Both research and development of accessible websites are attempts at improving the quality of life of people with disabilities. Some of them focus on aligning with the Web Content Accessibility Guidelines (WCAG). Poor...
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Both research and development of accessible websites are attempts at improving the quality of life of people with disabilities. Some of them focus on aligning with the Web Content Accessibility Guidelines (WCAG). Poor quality of content on some websites may cause rejection from users with disabilities, and the development and testing processes to ensure accessibility are often complex. This paper presents the actual experience of implementing an adaptation of SCRUM that assists in constructing and testing accessible websites continuously in the software life cycle, controlling usability and accessibility errors in a timely manner. This approach is innovative because it fosters implementation and testing of accessibility in software more quickly and with greater flexibility. Two use cases are presented, namely "Information System of Costa Rica on the Disability" (SICID, by its acronym in Spanish) and National Board of the Blind (PANACI, by its acronym in Spanish).
Thoracoabdominal Asynchrony (TAA) is a key metric in respiration monitoring, which characterizes the non-parallel periodical motion of human's rib cage (RC) and abdomen (AB) during each breath. Long-term measureme...
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Thoracoabdominal Asynchrony (TAA) is a key metric in respiration monitoring, which characterizes the non-parallel periodical motion of human's rib cage (RC) and abdomen (AB) during each breath. Long-term measurement of TAA plays a significant role in respiration health tracking. Existing TAA measurement methods including Respiratory Inductive Plethysmography (RIP) and Optoelectronic Plethysmography (OEP) all intrusive to subjects and have certain requirements on operation conditions, which limit their usage to hospital scenario. To address this gap, we propose mmTAA, the first mmWave-based, non-intrusive TAA measurement system ready for ubiquitous usage in daily-life. In mmTAA, we design a Two-stage RC-AB centroid finding module, aiming to identify the most probable location of RC-AB centroid, which can best represent RC and AB in mmWave sensing scenario. Subsequently, we design TAANet, a novel Convolutional Neural Network (CNN)-based architecture with residual modules, tailored for TAA measurement. Meanwhile, in order to address the imbalance of continuous data, we add imbalance information equalizer including feature and label equalizer during network training. We implement mmTAA on a commonly used multi-antenna mmWave radar. We prototype, deploy and evaluate mmTAA on 25 subjects and 25.7h data in total. mmTAA achieves 4.01 degrees MAE and 1.56 degrees average error, close to OEP method.
Social media web sites thrive on user engagement by employing Attention Capture Damaging Patterns (ACDPs), e.g., infinite scroll, that prey on cognitive vulnerabilities to distract users. Prior work has taxonomized th...
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Social media web sites thrive on user engagement by employing Attention Capture Damaging Patterns (ACDPs), e.g., infinite scroll, that prey on cognitive vulnerabilities to distract users. Prior work has taxonomized these ACDPs, but we have yet to measure how the presence of ACDPs impacts perceived distraction nor how mechanisms that suppress ACDPs reduce distraction. We conducted a 2-week, mixed-methods field study with 29 participants to model how people get distracted when browsing social media web sites and how ACDPs might play a role. In the first week of the study, we sample participants' in situ perceptions of distraction, subjective perceptions of the browsing session (e.g., satisfaction), and the presence/absence of ACDPs. Participants reported feeling distracted 28% of the time and that subjective perceptions and some ACDPs (e.g., notifications) highly correlated with when they felt distracted. In the second week of the study, participants were given access to Purpose Mode-a browser extension that allows users to "toggle off" ACDPs. Participants reported feeling distracted only 7% of the time and spent 21 fewer daily minutes browsing these web sites. We discovered that Purpose Mode empowered users to feel more in control over their social media browsing and made participants feel less irritated and frustrated.
Mental Workload (MWL) is a construct widely used in HCI to assess the cognitive demand users must exert to perform a task. Research in human factors, however, has suggested several issues regarding its definitions, sc...
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Mental Workload (MWL) is a construct widely used in HCI to assess the cognitive demand users must exert to perform a task. Research in human factors, however, has suggested several issues regarding its definitions, scales, and applications. This paper, first, introduces debates surrounding the MWL concept and its most popular measure, the NASA-TLX. We present a systematic review of CHI papers involving MWL and highlight severe issues in its application. Finally, through a validation experiment, we assess the convergent validity and sensitivity of two MWL instruments-NASA-TLX and MRQ. Our findings reveal disagreements in the definitions of MWL and severe drawbacks in NASA-TLX and its applications. Our validation study also presents evidence for a lack of convergent validity and sensitivity of MWL subjective scales in HCI tasks. Our findings recommend caution when employing NASA-TLX in user studies and highlight the need for an MWL definition that is agreed upon within the HCI community.
Sensor-based human activity recognition (HAR) has been an active research area for many years, resulting in practical applications in smart environments, assisted living, fitness, healthcare, and more. Recently, deep-...
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Sensor-based human activity recognition (HAR) has been an active research area for many years, resulting in practical applications in smart environments, assisted living, fitness, healthcare, and more. Recently, deep-learning-based end-to-end training has pushed the state-of-the-art performance in domains such as computer vision and natural language, where large amounts of annotated data are available. However, large quantities of annotated data are typically not available for sensor-based HAR. Moreover, the real-world settings on which HAR is performed differ in terms of sensor modalities, classification tasks, and target users. To address this problem, transfer learning has been explored extensively. In this survey, we focus on these transfer learning methods in the application domains of smart home and wearables-based HAR. In particular, we provide a problem-solution perspective by categorizing and presenting the works in terms of their contributions and the challenges they address. We present an overview of the state of the art for both application domains. Based on our analysis of 246 papers, we highlight the gaps in the literature and provide a roadmap for addressing these. This survey provides a reference to the HAR community by summarizing the existing works and providing a promising research agenda.
Internet of Things (IoT) devices have become increasingly important within the smart home domain, making the security of the devices a critical aspect. The majority of IoT devices are black-box systems running closed ...
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Internet of Things (IoT) devices have become increasingly important within the smart home domain, making the security of the devices a critical aspect. The majority of IoT devices are black-box systems running closed and pre-installed firmware. This raises concerns about the trustworthiness of these devices, especially considering that some of them are shipped with a microphone or a camera. Remote attestation aims at validating the trustworthiness of these devices by verifying the integrity of the software. However, users cannot validate whether the attestation has actually taken place and has not been manipulated by an attacker, raising the need for HCI research on trust and understandability. We conducted a qualitative study with 35 participants, investigating trust in the attestation process and whether this trust can be improved by additional explanations in the application. We developed an application that allows users to attest a smart speaker using their smartphone over an audio channel to identify the attested device and observe the attestation process. In order to observe the differences between the applications with and without explanations, we performed A/B testing. We discovered that trust increases when additional explanations of the technical process are provided, improving the understanding of the attestation process.
Three-dimensional (3D) shape generation techniques leveraging deep learning have garnered significant interest from both computer vision and architectural design communities, promising to enrich the content in the vir...
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Three-dimensional (3D) shape generation techniques leveraging deep learning have garnered significant interest from both computer vision and architectural design communities, promising to enrich the content in the virtual environment. However, research on virtual architectural design remains limited, particularly regarding designer-AI collaboration and deep learning-assisted design. In our survey, we reviewed 149 related articles (81.2% of articles published between 2019 and 2023) covering architectural design, 3D shape techniques, and virtual environments. Through scrutinizing the literature, we first identify the principles of virtual architecture and illuminate its current production challenges, including datasets, multimodality, design intuition, and generative frameworks. We then introduce the latest approaches to designing and generating virtual buildings leveraging 3D shape generation and summarize four characteristics of various approaches to virtual architecture. Based on our analysis, we expound on four research agendas, including agency, communication, user consideration, and integrating tools. Additionally, we highlight four important enablers of ubiquitous interaction with immersive systems in deep learning-assisted architectural generation. Our work contributes to fostering understanding between designers and deep learning techniques, broadening access to designer-AI collaboration. We advocate for interdisciplinary efforts to address this timely research topic, facilitating content designing and generation in the virtual environment.
Fact-checking has emerged as a principal part of news reporting with over 400 fact-checking organisations worldwide. However, fewer than one in ten individuals report having used a fact-checking service. In this paper...
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Fact-checking has emerged as a principal part of news reporting with over 400 fact-checking organisations worldwide. However, fewer than one in ten individuals report having used a fact-checking service. In this paper, we introduce Google Inject: a technology-mediated nudge that integrates, relevant to one's query, fact-checks, into the Google search results page. We report on a laboratory study that inquired into how four design variables, in particular, the number of fact-checking articles injected, their positioning, concealment and seamlessness affect users' experience and proximal behaviours with Google Inject. All in all, the paper highlights the complexity and importance of nudge design, as seemingly subtle variations in the design and implementation of a nudge can have a profound impact on its effectiveness.
humans encounter a vast array of sensory stimuli in their everyday lives. However, many visualization techniques primarily utilize visual feedback, which may disregard certain intricate details. Relying on a single vi...
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humans encounter a vast array of sensory stimuli in their everyday lives. However, many visualization techniques primarily utilize visual feedback, which may disregard certain intricate details. Relying on a single visual channel may overlook complex layouts. However, how haptic force feedback can be used to assist visualization remained under-explored. In this work, we initially conducted a literature review to identify potential problems in the visualization of large datasets and engaged in discussions with domain experts to explore the potential of haptic force feedback and visual collision representation. Subsequently, we designed an innovative haptic force feedback knob, which included 3 primary modules and 29 elements. To evaluate the clarity and usefulness of this design space, we conducted a workshop and devised "recommended solutions" for the identified visualization problems. Finally, we implemented a prototype of the haptic force feedback knob and assessed its performance on scatterplot and parallel coordinate plot tasks using large datasets. The results indicated that the knob prototype could reduce visual strain and enhance the efficiency of visualization tasks.
With the global expansion of the Internet and the World Wide Web, users are becoming increasingly diverse, including their language proficiencies. In particular, there is now a significant number of polyglot Web users...
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With the global expansion of the Internet and the World Wide Web, users are becoming increasingly diverse, including their language proficiencies. In particular, there is now a significant number of polyglot Web users, i.e., users who are proficient in more than one language. However, even such users with potential access to a broad range of information from multiple languages often continue to suffer from unbalanced and fragmented news information, as traditional news access systems seldom allow users to simultaneously search for and/or compare news in different languages. To overcome language barriers, the majority of research has focused primarily on improving retrieval and translation accuracy, while paying comparably less attention to multilingual user interaction aspects. In particular, relatively little human-centered research has been conducted to better understand and support multilingual user abilities and preferences, and even less so regarding news search and different access modalities (such as desktop and mobile interfaces). The research presented in this article provides the first comparative analyses of polyglot users' preferences and behaviors with respect to different multilingual news search interfaces on both desktop and mobile platforms. Specifically, through a set of task-based user studies in laboratory experiments, the key contribution of this article is the presentation of the first human-centered studies in multilingual news search result interfaces, aiming to drive the development of human-centered multilingual news access systems for both desktop and mobile platforms. This contribution includes a detailed analysis of different interface design paradigms, as well as a series of implications for design.
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