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Abstract: Abstract Despite recent progress, hand gesture recognition, a highly regarded method of human computer interaction, still faces considerable challenges. In this paper, we address the problem of individual user style variation, which can significantly affect system performance. While previous work only supports the manual inclusion of customized hand gestures in the context of very specific application settings, here, an effective, adaptable graphical interface, supporting user-defined hand gestures is introduced. In our system, hand gestures are personalized by training a camera-based hand gesture recognition model for a particular user, using data just from that user. We employ a lightweight Multilayer Perceptron architecture based on contrastive learning, reducing the size of the data needed and the training timeframes compared to previous recognition models that require massive training datasets. Experimental results demonstrate rapid convergence and satisfactory accuracy of the recognition model, while a user study collects and analyses some initial user feedback on the system in deployment. PubDate: 2024-08-02
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Abstract: Abstract The characteristics of people who have never used the internet (non-adopters) and policy remedies have been well researched in scholarship on the digital divide. However, little is known about un-adopters, people who once used the internet but no longer do. Based on data obtained from the third and fourth follow-up surveys (2016 and 2018) of the China Family Panel Studies, this study reveals that China’s internet un-adopters are largely similar to non-adopters. However, place of residence and gender are non-significant predictors of internet discontinuation. It is suggested that conventional user-side digital divide programs targeting non-adopters, such as lowering costs, increasing awareness, and improving digital literacy, are still effective and should be extended to cover internet un-adopters. PubDate: 2024-08-01
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Abstract: Abstract China is transitioning into a moderate aging society and a significant portion of the elderly population faces difficulties in indoor transferring. This study was conducted in December 2022 with the aim of constructing personas for a specific population. This was achieved by filtering target data from the latest current data in the CHARLS database and performing hierarchical cluster analysis on 12 variables across 119 samples. The results showed that the elderly individuals with indoor transferring difficulties can be divided into 7 clusters, which were then refined to form 7 data-driven personas. The cluster characteristics were used to determine the design direction for mobility aid, including functional features and corresponding interactive solutions for the physical needs of the elderly individuals with indoor transferring difficulties. PubDate: 2024-07-28
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Abstract: Abstract This study addresses the challenge of improving communication between the deaf and hearing community by exploring different sign language recognition (SLR) techniques. Due to privacy issues and the need for validation by interpreters, creating large-scale sign language (SL) datasets can be difficult. The authors address this by presenting a new Spanish isolated sign language recognition dataset, CALSE-1000, consisting of 5000 videos representing 1000 glosses, with various signers and scenarios. The study also proposes using different computer vision techniques, such as face swapping and affine transformations, to augment the SL dataset and improve the accuracy of the model I3D trained using them. The results show that the inclusion of these augmentations during training leads to an improvement in accuracy in top-1 metrics by up to 11.7 points, top-5 by up to 8.8 points and top-10 by up to 9 points. This has great potential to improve the state of the art in other datasets and other models. Furthermore, the analysis confirms the importance of facial expressions in the model by testing with a facial omission dataset and shows how face swapping can be used to include new anonymous signers without the costly and time-consuming process of recording. PubDate: 2024-07-24
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Abstract: Autism Spectrum Disorder (ASD) involves difficulties in communication, expression, and social interaction, making it challenging for individuals to respond and engage effectively in various social contexts. This study used AR and MR (A/MR) technologies for social skills training in children with ASD. Previous applications of A/MR technology in teaching have lacked an explicit teaching framework and learning structure, resulting in confusion among learners and eventual abandonment of learning. To address these issues, the study combined concept mapping with A/MR technology to develop visualized and structured teaching materials and game strategies to aid children with autism in understanding and organizing abstract social concepts into a systematic mind map. Two game strategies, CMAR-ST and CMMR-ST, were implemented to enable children with autism to gradually strengthen and construct their cognition of social relationships and situations. Through situational guidance and in-game tasks, the children were empowered to make social judgments and exhibit appropriate reciprocal social responses when interacting with others. The present study recruited three high-functioning children with autism aged seven to nine as the research participants. A multiple-baseline across-subject design was employed for the teaching interventions. After three stages of experimentation, the results demonstrated that the teaching materials presented through CMAR-ST and CMMR-ST effectively enhanced the social concepts of children with autism. The game strategies helped the participants understand the relationships between different social information and cues, enabling them to effectively discern others' emotions, comprehend specific social gestures, and respond appropriately based on different social contexts with various individuals. PubDate: 2024-07-20
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Abstract: Abstract The internet is a drug information resource for consumers because of its ease of use and convenience; however, accessibility for individuals with visual impairment is often not considered. Previous studies have found that pharmaceutical websites did not meet accessibility standards. This study builds on previous research by evaluating the accessibility of prescription ocular drug product websites using two accessibility checkers. Twenty ocular medications were initially selected and 11 medications were included in the final analysis because a product website was available. AChecker and WAVE tools were used to evaluate accessibility of each drug product homepage then a screen reader was used to verify accessibility of the websites. Descriptive statistics were used to represent the errors and problems identified by the accessibility checkers. All websites had varying number of errors and problems based on the WAVE and AChecker tools. Travatan Z® had the highest number of errors (n = 117) according to WAVE and Durysta™ had the highest number of problems (n = 42) based on the AChecker tool. Some of the common issues identified by the screen reader included lack of alternative text for images (e.g., graphs), no description for links, and drop-down menus do not expand using the keyboard functions. This study highlights the need for manufacturers to improve accessibility of their product websites. Due to the lack of accessible content on these websites, it is prudent for pharmacists and other healthcare professionals to provide education through verbal counseling and auditory resources or recordings of drug information as an alternative format. PubDate: 2024-07-16
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Abstract: Abstract Sustainable design principles have become increasingly important in website development, mainly focusing on reducing carbon emissions and energy consumption. Easy language (EL) is a simplified language variety that makes websites more accessible to a wider range of users; but there has been no attention given to its usefulness in sustainability efforts. As such, this study is intended to become a starting point for future research in the area. By examining the intersection between EL and website sustainability guidelines and practices, the study highlights the potential for EL to contribute to sustainable website design. Along the paper, the following theory is defended: when adapted to Easy Language, text and interactions in websites are simplified, which makes them require less data transfer, become more efficient and, ultimately, more sustainable. The paper also presents a small comparative analysis of the sustainability of websites in EL and standard language that indicated that EL generally enhanced the sustainability of websites. The nine websites in EL analysed showed a mean reduction of CO2 production of 42% in comparison to their equivalents in standard language (p = 0.049, F = 2.42). The discussion and results presented open potential solutions for an urgent problem that deserve to be considered and researched further. PubDate: 2024-07-11
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Abstract: Abstract Augmentative and alternative communication (AAC) methods aim to enable a variety of interactions and participation for those with complex communication needs. AAC’s benefits are well known. However, many with these unique needs do not have access to these technologies, do not use them to their full potential, or abandon the system for a variety of reasons. Novel approaches are needed to enable AAC’s availability, accessibility, and independent communication opportunities. Creating novel, functional AAC systems requires understanding the diversity of known barriers. Furthermore, collaboration between technology developers and those stakeholders who can see the problems is crucial. Therefore, this study aims to establish a connection between speech-language pathologists (SLPs) and technology developers by implementing the International Classification of Functioning, Disability and Health (ICF) Framework to evaluate the existing barriers and assess which aspects of functional ability are affected when using a novel textile-based AAC technology (TAAC) perceived by SLPs. To this end, we organized an online survey and focus group discussions for 12 SLPs experienced in implementing AAC. Meaningful concepts were extracted and linked to the ICF framework in a deductive, qualitative research design. The results revealed a broad range of factors that affect one’s functional abilities in the areas of communication, learning and applying knowledge, using the TAAC, and motivation when the TAAC is individually designed to meet the requirements of ease and appropriate content. The results of this analysis provide the platform for implementing the ICF into the AAC technology design, offering a common platform for collaboration between AAC experts and technology developers. PubDate: 2024-06-28
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Abstract: Abstract Researchers and practitioners have been seeking the active participation of persons with disabilities (PwD) in participatory design (PD) to assign a “sensitive value” to their assistive technologies (ATs). However, there is a huge gap between the intention of engagement and effective user empowerment in PD. Considering the importance of PwD’s motivation in PD to influence the extent of his/her empowerment, this study analyzes two case studies in which accommodations to PD practices, provided by PD4CAT, were intended to promote the effective participation of people with cerebral palsy in the development of their customized computational ATs—ommunicators. The cases were developed with two persons with cerebral palsy, their therapists, caregivers, developers and researchers. This paper intends to answer the research question “How do accommodations to PD practices provided by PD4CAT affect the motivation and empowerment of participants with cerebral palsy in the case studies under analysis'” The main objective of this research is to analyze the motivation and empowerment of cerebral palsy co-designers in PD practices in the two case studies. This analysis was carried out in a qualitative approach in light of the self-determination theory and levels of empowerment opportunity. Our results show that the proposed accommodations promoted self-motivation and effective participation of the two cerebral palsy co-designers in designing their communicators. Also, recommendations were proposed based on the findings of this research. We hope that these results help create design opportunities that include PwD in PD practices to design their customized ATs. PubDate: 2024-06-22
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Abstract: Abstract Generative AI needs to collect massive information including personal information to train the model and improve the accuracy of answers. This may incur privacy risks and reduce user disclosure intention. Based on the elaboration likelihood model (ELM), this research explored generative AI user disclosure intention. The results revealed that disclosure intention receives a dual influence from both central factors (perceived anthropomorphism, perceived accuracy and perceived affordance) and peripheral factors (privacy statement, social influence and privacy risk). Algorithm literacy acts as a significant moderation variable of this dual-path model. The fsQCA identified three configurations leading to disclosure intention. These results imply that generative AI platforms need to improve content quality and reduce privacy risk in order to promote user disclosure intention. PubDate: 2024-06-20
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Abstract: Abstract Since the introduction of the electronic Personal Health Record (ePHR) in Germany in 2021, usage rates among those with statutory health insurance have remained below 1%. The patient-administered conception of the ePHR presents access barriers, particularly for older adults. This study aimed to evaluate an e-learning platform as an empowerment tool for ePHR usage, tailored toward older adults. In this explorative study, a micro-learning-based prototype platform for effective utilization of the ePHR was evaluated through both an online (n = 53) and a face-to-face (n = 6) intervention. The usability of the e-learning platform was measured using the System Usability Scale (SUS) and user experience with the User Experience Questionnaire (UEQ). The mean rating in the SUS was 67.9 in the online group and 70.4 in the face-to-face group. For participants of the online group, only the perspicuity subscale of the UEQ was rated above average compared to the benchmark. There was a strong positive correlation between usability and the perception of how learning content was presented, as measured by the eHealth Impact Questionnaire, in the online group (p = < 0.001, r(40) = 0.72). An investigation of the face-to-face group helped identify key usability challenges. The results of our study suggest that aspects of the target group-oriented design of the learning platform, in particular, still need to be improved. The insights gleaned from this study will contribute to the ongoing development of the learning platform in subsequent phases. Future studies will investigate the platform’s effectiveness in empowering older adults. Trial Registration The study was registered in the German Clinical Trials Register (registration number: DRKS00029700) and received approval from the Ethics Committee of the Charité - Universitätsmedizin Berlin (application number: EA1/081/22). PubDate: 2024-06-14 DOI: 10.1007/s10209-024-01124-z
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Abstract: Abstract When performing decision-making tasks, individuals commonly use the user interface (UI) of a decision aid repeatedly. Conversational user interfaces (CUIs) and graphical user interfaces (GUIs) can both be applied for decision aids. Compared with GUIs, CUIs require less learning effort and are able to provide more natural and engaging user experience. However, CUIs cannot replace entire existing GUIs of decision aids because of the characteristics of decision-making tasks and individual rational decision processes. This research investigates the effect of rational decision style when individuals use different UIs of decision aids repeatedly. We conduct a between- and within-subject lab experiment to compare the differences between task completion time and user perception of the UIs, which presents interesting results. CUIs do not always surpass GUIs, which have merits in repeated use and particularly benefit decision-makers having a high rationality score. The results suggest when designing UIs for decision aids, the frequency of use and individual rational decision style need to be considered. This research contributes by analyzing the effect of rational decision style on user perception, and comparing the task completion time when individuals use CUI or GUI to perform decision-making tasks repeatedly. PubDate: 2024-06-13 DOI: 10.1007/s10209-024-01122-1
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Abstract: Abstract Recognizing multiple residents’ activities is a pivotal domain within active and assisted living technologies, where the diversity of actions in a multi-occupant home poses a challenge due to their uneven distribution. Frequent activities contrast with those occurring sporadically, necessitating adept handling of class imbalance to ensure the integrity of activity recognition systems based on raw sensor data. While deep learning has proven its merit in identifying activities for solitary residents within balanced datasets, its application to multi-resident scenarios requires careful consideration. This study provides a comprehensive survey on the issue of class imbalance and explores the efficacy of Long Short-Term Memory and Bidirectional Long Short-Term Memory networks in discerning activities of multiple residents, considering both individual and aggregate labeling of actions. Through rigorous experimentation with data-level and algorithmic strategies to address class imbalances, this research scrutinizes the explicability of deep learning models, enhancing their transparency and reliability. Performance metrics are drawn from a series of evaluations on three distinct, highly imbalanced smart home datasets, offering insights into the models’ behavior and contributing to the advancement of trustworthy multi-resident activity recognition systems. PubDate: 2024-06-13 DOI: 10.1007/s10209-024-01123-0
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Abstract: Abstract Nowadays, social network game platforms have gathered a large number of young players. This study adopted a technological–personal–environmental framework to explain the continued usage intention and related influential factors for two major player groups (novice and expert game players) of social network games. Two models include 13 influential factors, which affected the players’ continued usage intention, were proposed. The questionnaire method (in total, 817 valid questionnaires) was adopted for testing the models. The results showed many differences between the two groups (novice and expert players) in many aspects. Particularly, technostress was not found to positively affect or change the intention to continue playing social network games for both the novice and the expert players. Generally, the research results provide useful inspiration and contributions to the development of social network games. PubDate: 2024-06-12 DOI: 10.1007/s10209-024-01126-x
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Abstract: Abstract Many universities around the world were forced to lock down and students had to continue their learning in online environments in response to the COVID-19 pandemic. Teachers thus had to adopt effective and appropriate online teaching pedagogy integrated with related educational technologies to help their students achieve satisfactory learning outcomes in these courses. In addition, the world-wide problems of high failure level and dropout rates in programming courses challenge both teachers and students. Aiming to develop students’ practical programming skills, commitment to learning, and reduce learning disengagement, the researchers behind this study adopted two teaching approaches, integrating online partial pair programming (PPP) and socially shared metacognitive regulation (SSMR), to explore their effects on students’ learning performance in an online programming course. A quasi-experiment was implemented to explore the effects of online PPP and SSMR. The participants comprised three classes of students, all from non-information or non-computer departments taking a compulsory course titled ‘Programming Design’. The experimental groups included the first class (G1) simultaneously receiving the online PPP and SSMR intervention and the second class (G2) receiving only the online SSMR intervention. The third class (G3) received a traditional teaching method (non-PPP and non-SSMR) delivered online and served as the control group. Both quantitative and qualitative data were collected and analyzed. Experimental results show that the SSMR group (G2) demonstrated significantly better development of programming skills and commitment to learning than the control group (G3). However, the expected effects of online PPP on improving students’ learning were not found. The implications of designing pedagogies with PPP and SSMR in an online programming course for decision-makers in governments and universities, researchers, and teachers implementing online courses, particularly programming courses, are provided and discussed. PubDate: 2024-06-09 DOI: 10.1007/s10209-024-01127-w
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Abstract: Abstract Currently, an increasing number of elderly people are choosing to live in elderly care communities, where they have access to smart health services. Despite the availability of these services, the utilization rate among the elderly remains low, resulting in the elderly not fully experiencing the benefits of this advanced technology. To ensure more elderly people to receive these benefits, this study constructed a model of the mechanisms affecting the use of smart health services by elderly people in retirement communities based on the TAM theory and collected data through questionnaires. A total of 1,292 valid questionnaires were collected from 8 retirement communities in several cities in China, and the data were analyzed by PLS-SEM. This study finds that different types of trust differ in how they influence the elderly’s perception of smart health services; perceived ease of use cannot directly affect the elderly’s willingness to adopt smart health services but should be achieved through the influence of health expectations; various types of social support play an important role in the elderly’s perceived usability of smart health services; and perceived usefulness plays an important role in the adoption of smart health services. In addition, through a multi-cohort comparative analysis, this study found differences in gender, age, income, and education in the adoption of health services by the elderly. The findings support the advancement and implementation of smart healthcare services among the elderly. PubDate: 2024-06-07 DOI: 10.1007/s10209-024-01125-y
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Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
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Abstract: Abstract This article offers a description and discussion of minority features in visual art audio description (AD). For this purpose, a qualitative analysis of a multilingual corpus of visual art ADs and their context of creation and implementation was carried out, drawing on Langacker’s (Cognitive grammar: a basic introduction, Oxford University Press, Oxford, 2008) and its further development by Croft and Cruse (Cognitive linguistics, Cambridge University Press, Cambridge, 2004). The results show that some ADs in the corpus conceptualize the artwork as a process, moving from a static to a dynamic description, utilize an internal and subjective viewpoint that places the describer and users in the space of the work, or shift the focus of attention to the subjective sensations elicited by the work. These minority features could facilitate users' multisensory experience of the work and enhance their understanding of contextual information. This could benefit blind and partially blind people, as well as other visitors to art museums and exhibitions. PubDate: 2024-06-01 DOI: 10.1007/s10209-023-01003-z
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