emerged as a promising approach due to their broad applicability and convenience in assessing symptoms associated with this progressively debilitating condition. However, existing rehabilitation training systems for cognitive impairment lack effective assessment methods to meet the diverse rehabilitation needs of users. In this article, we surveyed existing HCI-based cognitive rehabilitation training systems and analyzed their advantages and shortcomings. Drawing from the insights gained from these systems, we propose a novel Leap Motion-based building block training system that incorporates system software capable of generating highly realistic virtual scenes, with the added capability of user behavior detection using Kinect. We conducted user testing of this new system, comparing the performance of a representative cohort with mild cognitive impairment (MCI) (n = 9) to that of disease-free participants (n = 10). Additionally, we conducted ergonomic experiments to assess the system’s performance in elderly people. The experimental results revealed significant differences between the MCI cohort and the control cohort. Specifically, the MCI cohort exhibited a reduced range of motion and longer task completion times compared to the control cohort. These findings have the potential to contribute to the differentiation of cognitive levels. In conclusion, our analysis of existing cognitive rehabilitation training systems provides valuable insights for researchers working on the development of future innovative cognitive rehabilitation training systems and enriches the non-pharmacological treatment models for cognitive impairment. Furthermore, the observed relationship between behavioral data, task completion times, and cognitive levels in older adults offers useful insights for the design of HCI-based approaches for diagnosing and assessing the treatment of MCI.

A Multimodal Human-Computer Interaction for Smart Learning System

The rise of digitalization and computing devices has transformed the educational landscape, making traditional teaching methods less productive. In this context, early and continuous user interaction is crucial for designing and developing effective learning applications. The field of Human-Computer Interaction (HCI) has seen significant technological growth, enabling educators to provide quality educational services through smart input and output channels. However, to prevent students from discontinuing their studies and help them grow their careers, a multimodal HCI approach is needed. This paper proposes a multimodal deep learning multi-layer Convolutional Neural Network (CNN) to improve the educational experience. Our designed system aims to create a promising solution for improving the educational experience and enabling educators to provide high-quality educational services to students. Our implementation results show promising real-time performances, including a high success rate in a constriction learning concept, a quality interaction experience, and enhanced educational services. We evaluated the accuracy of five multimodal inputs, including Finger Touch (FT), Hands Up (HU), Hands Down (HD), Voice Command (VC), and Click/Typing (CT). The results indicate an average accuracy of 90.8%, 87%, 88.6%, 91.8%, and 87%, respectively, demonstrating the effectiveness of our proposed approach.

RETRACTED ARTICLE: Evaluating human–computer interaction education based on active learning methods using the CRITIC and TOPSIS approach

With the ever-growing development of information technology, the education sector has adopted advanced technologies to improve this field. Various procedures based on human–computer interaction (HCI) can be applied to enhance the efficiency of interaction between humans and computers, especially in education. Active learning is one of the major technological fields that improve the usability of active learning. The implementation of HCI approaches such as project-based learning (PBL), active learning classrooms (ALCs), and multi-user virtual environments (MUVE) can improve students' learning capabilities and teachers' teaching skills, making education more effective. After studying different applications of HCI in active learning, this study aims to extract common features and identify the most efficient ones. For the evaluation process, we presented two techniques: Criteria Importance Through Inter Correlation (CRITIC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to select the most effective HCI approach among various options. We chose nine criteria along with ten alternatives and ranked them based on their performance scores. For assigning weights to criteria, we utilized the CRITIC strategy, while the TOPSIS technique was applied to rank the alternatives. In the proposed study, we identified that the alternative with the highest performance score is placed in first place, while the alternative with the worst performance score is placed at the bottom. The study concluded that the most efficient and effective approach was selected among various options, which can be used as a suggestion for decision-related issues and future directions.

A Unified Look at Cultural Heritage: Comparison of Aggregated Scanpaths over Architectural Artifacts

The paper contributes to scanpath bundling methods. We propose an analytical approach for statistical comparisons of aggregated scanpath visualizations by means of second-order gaze analysis metrics. The present study explores differences in attention distribution and cognitive processing over architectural objects between architects, art historians, and non-experts. The results show between-group differences in attention dynamics of the aggregated scanpaths. The aggregated scanpaths of both expert groups were focal, while non-experts' scanpaths were ambient. Experts also paid more attention to and tended to remember better the architectural details and their location. The discussion explores the scalability of the proposed approach for Human-Computer Interaction and accessibility technologies designed to enhance the experience of cultural heritage.

VIRTUSOFT- The Virtual System

Many modules are developed to assist the physical world interact with the digital world. Here we present a very unique approach for Human Computer Interaction (HCI) where, we control Cursor movement, Keyboard typing with alternative input hardware collectively switch, and a Camera method presented integrates tricks operation like Clicking and Saving the photos in gallery are visiting be performed with the numerous hand gestures by using webcam as data device employing a real-time web camera. During this “VIRTUSOFT” Our method is to use a web camera and computer vision technology, like image segmentation, background subtraction and color tracking to manage mouse tasks (left clicking, right clicking, double clicking and scrolling actions) which we show how it can perform everything as current hardware devices can. For the thing recognition and tracking the color pointer has been used and implement the module with none physical contact with the system. Click events of the mouse are achieved by detecting the quantity of recommendations on the pictures.

Computer-Supported Experiential Learning-Based Tool for Healthcare Skills.

Care experiences and health outcomes may suffer greatly because of healthcare professionals' deficient educational preparation and practices. The limited awareness about the impact of stereotypes, implicit/explicit biases, and Social Determinants of Health (SDH) may result in unpleasant care experiences and healthcare professional-patient relationships. Additionally, as healthcare professionals are no less prone to have biases than other people, it is essential to deliver the learning platform to enhance healthcare skills (e.g., awareness of the importance of cultural humility, inclusive communication proficiencies, awareness of the enduring impact of both SDH and implicit/explicit biases on health outcomes, and compassionate and empathetic attitude) of healthcare professionals which eventually help to raise health equity in society. Moreover, employing the "learning-by-doing" approach directly in real-life clinical practices is less preferable wherein high-risk care is essential. Thus, there is a huge scope to deliver virtual reality-based care practices by engaging the digital experiential learning and Human-Computer Interaction (HCI) approach to enhance patient care experiences, healthcare experiences, and healthcare skills. Thus, this research provides the Computer-Supported Experiential Learning (CSEL) approach-based tool or mobile application that facilitates virtual reality-based serious role-playing scenarios to enhance the healthcare skills of healthcare professionals and for public awareness.

Spin-Antenna: Enhanced 3D Motion Tracking Via Spinning Antenna Based on COTS RFID

With the rising of demands for novel Human-Computer Interaction (HCI) approaches in the 3D space, a number of intelligent approaches have been proposed to achieve the HCI by tracking the translation and rotation of the target devices. In this paper, we propose to realize a light-weight, battery-free, 3D motion tracking solution by leveraging a spinning linearly polarized antenna to track a passive RFID tag array. Instead of using the fixed antennas, which can only receive stable signal in some specific environments due to the unpredictable multipath effect, we propose to mitigate the multipath effect and the ambient interference by continuously spinning a linearly polarized antenna, and then extract the most distinctive features based on the optimal reading conditions of the spinning antenna. In particular, because the phase variation around the matching direction is more stable while the RSSI variation around the mismatching direction is more distinctive, we leverage such matching/mismatching property of the linearly polarized antenna to extract the most distinctive features for motion tracking. To depict the property, we build a theoretical model to explain the RSSI and the phase variation of the RFID tag along with the spinning of the antenna, and further extend the model from a single RFID tag to an RFID tag array. Based on the model, we can extract the distinctive RSSI features for the rotation tracking and the stable phase features for the translation tracking. Moreover, to tackle the low rate of feature extraction due to the spinning of antenna, we further propose to enhance the unstable phase features based on the overall trend of other tags with interpolation, such that the sampling rate can be efficiently improved. Finally, we propose a LSTM (Long Short Term Memory)-based network to track the 3D motion based on the signal features extracted based on the polarization model. The experimental results show that our system can achieve an average error of 10.45 cm in the translation tracking, and an average error of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$6.02^\circ$</tex-math></inline-formula> in the rotation tracking in the 3D space.

Meaningful XAI based on user-centric design methodology: Combining legal and human-computer interaction (HCI) approaches to achieve meaningful algorithmic explainability.

Meaningful XAI based on user-centric design methodology: Combining legal and human-computer interaction (HCI) approaches to achieve meaningful algorithmic explainability.

A Systematic Review of Human–Computer Interaction (HCI) Research in Medical and Other Engineering Fields

This article provides a systematic review of research related to Human–Computer Interaction techniques supporting training and learning in various domains including medicine, healthcare, and engineering. The focus is on HCI techniques involving Extended Reality (XR) technology which encompasses Virtual Reality, Augmented Reality, and Mixed Reality. HCI-based research is assuming more importance with the rapid adoption of XR tools and techniques in various training and learning contexts including education. There are many challenges in the adoption of HCI approaches, which results in a need to have a comprehensive and systematic review of such HCI methods in various domains. This article addresses this need by providing a systematic literature review of a cross-section of HCI approaches involving proposed so far. The PRISMA-guided search strategy identified 1156 articles for abstract review. Irrelevant abstracts were discarded. The whole body of each article was reviewed for the remaining articles, and those that were not linked to the scope of our specific issue were also eliminated. Following the application of inclusion/exclusion criteria, 69 publications were chosen for review. This article has been divided into the following sections: Introduction; Research methodology; Literature review; Threats of validity; Future research and Conclusion. Detailed classifications (pertaining to HCI criteria and concepts, such as affordance; training, and learning techniques) have also been included based on different parameters based on the analysis of research techniques adopted by various investigators. The article concludes with a discussion of the key challenges for this HCI area along with future research directions. A review of the research outcomes from these publications underscores the potential for greater success when such HCI-based approaches are adopted during such 3D-based training interactions. Such a higher degree of success may be due to the emphasis on the design of user-friendly (and user-centric) training environments, interactions, and processes that positively impact the cognitive abilities of users and their respective learning/training experiences. We discovered data validating XR-HCI as an ascending method that brings a new paradigm by enhancing skills and safety while reducing costs and learning time through replies to three exploratory study questions. We believe that the findings of this study will aid academics in developing new research avenues that will assist XR-HCI applications to mature and become more widely adopted.

Wearable Devices in Diving: Scoping Review.

BackgroundWearables and their benefits for the safety and well-being of users have been widely studied and have had an enormous impact on the general development of these kinds of devices. Yet, the extent of research into the use and impact of wearable devices in the underwater environment is comparatively low. In the past 15 years, there has been an increased interest in research into wearables that are used underwater, as the use of such wearables has steadily grown over time. However, there has so far been no clear indication in the literature about the direction in which efforts for the design and construction of underwater wearable devices are developing. Therefore, the analysis presented in this scoping review establishes a good and powerful basis for the further development and orientation of current underwater wearables within the field.ObjectiveIn this scoping review, we targeted wearable devices for underwater use to make a comprehensive map of their capabilities and features and discuss the general direction of the development of underwater wearables and the orientation of research into novel prototypes of these kinds of devices.MethodsIn September 2021, we conducted an extensive search for existing literature on 4 databases and for grey literature to identify developed prototypes and early-stage products that were described and tested in water, could be worn and interacted with (eg, displays, buttons, etc), and were fully functional without external equipment. The studies were written in English, came from peer-reviewed academic sources, and were published between 2005 and 2021. We reviewed each title and abstract. The data extraction process was carried out by one author and verified by another author.ResultsIn total, 36 relevant studies were included. Among these, 4 different categories were identified; 18 studies dealt primarily with safety devices, 9 dealt with underwater communication devices, 7 dealt with head-up displays, and 2 dealt with underwater human-computer interaction approaches. Although the safety devices seemed to have gained the most interest at the time of this study, a clear trend toward underwater communication wearables was identified.ConclusionsThis review sought to provide a first insight into the possibilities and challenges of the technologies that have been used in and for wearable devices that are meant for use in the underwater environment. Among these, underwater communication technologies have had the most significant influence on future developments. Moreover, a topic that has not received enough attention but should be further addressed is human-computer interaction. By developing underwater wearables that cover 2 or more of the technology categories that we identified, the extent of the benefits of such devices can be significantly increased in the future.

What Drives the Digital Customer Experience and Customer Loyalty in Mobile Short-Form Video Shopping? Evidence from Douyin (TikTok)

Mobile short-form video (MSFV) shopping represents an emerging method of mobile e-commerce and indicates the future development trend of mobile e-commerce. Unlike other famous mobile commerce applications, MSFV apps provide customers with animated videos which enable them to view product information vividly. This study examines the associations between digital customer experience and customer loyalty based on a human–computer interaction approach. We draw on content quality, relationship quality, and stickiness to investigate customer attitudinal loyalty and behavioral loyalty. A total of 796 users who use the leading MSFV app in China were randomly surveyed, among whom 778 users were involved in testing the hypotheses. Our findings indicate that content and relationship quality positively influence customers’ stickiness to MSFV shopping. Moreover, stickiness positively mediates the indirect link between content quality and customer loyalty as well as relationship quality and customer loyalty. This study demonstrates the value of extending the human-computer interaction approach to MSFV shopping and contributes to the existing literature by offering a deeper understanding of customer loyalty in the context of MSFV shopping. In addition, it has some managerial implications for making the most of the MSFV app’s huge potential to help the sustainable growth of mobile e-commerce.

A Unified Representation of Control Logic in Human-Ultrasound Machine Interaction.

Advances in human-computer interaction (HCI) technologies have granted sonographers and radiologists a much improved user experience when operating different ultrasound (US) machines. Continued HCI improvements in US would benefit from a systematic study of the HCI control logic used in this domain. Such a study has not been presented previously and is the subject of this paper. We surveyed sonographers to determine the most frequently used controls in US machines. We standardized the representation of the US machine HCI control logic by using the unified modelling language (UML). We used UML diagrams to analyze the HCI control logic of 10 different cart-based US machines from several major manufacturers, and we discovered that the control logic for the most frequently used functions are identical. While this control logic does not follow an established standard, it has been commonly adopted. Using the UML for the visualization and formulation of control logic, we can target logically optimal interactions (whose operation steps cannot be further reduced), e.g., adjustment of B-mode gain, frequency and depth, and can derive methods to simplify logically sub-optimal interactions, e.g., the pointing and selecting operation, as well as image measurements.Our study provides insights into existing HCI approaches used in US machines and establishes a rigorous UML-based framework for future US machine design to improve interoperability, efficiency and ease-of-use.

Utilising the triboelectricity of the human body for human-computer interactions

Human-computer interaction (HCI) strategies communicate the human mind and machine intelligence based on different devices and technologies. The majority of HCI strategies assume normal physical conditions that limit accessibility for users with disabilities. Certain products, such as Braille keyboards, work fine for people with specific disabilities. However, a more general HCI strategy that can neglect users’ physical conditions would enhance the accessibility of these tools for disabled persons. Here, we report an HCI strategy that utilises triboelectricity of the human body (TEHB) for HCI. The TEHB can be generated by many parts of the human body, eliminating the obstacles imposed by physical function disabilities. Such an HCI approach has been used for text inputs, graphical inputs, and mimicked mouse functions. With the assistance of deep learning, an accuracy of approximately 98.4 % is achieved for text inputs obtained directly from handwriting. Our findings provide a new approach for HCI and demonstrate the feasibility of multiple interaction modes.

When hearts speak

This article gathers and analyses research on biosensing user-interface design strategies and empirical research approaches in human-computer interaction (HCI). Placing human experience at the core of the primary investigation, this research article will explore Soma Design strategies developed by researcher and computer scientist Kristina Höök and comparable approaches in human computer mediations. In addition, this article investigates the peculiarities of creating a container and expressive model for architectonic media based on WorldMaker Universe (WMU) schematic, a software framework for the development of computational artworks, created by scholar and artist Mark-David Hosale and explores works and research that intersect the art and science domains. This research document also offers a unique angle on the creative and technical processes of creating a bio-art installation and virtual sculpture called Somatic Interventions, developed as a group assignment for the Vertical Studio Lab course taught by Professor Mark-David Hosale at York University, Toronto, Canada. It will critically examine and question the sculpture design’s architectural choices and evaluate the biosignal feedback system that connects human participants to internally built artificial chemistry and multiple layers of unique state machines.

Real-Time Sign Language Detection using TensorFlow, OpenCV and Python

Abstract: Deaf and hard-of-hearing persons, as well as others who are unable to communicate verbally, utilise sign language to communicate within their communities and with others. Sign languages are a set of preset languages that communicate information using a visual-manual modality. The dilemma of real-time finger-spelling recognition in Sign Language is discussed. We gathered a dataset for identifying 36 distinct gestures (alphabets and numerals) and a dataset for typical hand gestures in ISL created from scratch using webcam images. The system accepts a hand gesture as input and displays the identified character on the monitor screen in real time. This project falls under the category of human-computer interaction (HCI) and tries to recognise multiple alphabets (a-z), digits (0-9) and several typical ISL hand gestures. To apply Transfer learning to the problem, we used a Pre-Trained SSD Mobile net V2 architecture trained on our own dataset. In the vast majority of situations, we constructed a robust model that consistently classifies Sign language. Many studies have been done in the past in this area employing sensors (such as glove sensors) and other image processing techniques (such as edge detection technique, Hough Transform, and so on), but these technologies are quite costly, and many people cannot afford them. During the study, various human-computer interaction approaches for posture recognition were investigated and evaluated. The optimum solution was determined to comprise a set of image processing approaches with Human movement categorization. Without a controlled background and low light, the system can detect chosen Sign Language signs with an accuracy of 70-80%. As a result, we're creating this software to assist such folks because it's free and simple to use. However, aside from a small group of people, not everyone is familiar with sign language, and they may need an interpreter, which may be cumbersome and costly. This research intends to bridge the communication gap by building algorithms that can anticipate alphanumeric hand motions in sign language in real time. The main goal of this research is to create a computer-based intelligent system that will allow deaf persons to interact effectively with others by utilising hand gestures. Keywords: Pre-Trained SSD Mobile net V2, Sign Language , HCI