Optimizing The Design Of Multimodal User Interfaces

Due to a current lack of principle-driven multimodal user interface design guidelines, designers may encounter difficulties when choosing the most appropriate display modality for given users or specific tasks (e.g., verbal versus spatial tasks). The development of multimodal display guidelines from both a user and task domain perspective is thus critical to the achievement of successful human-system interaction. Specifically, there is a need to determine how to design task information presentation (e.g., via which modalities) to capitalize on an individual operator\u27s information processing capabilities and the inherent efficiencies associated with redundant sensory information, thereby alleviating information overload. The present effort addresses this issue by proposing a theoretical framework (Architecture for Multi-Modal Optimization, AMMO) from which multimodal display design guidelines and adaptive automation strategies may be derived. The foundation of the proposed framework is based on extending, at a functional working memory (WM) level, existing information processing theories and models with the latest findings in cognitive psychology, neuroscience, and other allied sciences. The utility of AMMO lies in its ability to provide designers with strategies for directing system design, as well as dynamic adaptation strategies (i.e., multimodal mitigation strategies) in support of real-time operations. In an effort to validate specific components of AMMO, a subset of AMMO-derived multimodal design guidelines was evaluated with a simulated weapons control system multitasking environment. The results of this study demonstrated significant performance improvements in user response time and accuracy when multimodal display cues were used (i.e., auditory and tactile, individually and in combination) to augment the visual display of information, thereby distributing human information processing resources across multiple sensory and WM resources. These results provide initial empirical support for validation of the overall AMMO model and a sub-set of the principle-driven multimodal design guidelines derived from it. The empirically-validated multimodal design guidelines may be applicable to a wide range of information-intensive computer-based multitasking environments

Continuous Interaction with a Virtual Human

Attentive Speaking and Active Listening require that a Virtual Human be capable of simultaneous perception/interpretation and production of communicative behavior. A Virtual Human should be able to signal its attitude and attention while it is listening to its interaction partner, and be able to attend to its interaction partner while it is speaking – and modify its communicative behavior on-the-fly based on what it perceives from its partner. This report presents the results of a four week summer project that was part of eNTERFACE’10. The project resulted in progress on several aspects of continuous interaction such as scheduling and interrupting multimodal behavior, automatic classification of listener responses, generation of response eliciting behavior, and models for appropriate reactions to listener responses. A pilot user study was conducted with ten participants. In addition, the project yielded a number of deliverables that are released for public access

Spotting Agreement and Disagreement: A Survey of Nonverbal Audiovisual Cues and Tools

While detecting and interpreting temporal patterns of non–verbal behavioral cues in a given context is a natural and often unconscious process for humans, it remains a rather difficult task for computer systems. Nevertheless, it is an important one to achieve if the goal is to realise a naturalistic communication between humans and machines. Machines that are able to sense social attitudes like agreement and disagreement and respond to them in a meaningful way are likely to be welcomed by users due to the more natural, efficient and human–centered interaction they are bound to experience. This paper surveys the nonverbal cues that could be present during agreement and disagreement behavioural displays and lists a number of tools that could be useful in detecting them, as well as a few publicly available databases that could be used to train these tools for analysis of spontaneous, audiovisual instances of agreement and disagreement

Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

Today's mobile phones are far from mere communication devices they were ten years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.Comment: 29 pages, 5 figure

Archiving and Delivery of 3DTI Rehabilitation Sessions

In this paper we present CyPhy: a cyber-physiotherapy system that brings daily rehabilitation to patient’s home with supervision from trained therapist. With its archiving and delivery features, CyPhy is able to 1) capture and record RGB-D and physiotherapy-related medical sensing data streams in home environment; 2) provide efficient storage for rehabilitation session recordings; 3) provide fast metadata analysis over stored sessions for review recommendation; 4) adaptively deliver rehabilitation session under different networking capabilities; 5) support smooth viewpoint changing during 3D video streaming with scene rendering schemes tailored for devices with different bandwidth and power limitations; and 6) provide platform-independent streaming client for various mobile and PC environments

Multimodal information presentation for high-load human computer interaction

This dissertation addresses the question: given an application and an interaction context, how can interfaces present information to users in a way that improves the quality of interaction (e.g. a better user performance, a lower cognitive demand and a greater user satisfaction)? Information presentation is critical to the quality of interaction because it guides, constrains and even determines cognitive behavior. A good presentation is particularly desired in high-load human computer interactions, such as when users are under time pressure, stress, or are multi-tasking. Under a high mental workload, users may not have the spared cognitive capacity to cope with the unnecessary workload induced by a bad presentation. In this dissertation work, the major presentation factor of interest is modality. We have conducted theoretical studies in the cognitive psychology domain, in order to understand the role of presentation modality in different stages of human information processing. Based on the theoretical guidance, we have conducted a series of user studies investigating the effect of information presentation (modality and other factors) in several high-load task settings. The two task domains are crisis management and driving. Using crisis scenario, we investigated how to presentation information to facilitate time-limited visual search and time-limited decision making. In the driving domain, we investigated how to present highly-urgent danger warnings and how to present informative cues that help drivers manage their attention between multiple tasks. The outcomes of this dissertation work have useful implications to the design of cognitively-compatible user interfaces, and are not limited to high-load applications

Diverse Contributions to Implicit Human-Computer Interaction

Cuando las personas interactúan con los ordenadores, hay mucha información que no se proporciona a propósito. Mediante el estudio de estas interacciones implícitas es posible entender qué características de la interfaz de usuario son beneficiosas (o no), derivando así en implicaciones para el diseño de futuros sistemas interactivos. La principal ventaja de aprovechar datos implícitos del usuario en aplicaciones informáticas es que cualquier interacción con el sistema puede contribuir a mejorar su utilidad. Además, dichos datos eliminan el coste de tener que interrumpir al usuario para que envíe información explícitamente sobre un tema que en principio no tiene por qué guardar relación con la intención de utilizar el sistema. Por el contrario, en ocasiones las interacciones implícitas no proporcionan datos claros y concretos. Por ello, hay que prestar especial atención a la manera de gestionar esta fuente de información. El propósito de esta investigación es doble: 1) aplicar una nueva visión tanto al diseño como al desarrollo de aplicaciones que puedan reaccionar consecuentemente a las interacciones implícitas del usuario, y 2) proporcionar una serie de metodologías para la evaluación de dichos sistemas interactivos. Cinco escenarios sirven para ilustrar la viabilidad y la adecuación del marco de trabajo de la tesis. Resultados empíricos con usuarios reales demuestran que aprovechar la interacción implícita es un medio tanto adecuado como conveniente para mejorar de múltiples maneras los sistemas interactivos.Leiva Torres, LA. (2012). Diverse Contributions to Implicit Human-Computer Interaction [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/17803Palanci

Age-Related Differences in Multimodal Information Processing and Their Implications for Adaptive Display Design.

In many data-rich, safety-critical environments, such as driving and aviation, multimodal displays (i.e., displays that present information in visual, auditory, and tactile form) are employed to support operators in dividing their attention across numerous tasks and sources of information. However, limitations of this approach are not well understood. Specifically, most research on the effectiveness of multimodal interfaces has examined the processing of only two concurrent signals in different modalities, primarily in vision and hearing. Also, nearly all studies to date have involved young participants only. The goals of this dissertation were therefore to (1) determine the extent to which people can notice and process three unrelated concurrent signals in vision, hearing and touch, (2) examine how well aging modulates this ability, and (3) develop countermeasures to overcome observed performance limitations. Adults aged 65+ years were of particular interest because they represent the fastest growing segment of the U.S. population, are known to suffer from various declines in sensory abilities, and experience difficulties with divided attention. Response times and incorrect response rates to singles, pairs, and triplets of visual, auditory, and tactile stimuli were significantly higher for older adults, compared to younger participants. In particular, elderly participants often failed to notice the tactile signal when all three cues were combined. They also frequently falsely reported the presence of a visual cue when presented with a combination of auditory and tactile cues. These performance breakdowns were observed both in the absence and presence of a concurrent visual/manual (driving) task. Also, performance on the driving task suffered the most for older adult participants and with the combined visual-auditory-tactile stimulation. Introducing a half-second delay between two stimuli significantly increased response accuracy for older adults. This work adds to the knowledge base in multimodal information processing, the perceptual and attentional abilities and limitations of the elderly, and adaptive display design. From an applied perspective, these results can inform the design of multimodal displays and enable aging drivers to cope with increasingly data-rich in-vehicle technologies. The findings are expected to generalize and thus contribute to improved overall public safety in a wide range of complex environments.PhDIndustrial and Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133203/1/bjpitts_1.pd

Kind mobile notifications for healthcare professionals

[EN] The inclusion of the Internet of Things in healthcare is producing numerous automatic notifications for health professionals. These notifications must be delivered in the right moment and in the right way to be appropriately attended, and at the same time, ensuring no important task is interrupted. In this work, we have applied a human-centred design method to deal with this issue. By collaborating with health professionals in Belgium, we have designed and validated DELICATE, a conceptual framework that categorizes the different attention needs for each notification, and links them with the delivery mechanisms that are more appropriate for each particular context. As an aid for designers, we also define methodological guidelines to clearly determine how DELICATE can be used to develop a notification system. Finally, as a proof-of-concept validation of the framework, we have implemented it in an Android application and tested it using real scenarios. This validation has shown that DELICATE can be used to design a notification system that delivers kind healthcare notifications.The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: Pedro Valderas's work has been developed with the financial support of the Spanish State Research Agency under the project TIN2017-84094-R and co-financed with ERDF. Estefania Serral and Jan Derboven's work has been supported by IMEC funding.Serral, E.; Valderas, P.; Derboven, J. (2020). Kind mobile notifications for healthcare professionals. Health Informatics Journal. 26(3):1516-1537. https://doi.org/10.1177/1460458219884184S15161537263Sasangohar, F., Donmez, B., Trbovich, P., & Easty, A. C. (2012). Not All Interruptions are Created Equal: Positive Interruptions in Healthcare. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 56(1), 824-828. doi:10.1177/1071181312561172McFarlane DC. Interruption of people in human-computer interaction: a general unifying definition of human interruption and taxonomy. Technical report, Office of Naval Research, Arlington VA, 31 December 1997.Ross, D. T., & Schoman, K. E. (1977). Structured Analysis for Requirements Definition. IEEE Transactions on Software Engineering, SE-3(1), 6-15. doi:10.1109/tse.1977.229899Gulliksen, J., Göransson, B., Boivie, I., Blomkvist, S., Persson, J., & Cajander, Å. (2003). Key principles for user-centred systems design. Behaviour & Information Technology, 22(6), 397-409. doi:10.1080/01449290310001624329Beyer, H. R., & Holtzblatt, K. (1995). Apprenticing with the customer. Communications of the ACM, 38(5), 45-52. doi:10.1145/203356.203365Christel, M. G., & Kang, K. C. (1992). Issues in Requirements Elicitation. doi:10.21236/ada25893