Current Issue : April-June Volume : 2025 Issue Number : 2 Articles : 5 Articles
Amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig's disease and gradual freezing disease, is a rare disease. At present, it mainly relies on drug therapy and supportive therapy, but the therapeutic effect is not significant. With the progress of medical technology and computer science, brain-computer interface technology, also known as BCI, has been developed in recent years. Previous studies have shown that BCI can be used to help patients with dyskinesia recover and assist patients with brain injury to recover after operation. With further research, the central nervous system signal is transformed into the external environment’s instruction. For patients with ALS and AD, it is possible to communicate with the outside world through BCI technology. This paper mainly discusses the application in the treatment of ALS to realize barrier-free communication between ALS patients and the outside world. This paper mainly introduces ALS, brain-computer interface technology, and case analysis and explores the application of brain-computer interface technology in the treatment of amyotrophic lateral sclerosis. The conclusion is that this treatment method is obviously superior to the traditional method, but it has not been widely popularized and needs further study....
Background/Objectives: Studies on the application and exploration of human–computer interaction (HCI) technologies within the healthcare sector have rapidly expanded, showcasing the immense potential of HCI to enhance medical services, elevate patient experiences, and advance health management. Despite this proliferating interest, there is a notable shortage of comprehensive bibliometric analyses dedicated to the application of HCI in healthcare, which limits a thorough comprehension of the growth trends and future trajectories in this area. Methods: To bridge this gap, we employed bibliometric methods using the CiteSpace tool to systematically review and analyze the current state and trends of HCI research in healthcare. A meticulous topic search ofWeb of Science yielded 3598 papers published between 2004 and 2023. Results: Through literature analysis, the most productive researchers, institutes, and countries/territories and the collaboration networks among authors and countries within the field were analyzed. Additionally, by conducting a cocitation analysis, journals and literature with high citation rates and influence within the academic community in this field were revealed. Through a cluster analysis based on literature co-citations and keyword burst analyses, we further explored the main research themes and hot topics within the fields of healthcare and HCI. Conclusions: In summary, through a comprehensive and systematic bibliometric analysis, this study provides a solid knowledge foundation for HCI in the healthcare research community, thereby fostering the development of innovative research and the optimization of practical applications in the field....
In the evolving field of human–computer interaction (HCI), gesture recognition has emerged as a critical focus, with smart gloves equipped with sensors playing one of the most important roles. Despite the significance of dynamic gesture recognition, most research on data gloves has concentrated on static gestures, with only a small percentage addressing dynamic gestures or both. This study explores the development of a low-cost smart glove prototype designed to capture and classify dynamic hand gestures for game control and presents a prototype of data gloves equipped with five flex sensors, five force sensors, and one inertial measurement unit (IMU) sensor. To classify dynamic gestures, we developed a neural network-based classifier, utilizing a convolutional neural network (CNN) with three two-dimensional convolutional layers and rectified linear unit (ReLU) activation where its accuracy was 90%. The developed glove effectively captures dynamic gestures for game control, achieving high classification accuracy, precision, and recall, as evidenced by the confusion matrix and training metrics. Despite limitations in the number of gestures and participants, the solution offers a cost-effective and accurate approach to gesture recognition, with potential applications in VR/AR environments....
Traditional rigid electronic materials for brain-computer interface cannot work stably and will cause rejection reactions and inflammation of the brain. In response, scientists have tried new strategies to develop flexible bioelectronic materials that can stably recognize and control neural activity in the tissue interface environment to monitor and modulate brain function, and meet desired level of effect to provide safe treatment to neural and muscle diseases such as Hence, in this comprehensive review, the paramount significance of optimal electronic materials tailored for Brain-Computer Interface (BCI) applications is underscored. The virtues of biocompatible materials are highlighted, delving into their fabrication methodologies, distinctive material attributes, and deployment in secure therapeutic interventions for a spectrum of neurological disorders including paralysis, dementia, and depression. Current investigations in this domain are presented, outlining the pivotal evaluation criteria for these materials. Recent advancements are introduced and synthesized, considering the prevailing influential factors that shape the field's trajectory. Additionally, the review acknowledges lingering hurdles and outlines prospective avenues for future exploration, ensuring a holistic perspective. Ultimately, the entire discourse culminates in a synthesis that validates the substantial applicability and potential of soft bioelectronic materials within the realm of interfacing computer science with biology, heralding a promising future in neurotechnology....
Human-Computer Interaction has evolved from command-line, then to graphical, up to a tangible user interface (TUI). TUIs represent a new paradigm in incorporating physical objects within the digital environment in order to offer users richer, more natural, and intuitive interaction means. This paper reviews the applications of TUIs within cognitive ergonomics, education, and industry, with special emphasis on the potential effects that TUI might have in reducing cognitive load and improving retention and enhancing problem-solving behavior. It covers various case studies on cognitive benefits at TUI, frameworks of distributed and embodied cognition, scalability and accessibility issues, ways to reduce technical obstacles along with users' reluctance, and how TUI is being merged with IoT. The authors also discuss how TUI will see huge improvements in terms of networking and control in intelligent environments. From the above, though TUIs promise great benefits related to the conventional GUIs, full utilization in different applications calls for addressing cost, adaptability, and inclusivity for wide usage....
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