Multimodal Technol. Interact., Volume 7, Issue 10 (October 2023) – 8 articles

This research pursues the question of how the computer-generated analysis and visualization of communication can foster collaboration in teams that work together online. The audio data of regular online video meetings of three different teams were analyzed. Structural information regarding their communication was visualized in a communication report, and then, discussed with the teams in so-called digitally supported coaching (DSC) sessions. The aim of the DSC is to improve team collaboration by discerning helpful and less helpful patterns in the teams’ communication. This report allows us to recognize individual positions within the teams, as well as communication structures, such as conversational turn taking, that are relevant for group intelligence, as other research has shown. The findings pertaining to the team members during the DSC were gathered via questionnaires. These qualitative data were then matched with the quantitative data derived from the calls, particularly social network analysis (SNA). The SNA was inferred using the average number of interactions between the participants as measured in the calls. The qualitative findings of the teams were then cross-checked with the quantitative analysis. As a result, the assessment of team members’ roles was highly coherent with the SNA. Furthermore, all teams managed to derive concrete measures for improving their collaboration based on the reflection in the DSC. Full article

In this paper, we report a method of implementing a universal volumetric haptic actuation platform which can be adapted to fit a wide variety of visual displays with flat surfaces. This platform aims to enable the simulation of the 3D features of input interfaces. This goal is achieved using four readily available stepper motors in a diagonal cross configuration with which we can quickly change the position of a surface in a manner that can render these volumetric features. In our research, we use a Microsoft Surface Go tablet placed on the haptic enhancement actuation platform to replicate the exploratory features of virtual keyboard keycaps displayed on the touchscreen. We ask seven participants to explore the surface of a virtual keypad comprised of 12 keycaps. As a second task, random key positions are announced one at a time, which the participant is expected to locate. These experiments are used to understand how and with what fidelity the volumetric feedback could improve performance (detection time, track length, and error rate) of detecting the specific keycaps location with haptic feedback and in the absence of visual feedback. Participants complete the tasks with great success (p < 0.05). In addition, their ability to feel convex keycaps is confirmed within the subjective comments. Full article

Immersive Unit Visualization is an emergent form of visualization that arose from Immersive Analytics where, unlike traditional visualizations, each data point is represented by an individual visual mark in an immersive virtual environment. This practice has focused almost exclusively on virtual reality, excluding augmented reality (AR). This article develops and tests a prototype of an Immersive Unit Visualization (Floating Companies II) with two AR devices: head-mounted display (HMD) and hand-held display (HHD). Results from the testing sessions with 20 users were analyzed through qualitative research analysis and thematic coding indicating that, while the HHD enabled a first contact with AR visualization on a familiar device, HMD improved the perception of hybrid space by supporting greater stability of virtual content, wider field of view, improved spatial perception, increased sense of immersion, and more realistic simulation, which had an impact on information reading and sense-making. The materialization of abstract quantitative values into concrete reality through its simulation in the real environment and the ludic dimension stand out as important opportunities for this type of visualization. This paper investigates the aspects distinguishing two experiences regarding data visualization in hybrid space, and characterizes ways of seeing information with AR, identifying opportunities to advance information design research. Full article

Sign language (SL) avatar systems aid communication between the hearing and deaf communities. Despite technological progress, there is a lack of a standardized avatar development framework. This paper offers a systematic review of SL avatar systems spanning from 1982 to 2022. Using PRISMA guidelines, we shortlisted 47 papers from an initial 1765, focusing on sign synthesis techniques, corpora, design strategies, and facial expression methods. We also discuss both objective and subjective evaluation methodologies. Our findings highlight key trends and suggest new research avenues for improving SL avatars. Full article

Immersive journalism is a new form of media communication that uses extended reality systems to produce its content. Despite the possibilities it offers, its use is still limited in the media due to the lack of systematised and scientific knowledge regarding its application. This is a problem because it is a very powerful technology that changes the way audiences receive information and can be used both for new forms of storytelling that generate greater user engagement and for very sophisticated disinformation, which is why it is really important to study it. This study analyses articles published in the last 5 years that cover the use of extended technologies and the metaverse applied to immersive journalism. A systematic literature review applying PRISMA was carried out to identify literature within Web of Science, Scopus and Google Scholar (n = 61). Quantitative and qualitative analyses were conducted on the data collection techniques, the type of the data and the analysis techniques used. The results show a low level of methodological maturity, with research that is fundamentally descriptive and not very formalised, which limits the scope of its results and, therefore, the transfer of knowledge for its application in the configuration of new immersive journalistic products. The metaverse and extended technologies are considered independently and with distinct applications. It is concluded that research in this area is still in an initial exploratory and generalist stage that offers results that are not yet applicable to the promotion of this type of media format. Full article

The field of brain–computer interface (BCI) enables us to establish a pathway between the human brain and computers, with applications in the medical and nonmedical field. Brain computer interfaces can have a significant impact on the way humans interact with machines. In recent years, the surge in computational power has enabled deep learning algorithms to act as a robust avenue for leveraging BCIs. This paper provides an up-to-date review of deep and hybrid deep learning techniques utilized in the field of BCI through motor imagery. It delves into the adoption of deep learning techniques, including convolutional neural networks (CNNs), autoencoders (AEs), and recurrent structures such as long short-term memory (LSTM) networks. Moreover, hybrid approaches, such as combining CNNs with LSTMs or AEs and other techniques, are reviewed for their potential to enhance classification performance. Finally, we address challenges within motor imagery BCIs and highlight further research directions in this emerging field. Full article

Public warning systems are an essential element of safe cities. However, the functionality of neither traditional nor digital emergency warnings is understood well enough from the perspective of citizens. This study examines smart city development from the perspective of safety by exploring citizens’ viewpoints. It investigates people’s perceptions of the ways in which they obtain warnings and information about emergencies involving health risks. Data were collected in the form of focus group interviews and semi-structured interviews in Finland, Germany, and Greece. The results suggest that people place a lot of trust in their social network, receiving text messages, and their ability to use web-based search engines in order to obtain public warnings. The study discusses the challenges identified by citizens in the use of conventional radio and television transmissions and sirens for public warnings. Based on the results, citizens demonstrate informed ignorance about existing mobile emergency applications. Our results imply that it is not sufficient to build emergency communication infrastructure: the development of smart, safe cities requires continuous work and the integration of both hard and soft infrastructure-oriented strategies, i.e., technological infrastructure development including digitalisation and education, advancement of knowledge, and participation of people. Both strategic aspects are essential to enable people to take advantage of novel digital applications in emergency situations. Full article

Relational cues are extracts from actual verbal dialogues that help build the therapist–patient working alliance and stronger bond through the depiction of empathy, respect and openness. ECAs (Embodied conversational agents) are human-like virtual agents that exhibit verbal and non-verbal behaviours. In the digital health space, ECAs act as health coaches or experts. ECA dialogues have previously been designed to include relational cues to motivate patients to change their current behaviours and encourage adherence to a treatment plan. However, there is little understanding of who finds specific relational cues delivered by an ECA helpful or not. Drawing the literature together, we have categorised relational cues into empowering, working alliance, affirmative and social dialogue. In this study, we have embedded the dialogue of Alex, an ECA, to encourage healthy behaviours with all the relational cues (empathic Alex) or with none of the relational cues (neutral Alex). A total of 206 participants were randomly assigned to interact with either empathic or neutral Alex and were also asked to rate the helpfulness of selected relational cues. We explore if the perceived helpfulness of the relational cues is a good predictor of users’ intention to change the recommended health behaviours and/or development of a working alliance. Our models also investigate the impact of individual factors, including gender, age, culture and personality traits of the users. The idea is to establish whether a certain group of individuals having similarities in terms of individual factors found a particular cue or group of cues helpful. This will establish future versions of Alex and allow Alex to tailor its dialogue to specific groups, as well as help in building ECAs with multiple personalities and roles. Full article