Search Results (1,903)

Over the last few decades, a growing number of studies have used wearable technologies, such as inertial and pressure sensors, to investigate various domains of music experience, from performance to education. In this paper, we systematically review this body of literature using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method. The initial search yielded a total of 359 records. After removing duplicates and screening for content, 23 records were deemed fully eligible for further analysis. Studies were grouped into four categories based on their main objective, namely performance-oriented systems, measuring physiological parameters, gesture recognition, and sensory mapping. The reviewed literature demonstrated the various ways in which wearable systems impact musical contexts, from the design of multi-sensory instruments to systems monitoring key learning parameters. Limitations also emerged, mostly related to the technology’s comfort and usability, and directions for future research in wearables and music are outlined. Full article

Ondol is a heating system unique to Korean homes that increases indoor temperatures by supplying hot water through pipes embedded in floor slabs. Known for its comfort and sustained heating advantages, ondol has garnered international interest in countries requiring efficient heating solutions. Given the inherent challenges faced during installation and operation, timely inspection of ondol is crucial due to difficulties in detecting and locating defects in buried concrete pipes, often leading to costly rework and removal. However, specialized inspection systems tailored to ondol pipes remain underexplored. Therefore, this paper proposes a robotic inspection system capable of assessing the conditions of ondol pipelines. We analyze the characteristics of ondol piping to establish system requirements and develop a prototype of a compact capsule-shaped inspection robot tailored for ondol pipe inspection. Subsequent laboratory testing validates system performance and usability, confirming field applications through curvature maneuverability and image reception quality tests. This study aims to motivate advancements in ondol-specific system implementation and performance validation, potentially contributing to the smartification of ondol maintenance practices. Full article

Mild cognitive impairment (MCI) is characterized by a modest decline in cognitive function that, while noticeable, does not severely impact daily life, allowing individuals to maintain their independence—a key factor distinguishing it from dementia. Currently, there are no treatments available that can modify the course of the disease, although cognitive and physical activities have shown potential in slowing its progression. In response to the need for more accessible cognitive care, COGNIVITRA, an information- and communications-technology-based solution, was developed to extend cognitive training into the home environment. This platform not only facilitates communication between patients and care providers but also holds promise for enhancing cognitive care accessibility and potentially influencing the economic aspects of healthcare institutions. To evaluate the usability, impact, and effectiveness of COGNIVITRA, a 12-week (6 mandatory + 6 voluntary) multicenter study was conducted, with an expected total sample size of 20 professionals, 90 patients and 20 caregivers and involving two settings (clinical and home settings) and the collection of various data types at baseline and after 6 or 12 weeks of training, including sociodemographic information, cognitive assessments, and usability metrics. These metrics included the System Usability Scale (SUS), the International Classification of Functioning-Based Usability Scales (ICF-US I and II), the Unified Theory of Acceptance and Use of Technology (UTAUT), health-related quality of life measures such as the EQ-5D-5L, cognitive domain assessments via the Montreal Cognitive Assessment (MoCA), and physical assessments such as the Timed 25-Foot Walk (T25-FW) test. The study included 22 patients, 2 caregivers, and 24 professionals. The usability evaluation revealed that patients, particularly those participating in the home study, showed improved SUS scores, suggesting an enhanced user experience with the platform. The ICF-US I results further supported this finding by indicating that COGNIVITRA was particularly effective as a supportive tool in terms of satisfaction and ease of learning. Despite a higher incidence of errors during the home study, the observational grid questionnaire demonstrated high success rates for task completion. Professionals involved in the study also reported high SUS scores and provided positive feedback regarding device usability. Overall, the participants expressed increased satisfaction with the platform, as reflected in their responses. The UTAUT analysis confirmed a generally positive attitude toward the use of COGNIVITRA. However, when assessing effectiveness, the analysis revealed a noninferiority positive trend in the EQ-5D-5L, T25-FW, and MoCA scores, indicating that while there were positive changes, they were not statistically significant. Full article

In recent years, the integration of Internet of Things technologies in smart agriculture has become critical for sustainability and efficiency, to the extent that recent improvements have transformed greenhouse farming. This study investigated the complexity of IoT architecture in smart greenhouses by introducing a greenhouse language family (GreenH) that comprises three domain-specific languages designed to address various tasks in this domain. The purpose of this research was to streamline the creation, simulation, and monitoring of digital twins, an essential tool for optimizing greenhouse operations. A three-stage methodology was employed to develop the GreenH DSLs, a detailed metamodel for enhanced smart monitoring systems. Our approach used high-level metamodels and extended Backus–Naur form notation to define the DSL syntax and semantics. Through a comprehensive evaluation strategy and a selected language usability metrics, the expressiveness, consistency, readability, correctness, and scalability of the DSL were affirmed, and areas for usability improvement were highlighted. The findings suggest that GreenH languages hold significant potential for advancing digital twin modeling in smart agriculture. Future work should be aimed at refining usability and extending its application range. The anticipated integration with additional model-drive engineering and code generation tools will improve interoperability and contribute to digital transformation in the smart greenhouse domain and promote more sustainable food production systems. Full article

The growing population of aging adults, coupled with the widespread adoption of technology, including within virtual environments, prompts the need to understand technology engagement preferences among older adults. This study aimed to explore the experiences and perceptions of older adults engaging with a client-centered immersive virtual reality (IVR) protocol tailored to their specific occupational interests. Employing a mixed methods approach, the research combined the quantitative System Usability Scale (SUS) assessment with qualitative interviews to examine the feasibility, usability, and learning experiences of community-dwelling older adults. Fifteen (n = 15) older adult participants trialed an IVR session tailored to match their chosen occupations of importance. Findings revealed that the usability of IVR varied significantly among participants, with an average SUS score of 55, indicating a need for further investigation into usability issues. Qualitative analysis identified three themes: IVR is usable when it is intuitive and with training, balance the apps for success, and overall lasting impressions were related to the perceived implementation for the participant. The incorporation of meaningful occupations in IVR programming is feasible and can be integrated into healthy aging-in-place programming; however, expanding available leisure-based apps and increasing the learning time before engagement should be considered. Full article

Musculoskeletal Disorders (MSDs) stand as a prominent cause of injuries in modern agriculture. Scientific research has highlighted a causal link between MSDs and awkward working postures. Several methods for the evaluation of working postures, and related risks, have been developed such as the Rapid Upper Limb Assessment (RULA). Nevertheless, these methods are generally applied with manual measurements on pictures or videos. As a consequence, their applicability could be scarce, and their effectiveness could be limited. The use of wearable sensors to collect kinetic data could facilitate the use of these methods for risk assessment. Nevertheless, the existing system may not be usable in the agricultural and vine sectors because of its cost, robustness and versatility to the various anthropometric characteristics of workers. The aim of this study was to develop a technology capable of collecting accurate data about uncomfortable postures and repetitive movements typical of vine workers. Specific objectives of the project were the development of a low-cost, robust, and wearable device, which could measure data about wrist angles and workers’ hand positions during possible viticultural operations. Furthermore, the project was meant to test its use to evaluate incongruous postures and repetitive movements of workers’ hand positions during pruning operations in vineyard. The developed sensor had 3-axis accelerometers and a gyroscope, and it could monitor the positions of the hand–wrist–forearm musculoskeletal system when moving. When such a sensor was applied to the study of a real case, such as the pruning of a vines, it permitted the evaluation of a simulated sequence of pruning and the quantification of the levels of risk induced by this type of agricultural activity. Full article

This study aims to design an environmental management information system (EMIS) by integrating all necessary environmental documents for project implementation based on ISO 14001:2015 and using an exploratory sequential mixed method of research. The agile project management methodology was also used to speculate how a project must be managed using environmental information. The problems with the current operation in compliance with ISO 14001:2015 were addressed using EMIS with the participation of IT professionals. The end-users assessed the functionality, efficiency, compatibility, usability, reliability, security, maintainability, and portability of EMIS. A computer system is required for EMIS for accurate and effective document storage and updates. EMIS can be developed based on coding and simulation to make it simpler to save, retrieve, and update documents. EMIS needs to have functionality, efficiency, compatibility, usability, reliability, security, maintainability, and portability. Full article

This study introduces a system for visually impaired individuals in a walking environment. It combines object recognition using YOLOv5 and cautionary sentence generation with KoAlpaca. The system employs image data augmentation for diverse training data and GPT for natural language training. Furthermore, the implementation of the system on a single board was followed by a comprehensive comparative analysis with existing studies. Moreover, a pilot test involving visually impaired and healthy individuals was conducted to validate the system’s practical applicability and adaptability in real-world walking environments. Our pilot test results indicated an average usability score of 4.05. Participants expressed some dissatisfaction with the notification conveying time and online implementation, but they highly praised the system’s object detection range and accuracy. The experiments demonstrated that using QLoRA enables more efficient training of larger models, which is associated with improved model performance. Our study makes a significant contribution to the literature because the proposed system enables real-time monitoring of various environmental conditions and objects in pedestrian environments using AI. Full article

This article aims to assess the usability of selected map portals with a checklist. The methods employed allowed the author to conduct user experience tests from a longer temporal perspective against a retrospective analysis of the evolution of design techniques for presenting spatial data online. The author performed user experience tests on three versions of Tomice Municipality’s geoportal available on the Internet. The desktop and mobile laboratory tests were performed by fourteen experts following a test scenario. The study employs the exploratory approach, inspection method, and System Usability Scale (SUS). The author calculated the Geoportal Overall Quality (GOQ) index to better illustrate the relationships among the subjective perceptions of the usability quality of the three geoportals. The usability results were juxtaposed with performance measurements. Normalised and aggregated results of user experience demonstrated that the expert assessments of the usability of geoportals G1 and G3 on mobile devices were similar despite significant development differences. The overall results under the employed research design have confirmed that geoportal G2 offers the lowest usability in both mobile and desktop modes. The study has demonstrated that some websites can retain usability even considering the dynamic advances in hardware and software despite their design, which is perceived as outdated today. Users still expect well-performing and quick map applications, even if this means limited functionality and usability. Moreover, the results indirectly show that the past resolution of the ‘large raster problem’ led to the aggravation of the issue of ‘large scripts’. Full article

Water quality and usability are global concerns due to microbial and chemical pollution resulting from anthropogenic activities. Therefore, strategies for eliminating contaminants are required. In this context, the removal and decrease in antibiotic activity (AA) associated with levofloxacin (LEV), using TiO₂ and Ag/TiO₂ catalysts, with and without sunlight and peroxydisulfate, was evaluated. Additionally, the disinfection capacity of catalytic systems was assessed. The catalysts were synthesized and characterized. Moreover, the effect of Ag doping on visible light absorption was determined. Then, the photocatalytic treatment of LEV in water was performed. The materials characterization and EPR analyses revealed that LEV degradation and AA decrease were ascribed to a combined action of solar light, sulfate radical, and photocatalytic activity of the TiO₂-based materials. Also, the primary byproducts were elucidated using theoretical analyses (predictions about moieties on LEV more susceptible to being attacked by the degrading species) and experimental techniques (LC-MS), which evidenced transformations on the piperazyl ring, carboxylic acid, and cyclic ether on LEV. Moreover, the AA decrease was linked to the antibiotic transformations. In addition, the combined system (i.e., light/catalyst/peroxydisulfate) was shown to be effective for E. coli inactivation, indicating the versatility of this system for decontamination and disinfection. Full article

Numerous studies have explored the integration of technology-enhanced feedback systems in education. However, there is still a need for further investigation into their specific impact on teacher satisfaction, which is essential for effective feedback delivery to students. This study addresses this gap by analyzing teachers’ satisfaction with the “Compliments and Comments Tool”, a technology-enhanced system developed to provide written feedback to students. Using a quantitative approach, this study examined teachers’ perceptions of the tool’s usability in the Slovenian education context, involving a diverse group of 3412 primary and secondary school teachers. Data were collected through surveys employing the System Usability Scale (SUS) and Technology Acceptance Model (TAM) for quantitative analysis, complemented by qualitative insights. The results showed high teacher satisfaction, valuing the tool for facilitating feedback and supporting a positive learning environment. These findings suggest that the “Compliments and Comments Tool” is a valuable addition to educational technology, promoting effective teaching and enhancing student engagement. This study emphasizes the critical role of user-centered design and system usability in educational technology, particularly in fostering effective feedback and promoting student self-regulation. Full article

Stroke is the main cause of disability among adults. Decision-making in stroke rehabilitation is increasingly complex; therefore, the use of decision support systems by healthcare providers is becoming a necessity. However, there is a significant lack of software for the management of post-stroke telerehabilitation (TR). This paper presents the results of the developed software “TeleRehab” to support the decision-making of clinicians and healthcare providers in post-stroke TR. We designed a Python-based software with a graphical user interface to manage post-stroke TR. We searched Scopus, ScienceDirect, and PubMed databases to obtain research papers with results of clinical trials for post-stroke TR and to form the knowledge base of the software. The findings show that TeleRehab suggests recommendations for TR to provide practitioners with optimal and real-time support. We observed feasible outcomes of the software based on synthetic data of patients with balance problems, spatial neglect, and upper and lower extremities dysfunctions. Also, the software demonstrated excellent usability and acceptability scores among healthcare professionals. Full article

This study presents a framework for enabling autonomous pick–place operations, addressing the need for efficiency in complex logistics environments using a direct multi-target teaching interface. First, tag and segmentation information were combined to recognize products in a complex warehouse, and a camera was installed on the rack to allow workers to remotely see the work environment, allowing workers to view the work environment in real time through a tablet. Workers can access the camera view showing the rack containing the target product through a swiping action and select the target product through direct teaching action. When the target product is finally selected, an optimal path is created through task planning, and an autonomous pick–place operation is performed based on the generated path. As a result of conducting a usability evaluation using the SUS (System Usability Scale) with six users on the interface that enables these tasks, it was confirmed that high user satisfaction was achieved with an average of 77.5 points. In conclusion, the proposed interface enhances operational efficiency and provides a user-friendly solution for complex warehouse tasks. Full article

Nowadays, portrait drawing has gained significance in cultivating painting skills and human sentiments. In practice, novices often struggle with this art form without proper guidance from professionals, since they lack understanding of the proportions and structures of facial features. To solve this limitation, we have developed a Portrait Drawing Learning Assistant System (PDLAS) to assist novices in learning portrait drawing. The PDLAS provides auxiliary lines as references for facial features that are extracted by applying OpenPose and OpenCV libraries to a face photo image of the target. A learner can draw a portrait on an iPad using drawing software where the auxiliary lines appear on a different layer to the portrait. However, in the current implementation, the PDLAS does not offer a function to assess the exactness of the drawing result for feedback to the learner. In this paper, we present a drawing exactness assessment method using a Localized Normalized Cross-Correlation (NCC) algorithm in the PDLAS. NCC gives a similarity score between the original face photo and drawing result images by calculating the correlation of the brightness distributions. For precise feedback, the method calculates the NCC for each face component by extracting the bounding box. In addition, in this paper, we improve the auxiliary lines for the nose. For evaluations, we asked students at Okayama University, Japan, to draw portraits using the PDLAS, and applied the proposed method to their drawing results, where the application results validated the effectiveness by suggesting improvements in drawing components. The system usability was also confirmed through a questionnaire with a SUS score. The main finding of this research is that the implementation of the NCC algorithm within the PDLAS significantly enhances the accuracy of novice portrait drawings by providing detailed feedback on specific facial features, proving the system’s efficacy in art education and training. Full article

Decades of research have shown that magnetocardiography (MCG) has the potential to improve cardiac care decisions. However, sensor and system limitations have prevented its widespread adoption in clinical practice. We report an MCG system built around an array of scalar, optically pumped magnetometers (OPMs) that effectively rejects ambient magnetic interference without magnetic shielding. We successfully used this system, in conjunction with custom hardware and noise rejection algorithms, to record magneto-cardiograms and functional magnetic field maps from 30 volunteers in a regular downtown office environment. This demonstrates the technical feasibility of deploying our device architecture at the point-of-care, a key step in making MCG usable in real-world settings. Full article