Earticle

All over the world work-related musculoskeletal disorders are starting to take hold among digital device users, especially computer users. Weakness, sleepiness, shoulder pain, back pain/solidness/pain in the neck, and cerebral pain are quite often recorded as clear indicators during or after the use of personal computers, laptops, and devices. The most painful fact is that all these delicate indicators are routinely ignored as a sign of general weakness in most cases. This research work highlights this issue under the belt of Ergonomics. How can construct personal computers, laptops, and their associated equipment to be more human-friendly so that these serious health risks can be avoided, particularly in children. The paper also highlights previous important studies conducted at elementary levels of this subject.

This study attempted to compare usability of auditory interfaces, which is a comprehensive concept that includes safety, utility, effectiveness, and efficiency, in personal computing environments: verbal messages (speech sounds), earcons (musical sounds), and auditory icons (natural sounds). This study hypothesized that verbal messages would offer higher usability than earcons and auditory icons, since the verbal messages are easy to interpret and understand based on semiotic process. In this study, usability was measured by a set of seven items: ability to inform what the program is doing, relevance to visual interfaces, degree of stimulation, degree of understandability, perceived time pressure, clearness of sound outputs, and degrees of satisfaction. Through the experimental research, the results showed that verbal messages provided the highest level of usability. On the contrary, auditory icons showed the lowest level of usability, as they require users to establish new coding schemes, and thus demand more mental effort from users.

This research aims to examine the impact of human-computer interaction (HCI) on user happiness, with a specific focus on social media use, particularly TikTok, and its effects on users' mental health and overall well-being. The study aims to explore the relationship between TikTok use, users' mental health indicators, and subjective happiness levels. By employing a mixed-methods approach involving quantitative surveys and qualitative interviews, this research intends to gather comprehensive data on users' TikTok usage patterns, mental health status, and subjective well-being. The findings will provide valuable insights into the complex relationship between HCI, TikTok use, and users' mental health and well-being, contributing to a deeper understanding of the effects of social media on happiness.

사용자의 수요가 증가함으로 인하여 최근의 마커 기반 증강현실 기술은 제스처 기반 인간-컴 퓨터 상호작용 분야에서 주목을 받고 있다. 그러나 개체가 프레임에서 빠른 움직임을 보일 때 발 생하는 모션 블러 효과에 의하여 마커의 추적 및 감지의 한계점이 발생한다. 기존의 디블러링 기 술들에서 전체 프레임 중 특정 프레임을 추출하는 작업이 없다면 실시간 비디오에서 사용하기에 문제가 있다. 본 논문에서는 인간-컴퓨터 상호작용을 위하여 ArUco 마커를 사용한 특징점 기반 광학흐름 추적 방법을 제안하며, 마커를 이용한 자세 추정 방법을 설명한다. 이 방법은 ArUco 마 커를 감지하고 특수한 마커 추적 방법을 통해 마커 감지를 보완한다. 특히 마커 추적 방법은 FAST 알고리즘을 사용하여 특징점을 추출하고 루카스-카나데 방법을 사용하여 특징점의 움직임 을 분석하여 움직임 벡터를 계산한다. 또한 Perspective-n-Point 문제를 해결하여 마커 포즈 추정 을 구현했다. 제안된 시스템은 기존의 방법보다 높은 검출률을 보였으며, 마커를 포함한 비디오 에서 프레임 처리 속도가 약 37% 향상되었다. 또한 마커 포즈 추정을 그래픽으로 구현하였다. 이 연구는 실제 환경에서 카메라를 통한 제스처 기반 인간-컴퓨터 상호작용 분야와 또한 이동 로봇 분야에도 도움이 될 것이라 기대된다.

Recently, marker-based augmented reality technology has attracted attention in gesture based human-computer interaction due to the users' demand. However, the blur effect that occurs when the object shows fast motion in frames limits the marker detection and tracking. Conventional de-blurring techniques are not effective for real-time video without the task of extracting a specific frame from a full frame. In this paper, we proposed the algorithm which detects special marker first, and also tracks point features of markers based on optical flow method. Especially, marker tracking method extracts point features also using the FAST algorithm and calculates motion vectors by analyzing the motion of point features using Lucas-Kanade method. Also, we implemented a marker pose estimation by solving Perspective-n-Point problem. Our proposed system showed more improved results than conventional methods especially with the rate of 37% higher in the frame processing speed of marker tracking video. In addition, the marker pose estimation was graphically represented. It is expected that this research will be useful for gesture-based human-computer interaction field and mobile robot field through camera in real environment.

This article discusses unremarkable language user interface of human computer interaction areas. Growing demand for language performance in user interface design systems is creating new opportunities to use computer and all applications. Unless systems have proper user interface, there are more stringent constraints on cost and power consumption that lead to design for many applications. In terms of understanding basic challenges faced by user interface, we explore the challengers and goal of user interface. We show three case studies that there are guideline study of speech interface, experimental results on language interaction study, user study on new technology as wearable computer.

본 연구는 학제성이 강한 HCI 연구 내에서 문헌정보학 분야 연구가 수행한 연구내용과 역할을 분석하고 향후 타 학문분야와의 협력 가능성 및 수행 가능한 연구주제를 살펴보고자 하였다. 연구에서 사용된 데이터는 문헌정보학 분야의 대표적인 국내 학술지 및 한국HCI학회 학술대회의 발표논문집에서 추출한 키워드와 소속 정보이며, 이들을 활용하여 네트워크 분석과 빈도 분석을 하였다. 국내 HCI 분야에서는 정보통신, 컴퓨터공학, 기술산업 등이 활발한 교류를 보이고 있었으며, 문헌정보학은 연구 협력에 있어서 비교적 소극적이었다. 문헌정보학 연구의 HCI 분야 내 역할을 살펴본 결과, 타 분야와 협력이 필요한 전문적인 주제에 대해서는 그 관심도가 높지 않음을 발견했다. 그러나 문헌정보학 분야 학술지에 타 학문분야 연구자들이 HCI 관련 논문을 다수 게재했다는 점과 기술산업 분야와도 어느 정도 연결성을 가지고 있다는 점에서, 향후 문헌정보학 분야가 기술산업 등 타 분야와의 협력을 통한 공동연구를 적극적으로 수행한다면 학계 간의 연구주제 확장 및 발전에 기여할 수 있음을 발견하였다.

The purpose of this study was to analyze how the Library and Information Science (LIS) related research efforts in Korea contributed to the progress of the Human Computer Interaction (HCI) discipline to identify the potential collaboration research partners and topics. The following data was used for the network and frequency analysis: titles, keywords and affiliation information extracted from the Korean journals serving the LIS fields as well as the conference proceedings of the Korean HCI society. Information communication technology, computer engineering, and technology industry had been active in research collaborations but LIS field was comparatively not active. This study was able to determine that LIS researchers carried out important research but they had not much interests in the topics that required interdisciplinary collaboration. However, there were a number of papers, which were not authored by LIS discipline researchers, in the LIS related journals. In addition, there are a few ongoing interdisciplinary research projects which included LIS researchers. This reveals that it is possible for the LIS field could play an important role in the future if the researchers actively participate the collaborative projects.

In this paper, we present a face and gesture based human computer interaction (HCI) system. We combine head pose and hand gesture to control the system. We can identify the positions of the eyes and mouth, and use the face center to estimate the pose of the head. Moreover, we introduce a technique for automatic gesture area segmentation and orientation normalization of the hand gesture. The user does not need to keep gestures in upright position and the system segments and normalizes the gestures automatically. The experimental results show that the proposed approach is accurate with gesture recognition rate of 93.6%. Also, the user can control multiple devices, including robots simultaneously through a wireless network.

In the field of Human-Computer Interaction design, persuasive design has gradually been applied to the system development and design process, especially for mobile application design. However, most mobile applications have hitherto a very short using lifecycle. Especially, design features with long-term persuasive effectiveness remain to be further researched and developed. In this study, we focused on investigating and identifying the durative persuasive design characteristics through a data mining process and evaluating the durative effectiveness through a long-term observation process. Total five hundred healthcare-related mobile applications were selected from Apple iTunes Store and a mixed method was conducted to extract the most common persuasive design characteristics. Based on the results of extraction, a representative healthcare-related mobile application was selected as experimental subject. Total one hundred and twenty participants were observed during a six-months experiment and the monitoring data of app usage of all participants was collected once a week. According to the evaluation model for behavior change identification process, participants with habit formation features were proved to have a significant long-term perception level for ten persuasive design characteristics. Further interview research was performed to investigate the participant’s long-term perceptions on those characteristics for the purpose of identifying the durative persuasions. The results indicated that a long-term durative effectiveness can be observed and healthcare-related apps designed with those characteristics could have durative effectiveness. This study may contribute to the improvement of future mobile application designs in user experience and durative persuasion, as well as bringing future benefits for both mobile application developers and users.

Human Computer Interaction (HCI) is a discipline dealing with the study, planning, and design of interactions between humans and computers. The prevalent use of digital devices is increasing the need for research and education on HCI. Paying a close attention to HCI is important as poorly designed user interfaces can lead to unexpected problems. This work is focused on a new education method geared towards reducing errors and exceptions while developing a program, incorporating role-changing brainstorming techniques during HCI design process. According to the proposed approach, two evaluation elements, including the ability to find errors and exceptions and the ability to present alternative solutions when faced with these errors, are considered. Through a role-changing brainstorming based design exploration, a low-fi prototype was developed to set up an assessment method incorporating quantitative and qualitative factors for a team-based HCI project.

Among the various hand gestures, pointing gesture is highly intuitive, and does not require any priori assumptions. A major problem for pointing gesture recognition is the difficulty of pointing fingertip tracking and the unreliability of the direction estimation. A novel real-time method is developed for pointing gesture recognition using Kinect based depth image and skeletal points tracking. An adaptive virtual touch screen is constructed instead of estimating pointing direction. When a user stands in a certain distance from a large screen to perform pointing behaviors, he interacts with the virtual touch screen as if it is just right in front of him. The proposed method is suitable for both large and small pointing gestures, and it’s not subject to users’ characteristics and environmental changes. Experiments have highlighted that the proposed approach is robust and efficient to realize human-computer interaction based on pointing gesture recognition by comparisons.

Human-computer interaction (HCI) has great interactive applications in many fields. A novel eye-hand coordination based HCI approach has been proposed. According to the fact that the eye gazing starts prior to the hand movement and reaches the target in advance, an eye-hand coordination model in a non-contact way is constructed by facial orientation and skeletal joints of hand. Both temporal median filtering and moving average filter strategies are developed to overcome some fluctuation influences during HCI. The diversity of interactive habits among multiple users is considered in an ordinary hardware from a crowded scene without any hypothesis for the scenario contents in advance. Comparative comparisons with state-of-the-arts have highlighted the superior performance of the proposed approach.

Human-computer interaction (HCI) has great potential for applications in many fields. A HCI method has been developed based on audio-visual perceptive features and dynamic interactive pooling. A mode analysis based fusion strategy is proposed to fuse the interactive responses from audio-visual modalities especially for the case there are deviations from the modalities at the same time. The developed approach can be applied with a better performance even in single modal with multiple interactive users in the scenario. The users in the scenario are endowed with a fair chance to perform HCI by their interactive priorities no matter how many modalities used, and the interactive authority and priority are updated dynamically according to the variation of HCI content. The scenario and multiple users altogether are regarded as a dynamic HCI pooling. The diversity of interactive habits among multiple users is considered in an ordinary hardware from a crowded scene without any hypothesis for the scenario contents in advance. The pooling is updated dynamically to meet the user demands with the most intentions preferentially. Comparative study with state-of-the-arts has indicated the superior performance of the proposed method.

This paper develops the Adaptive Multisensory Integration Framework (AMIF), explaining how artificial intelligence coordinates sensory modalities to enhance human-computer interaction. Synthesizing cognitive neuroscience, AI, and HCI theories, AMIF identifies five cyclically-operating components governing multisensory integration. Critical analysis reveals fundamental limitations in temporal prediction, computational efficiency, and individual variability. Four case studies demonstrate the framework's explanatory power, showing both successes and persistent challenges in real-world systems. The framework generates testable hypotheses and design principles grounded in theoretical understanding.

Aiming at solving problem of points’ redundancy caused by full automatically detecting points and the problem of large workload caused by picking all points manually, I advanced a new method of picking points which is based on Human-Computer Interaction in our 3D reconstruction platform after automatically detecting points. We first detected and matched points automatically and got the homograph matrix between two images, then projected points which were picked by hand on the one image to the other image, at last we would search the interesting feature points in the neighborhood of corresponding points in the two images. Experiments have shown that this method decreases the redundancy brought by large number of points and successfully finds the important feature points, so it lays a good foundation for 3D reconstruction.

In this paper, a real-time Human-Computer Interaction (HCI) based on the hand data glove and K-NN classifier for gesture recognition is proposed. HCI is moving more and more natural and intuitive way to be used. One of the important parts of our body is our hand which is most frequently used for the Interaction in Digital Environment and thus complexity and flexibility of motion of hands are the research topics. To recognize these hand gestures more accurately and successfully data glove is used. Here, gloves are used to capture current position of the hand and the angles between the joints and then these features are used to classify the gestures using K-NN classifier. The gestures classified are categorized as clicking, rotating, dragging, pointing and ideal position. Recognizing these gestures relevant actions are taken, such as air writing and 3D sketching by tracking the path helpful in virtual augmented reality (VAR). The results show that glove used for interaction is better than normal static keyboard and mouse as the interaction process is more accurate and natural in dynamic environment with no distance limitations. Also it enhances the user’s interaction and immersion feeling.

Through the application of theories and principles of human-computer interaction design system, deficiencies on interaction of digital music player are analyzed; and through the analysis on cognitive features for interaction, hierarchy of needs, and emotional information of target users, the key factors and the relevant data that influence the objective of interaction design are researched, thus facilitating the modern digital music products design to follow up users’ physical and mental requirements, balancing the interaction design between human, computer and environment, bringing users more convenient and effective operation and experience, and providing more important theoretical thought and implementation process for humanized design.

In the era of aging society in China, focusing on the issue that it is difficult for elderly people to operate a variety of computing devices with the physiological and psychological changes brought by the aging, a research for ergonomics of interactive devices was put forward for elderly user groups. The research studied the performance of elderly people using the mouse, stylus and touchscreen to perform two-dimensional pointing tasks, compared with younger people, in the computer user interface by controlled experiments, measured the movement time and hit accuracy, and also investigated the subjective experience when they used the three input devices for completing two-dimensional pointing tasks. Experimental data analysis showed that elderly people spend more time than younger people to complete the pointing tasks with any of the three input devices, Fitts' law still hold when the elderly people used mouse, stylus and touchscreen to perform the two-dimensional pointing tasks, and the use of touchscreen can achieve higher performance with the target size should not less than 80 pixels (about 11.2 mm) for both elderly and younger people. Elderly people can benefit more from the touchscreen than younger people.

이 연구에서 우리는 생성형 인공지능의 도입이 영화·영상 제작 분야에서 인간-컴퓨터 상호작용(HCI) 패러다임을 어떻게 변화시키고 있는지 분석하고, 이러한 변화가 제작 효율성에 어떤 영향을 미치는지를 검토한다. 전통적 영화·영상 제작은 시간, 비용, 기술 복잡성 등의 문제로 비효율성을 지니고 있었다. AI 도입 이전의 직접 조작(Direct Manipulation) 기반 HCI 패러다임은 정밀한 제어를 통해 높은 품질을 담보했지만, 전문 기술 습득의 어려움과 반복 작업으로 인한 한계를 보였다. 반면, 생성형 AI의 등장으로 협업적 창작(Co-Creation) 및 의도 기반 상호작용(Intent-Based Interaction)이라는 새로운 HCI 패러다임이 부상하고 있다. 우리는 문헌 연구와 사례 분석을 통해 AI 도입 전후의 HCI 패러다임 변화를 체계적으로 비교하고, 프리-프로덕션부터 프로덕션 및 포스트-프로덕션에 이르는 영화·영상 제작 전 과정에서 나타나는 제작 효율성 증진 양상을 살펴본다. 또한, 우리는 이러한 변화 이면에 존재하는 프롬프트 엔지니어링의 어려움, 결과물 통제 및 일관성 문제, 워크플로 통합 상의 장애, 법적·윤리적 이슈와 결정 마비(Decision Paralysis) 등 새로운 도전 과제를 논의한다. 이를 바탕으로 우리는 향후 생성형 AI 기반 영화·영상 제작 환경에서 HCI의 발전 방향과 효율성 제고를 위한 시사점을 제시한다.

In this study, we analyze how the introduction of Generative Artificial Intelligence (AI) is transforming Human-Computer Interaction (HCI) paradigms in film and video production and examine the impact of these changes on production efficiency. Traditional film and video production has long suffered from inefficiencies caused by time, cost, and technical complexity. Prior to the adoption of AI, the direct manipulation-based HCI paradigm ensured high-quality outcomes through precise control, but it was constrained by the difficulty of acquiring specialized technical skills and the repetitive nature of production tasks. With the emergence of Generative AI, new HCI paradigms such as co-creation and intent-based interaction have gained prominence. Through literature review and case analysis, we systematically compare HCI paradigms before and after AI adoption and explore improvements in production efficiency across the entire workflow - from pre-production to production and post-production. Furthermore, we discuss emerging challenges, including the difficulties of prompt engineering, issues of output control and consistency, obstacles in workflow integration, as well as legal, ethical, and decision paralysis concerns. Based on these findings, we provide implications for the future development of HCI and propose strategies to enhance efficiency in Generative AI-driven film and video production environments.