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BACKGROUND: Improving arm-hand skill performance is a major therapeutic target in stroke rehabilitation. Arm-hand rehabilitation may be enriched in content and variation by using technology-assisted training. Especially for people with a severely affected arm, technology-assisted training offers more challenging training possibilities. OBJECTIVE: The aim of this study was to explore the feasibility of ReHab-TOAT, a “Remote Handling Based Task-Oriented Arm Training” approach featuring enriched haptic feedback aimed at improving daily activities and participation. METHODS: Five subacute or chronic stroke patients suffering moderate to severe arm-hand impairments and five rehabilitation therapists participated. All participants received 2 ReHab-TOAT sessions. Outcome measure was a bespoke feasibility questionnaire on user experiences and satisfaction regarding ‘motivation’, ‘individualization of training’, ‘potential training effects’, and ‘implementation in rehabilitation’ of patients and therapists. RESULTS: Both patients and therapists experienced ReHab-TOAT as being feasible. They found ReHab-TOAT very motivating and challenging. All patients perceived an added value of ReHab-TOAT and would continue the training. Small improvements regarding exercise variability were suggested. CONCLUSION: ReHab-TOAT seems to be a feasible and very promising training approach for arm-hand rehabilitation of stroke patients with a moderately or severely affected arm. Further research is necessary to investigate potential training effects of ReHab-TOAT.

Background Although disease-specific exercise guidelines for cardiovascular disease (CVD) are widely available, it remains uncertain whether these different exercise guidelines are integrated properly for patients with different CVDs. The aim of this study was to assess the inter-clinician variance in exercise prescription for patients with various CVDs and to compare these prescriptions with recommendations from the EXercise Prescription in Everyday practice and Rehabilitative Training (EXPERT) tool, a digital decision support system for integrated state-of-the-art exercise prescription in CVD. Design The study was a prospective observational survey. Methods Fifty-three CV rehabilitation clinicians from nine European countries were asked to prescribe exercise intensity (based on percentage of peak heart rate (HRpeak)), frequency, session duration, programme duration and exercise type (endurance or strength training) for the same five patients. Exercise prescriptions were compared between clinicians, and relationships with clinician characteristics were studied. In addition, these exercise prescriptions were compared with recommendations from the EXPERT tool. Results A large inter-clinician variance was found for prescribed exercise intensity (median (interquartile range (IQR)): 83 (13) % of HRpeak), frequency (median (IQR): 4 (2) days/week), session duration (median (IQR): 45 (18) min/session), programme duration (median (IQR): 12 (18) weeks), total exercise volume (median (IQR): 1215 (1961) peak-effort training hours) and prescription of strength training exercises (prescribed in 78% of all cases). Moreover, clinicians’ exercise prescriptions were significantly different from those of the EXPERT tool ( p Conclusions This study reveals significant inter-clinician variance in exercise prescription for patients with different CVDs and disagreement with an integrated state-of-the-art system for exercise prescription, justifying the need for standardization efforts regarding integrated exercise prescription in CV rehabilitation.

Over-the-top (OTT) streaming services like YouTube and Netflix induce massive amounts of video data, hereby putting substantial pressure on network infrastructure. This paper describes a demonstration of the object-based video (OBV) methodology that allows for the quality-variant MPEG-DASH streaming of respectively the background and foreground object(s) of a video scene. The OBV methodology is inspired by research into human visual attention and foveated compression, in that it allows to adaptively and dynamically assign bitrate to those portions of the visual scene that have the highest utility in terms of perceptual quality. Using a content corpus of interview-like video footage, the described demonstration proves the OBV methodology's potential to downsize video bitrate requirements while incurring at most marginal perceptual impact (i.e., in terms of subjective video quality). Thanks to its standards-compliant Web implementation, the OBV methodology is directly and broadly deployable without requiring capital expenditure.

Over-the-top (OTT) streaming services like YouTube and Netflix induce massive amounts of video traffic. To combat the resulting network load, this article empirically explores the use of the object-based video (OBV) methodology that allows for the quality-variant HTTP Adaptive Streaming of respectively the background and foreground object(s) of a video scene. In particular, we study two alternative video object representation methods where the first meticulously follows the object contour, while the second uses axis-aligned bounding box enclosures. We subjectively compare both techniques to traditional, frame-based video compression in the context of live action content featuring talking persons. The resulting mixed methods data shows that (i) OBV-informed users tolerate substantial background quality degradations, and (ii) at an average bitrate reduction of 14 percent, perceptual differences between respectively contour-based OBV and traditional encoding are small or even non-existing for the non-movie content in our corpus. Although our evaluation focuses on interview-like footage, our qualitative data hints that the presented results might be extrapolatable to other video genres. As such, our findings inform content owners and network operators about video bitrate saving opportunities with marginal perceptual impact.

Keeping track of design processes is a cumbersome task due to the apparently unconstrained and unstructured nature of creative work. Traceability is fundamental to revisit and reflect on the design narratives that describe artefact evolution. In this paper, we aim to identify what characteristics are necessary to facilitate traceability of creative design processes. For this end, we use a functional prototype to connect artefacts, design rationale, and decisions in a shared workspace. We evaluated this prototype for 15 weeks with six pairs of students engaged in a user-centered design project. Our findings show that having a lean repository of artefacts annotated with design rationale can facilitate tracking progress in different phases of the process. We found that creating a record of the participants' design work is useful to reflect on and for team agreement, ensure consistency of evolving artefacts, and help in planning future steps in the design project.

Whereas exercise training is key in the management of patients with cardiovascular disease (CVD) risk (obesity, diabetes, dyslipidaemia, hypertension), clinicians experience difficulties in how to optimally prescribe exercise in patients with different CVD risk factors. Therefore, a consensus statement for state-of-the-art exercise prescription in patients with combinations of CVD risk factors as integrated into a digital training and decision support system (the EXercise Prescription in Everyday practice & Rehabilitative Training (EXPERT) tool) needed to be established. EXPERT working group members systematically reviewed the literature for meta-analyses, systematic reviews and/or clinical studies addressing exercise prescriptions in specific CVD risk factors and formulated exercise recommendations (exercise training intensity, frequency, volume and type, session and programme duration) and exercise safety precautions, for obesity, arterial hypertension, type 1 and 2 diabetes, and dyslipidaemia. The impact of physical fitness, CVD risk altering medications and adverse events during exercise testing was further taken into account to fine-tune this exercise prescription. An algorithm, supported by the interactive EXPERT tool, was developed by Hasselt University based on these data. Specific exercise recommendations were formulated with the aim to decrease adipose tissue mass, improve glycaemic control and blood lipid profile, and lower blood pressure. The impact of medications to improve CVD risk, adverse events during exercise testing and physical fitness was also taken into account. Simulations were made of how the EXPERT tool provides exercise prescriptions according to the variables provided. In this paper, state-of-the-art exercise prescription to patients with combinations of CVD risk factors is formulated, and it is shown how the EXPERT tool may assist clinicians. This contributes to an appropriately tailored exercise regimen for every CVD risk patient. ispartof: SPORTS MEDICINE vol:48 issue:8 pages:1781-1797 ispartof: location:New Zealand status: published

Background Exercise rehabilitation is highly recommended by current guidelines on prevention of cardiovascular disease, but its implementation is still poor. Many clinicians experience difficulties in prescribing exercise in the presence of different concomitant cardiovascular diseases and risk factors within the same patient. It was aimed to develop a digital training and decision support system for exercise prescription in cardiovascular disease patients in clinical practice: the European Association of Preventive Cardiology Exercise Prescription in Everyday Practice and Rehabilitative Training (EXPERT) tool. Methods EXPERT working group members were requested to define (a) diagnostic criteria for specific cardiovascular diseases, cardiovascular disease risk factors, and other chronic non-cardiovascular conditions, (b) primary goals of exercise intervention, (c) disease-specific prescription of exercise training (intensity, frequency, volume, type, session and programme duration), and (d) exercise training safety advices. The impact of exercise tolerance, common cardiovascular medications and adverse events during exercise testing were further taken into account for optimized exercise prescription. Results Exercise training recommendations and safety advices were formulated for 10 cardiovascular diseases, five cardiovascular disease risk factors (type 1 and 2 diabetes, obesity, hypertension, hypercholesterolaemia), and three common chronic non-cardiovascular conditions (lung and renal failure and sarcopaenia), but also accounted for baseline exercise tolerance, common cardiovascular medications and occurrence of adverse events during exercise testing. An algorithm, supported by an interactive tool, was constructed based on these data. This training and decision support system automatically provides an exercise prescription according to the variables provided. Conclusion This digital training and decision support system may contribute in overcoming barriers in exercise implementation in common cardiovascular diseases. The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: The realisation of the proof of concept of the EXPERT tool was supported by a UHasselt Industrial Research Fund (IOF) proof of concept (PoC) project.

In this paper, we set out to find what encompasses an appropriate visual language for information presented on near-eye out-of-focus displays. These displays are positioned in a user's peripheral view, very near to the user's eyes, for example on the inside of the temples of a pair of glasses. We explored the usable display area, the role of spatial and retinal variables, and the influence of motion and interaction for such a language. Our findings show that a usable visual language can be accomplished by limiting the possible shapes and by making clever use of orientation and meaningful motion. We found that especially motion is very important to improve perception and comprehension of what is being displayed on near-eye out-of-focus displays, and that perception is further improved if direct interaction with the content is allowed.

This paper describes how optimized streaming strategies, based on MPEG-DASH, can be employed to power a new generation of interactive applications based on immersive video. The latter encompasses ultra-high-resolution, omnidirectional and panoramic video. The goal is to deliver experiences that are made up of multiple videos of short duration, which can be joined at run-time in an order defined through user interactions. Applications of the technology are widespread, ranging from virtual walkthroughs to interactive storytelling, the former of which will be featured in detail. The main technological challenges tackled in this paper are to deliver these experiences in a seamless fashion, at the highest quality level allowed by network conditions and on a wide range of platforms, including the Web. Besides these, the paper focuses on the two-tier software architecture of the proposed framework, as well as a short evaluation to substantiate the validity of the proposed solutions.

Omni-directional video (ODV) is a novel medium that offers viewers a 360o panoramic recording. This type of content will become more common within our living rooms in the near future, seeing that immersive displaying technologies such as 3D television are on the rise. However, little attention has been given to how to interact with ODV content. We present a gesture elicitation study in which we asked users to perform mid-air gestures that they consider to be appropriate for ODV interaction, both for individual as well as collocated settings. We are interested in the gesture variations and adaptations that come forth from individual and collocated usage. To this end, we gathered quantitative and qualitative data by means of observations, motion capture, questionnaires and interviews. This data resulted in a user-defined gesture set for ODV, alongside an in-depth analysis of the variation in gestures we observed during the study.

Recently, the design and development of persuasive applications to support behaviour change in healthcare have gained interest. However, achieving sustained behaviour change remains challenging. Shared decision making (SDM) is increasingly advocated for making preference-sensitive decisions. In SDM, the patient and caregiver combine the patient’s preferences, values, goals, and context with the medical evidence and expert opinions to make an informed decision. The link between shared decision making and behaviour change has not yet been investigated thoroughly. Furthermore, there is little guidance on designing applications providing SDM support. In this paper, we focus on how SDM can help in achieving sustained behaviour change by presenting how SDM can bring in the caregiver perspective in the well-known, patient-oriented Fogg Behaviour Model. We propose seven principles to design a system aimed at supporting patients and caregivers during SDM encounters when making decisions regarding behaviour change. We conclude with an illustration of how our proposed design principles have been applied in two existing applications developed to support SDM for behaviour change.