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Accurately predicting the time to an event of interest is an important problem in a wide range of real-world applications. However, prediction is often difficult because many medical datasets have a large number of unlabeled (“censored”) instances because labeling is costly and time consuming. Survival analysis focuses on labeled data to predict the time to an event of interest, such as time of death, or conversion to a different stage in a progressive disease. Grouping structure, which naturally exists in medical datasets, can be exploited to improve generalization performance by learning multiple related survival prediction tasks for subgroups collaboratively. Thus a multi-task learning framework can connect multiple survival prediction tasks (for different subgroups) and learn them simultaneously. In order to take into account both censored information, as well as discover the grouping structure, we propose a novel cluster-boosted multitask learning framework for survival analysis that boosts survival prediction performance. We develop an efficient algorithm and demonstrate the performance of the proposed cluster-boosted multi-task survival analysis method on The Cancer Genome Atlas (TCGA) dataset. Our results show that the proposed approach can significantly improve prediction performance in survival analysis while also identifying different subgroups of cancer patients.

The rapid aging of developed societies is creating an increasing number of cases of dementia and other aging-related diseases. Physical exercise has been shown to be beneficial for retaining cognitive, as well as physical function. In this paper we describe a system that we have developed for motivating older people to exercise. We begin by demonstrating how activity declines with age using an analysis of survey data (from 2003–2015) reported by the U.S. Bureau of Labor and Statistics on American Time Use Usage. We use multiple discriminant analysis to characterize which activities tend to become more, or less frequent as people age. We then review previous exergame approaches for motivating physical activity. After this we discuss a pedaling system that is designed to motivate and facilitate physical activity in the elderly using a combination of competition, social interaction, and engaging video content. We conclude with a discussion of how to adapt exergaming innovations to the context of use.

Many age-specific mental health problems can be related to maladaptive cognitive strategies for engaging with and processing the external environment in relation to self-perception and ego identity. These are essentially attentional balance problems, reflected in maladjustments of the subjective sense of presence in the external world. We present a theoretical rationale for well-being design that takes account of developmental changes, including cognitive aging, sleep, and the sense of presence. For example, young children may suffer from attentional problems, where events in the immediate environment are overly distracting. We see this as an overactive presence mechanism, or hyperpresence. As people become older, more waking time is spent in reminiscence and daydreaming. Eventually, the ability to give timely attention to the environment, as needed to carry out intentions, may become lost in hyperabsence. We specify several practical strategies for designing interactive technologies to help alleviate cognitive and behavioral problems, by restoring a more balanced relation between individual and environment.

Access to leisure and wellbeing can be difficult to arrive at due to constraints in health, income, location and time. With shifting demographics (inversion of the aging pyramid) and increasing urbanization, there is an increasingly urgent need to improve access to leisure activities, particularly for those living in crowded cities or who have limited mobility.

New technologies, such as serious games and ambient activities, are being developed to address problems of under-stimulation, anxiety, and agitation in millions of people living with dementia in long term care homes. Frequent interactions with instrumented versions of these technologies may not only be beneficial for long term care residents, but may also provide a valuable new set of multifaceted data related to the health status of residents over time. In this paper, we develop a model for health monitoring in healthcare environments and we report on two studies that show how medically relevant data can be collected from elderly residents and emergency department patients in an unobtrusive way. The first study shows how data related to cognitive abilities can be collected from elderly emergency department patients and the second study shows how detailed data on a range of factors can be collected from ambient activity units designed to provide engaging interactions for long term care residents. In summary, this paper proposes the use of new technologies to transform long term care from a data poor to a data rich environment, where the health status of long term care residents and elderly patients is more closely monitored.

Quality of Experience (QoE) is a measure of the overall level of customer satisfaction with a vendor. In telecommunications, consumer satisfaction is of great interest in the adoption of novel multimedia products and services. A number of factors can greatly influence the customer experience during a video session. Factors such as user perception, experience, and expectations are expressed by QoE while factors such as application and network performance are expressed by Quality of Service (QoS) parameters. This paper studies the relationship between QoS and QoE in a session-based mobile video streaming. Specific QoS Application Performance Metrics (APMs) are examined based on a QoE assessment database which is built for experimentation and contains 108 subjects. It is shown that these APMs are highly related to two QoE factors, Technical Quality (TQ) and Acceptability. Furthermore, Viewing Ration (VR) parameter and the corresponding Kendall correlation between VR and QoE factors proves that VR is a valuable metric for mapping QoS to QoE. We further generated the compacted decision tree to predict QoE factors through Rebuffering Ratio (RR), Non-interruption Content Viewing Ratio (VRc), and Non-interruption Viewing Ratio (VRs). Through extensive experimentation, a general relationship between APMs and QoE factors has been examined and a primary QoE model is proposed based on this relationship.

HCI education reflects the continual evolution of HCI, embracing the changing landscapes of technology, infrastructure, and technology use. This forum aims to provide a platform for HCI educators, practitioners, researchers, and students to share their perspectives, reflections, and experiences related to HCI education. --- Sukeshini Grandhi, Editor

Mobile computing provides new ways to interact with technology; applications such as navigation, social facilitation, and augmented reality are used while walking. We introduce Gait-Guided Adaptive Interfaces (GGAIs) as a way to manage cognitive load in dual-task conditions (walking while using a device). Gait markers that can be suitably assessed using smartphone sensors (decreased gait speed, increased variability) have been shown to be indicative of cognitive load in older adults. Motor-cognitive interference is a more significant issue as we age, gait becomes less automatic, and the risk of falls under distraction increases. Apps with GGAIs measure changes in gait to infer load and then adapt the way that the App interacts with the user accordingly. We validate this approach using a simple Go/No-Go task, and then show how gait responds to changes in task complexity. We conclude with a discussion of how GGAIs may be used by developers to improve the usability of apps for older users.

While previous research has shown that the sequencing of good and bad experience is an important predictor of overall evaluations of a set of experiences, the impact of sequencing effects on the experience of viewing online video has yet to be established. The aim of this study was to determine whether different sequences of good (G), mediocre (M), and bad (B) quality videos in different blocks would influence overall ratings after viewing those blocks. Thirty-two participants each watched 10 blocks of 4 videos and provided ratings of technical quality (TQ), satisfaction, and frustration for each video in the block, as well as overall ratings for each block (as a whole). Sequences of G, M, and B videos were designed to test whether block characteristics (features), like the peak-end effect and effect of linear trend, influenced summary evaluations of the block service. The results of the experiment show that overall block TQ, satisfaction, and frustration ratings differed significantly by sequencing feature. Difference scores were used to determine whether the features had an effect on overall evaluations beyond what could be explained by the total number of bad videos in the block or the average ratings of the videos in the block. Results showed a significant end effect for negative ends of a block, and an effect of linear trend (both increasing and decreasing). There was no evidence of a peak effect or an end effect for positive ends. The presence of a negative end effect and effect of linear trend indicate that where possible service providers should avoid service sessions with poor service quality at the end, or sessions that have decreasing quality as the session progresses.

Treatment of dementia has, until recently, largely been based on medical models that address the immediate biological needs, but often fail to meet the individualized needs of the person, including social and psychological needs. Recently, Montessori approaches have been used to validate the whole person and to provide engaging alternatives to the responsive behaviors that arise from unmet needs. In this population, sedentary lifestyle is a particularly severe problem, and there is an urgent need for more physical exercise. Given not only the known benefits of exercise, but also the difficulty of providing traditional methods of physiotherapy in the volume required, automated methods for motivating, and rewarding physical exercise are needed. The research reported in this paper focuses on the development of technologies for aging well through increased cognitive and physical activity among people with dementia. Our goal is to develop solutions for some of the issues faced by long-term care environments by creating engaging and rewarding activities that are available to people with dementia on a 24x7 basis. We have developed units called Centivizers (for “in-centivizing” behavior) that show promise in improving or maintaining physical and cognitive status in dementia by providing people with rewarding, and always-on, opportunities for engaging experiences that motivate physical exercise and cognitive activity.

Many people living with dementia are under-stimulated and socially isolated. While there has been an increase in activities and programming based on recreational therapy and music therapy, such programs can cover only a fraction of the day for people with dementia and are resource demanding to execute. The result is that many people with dementia, who are institutionalized, are staying most of the day either in their rooms, sitting in communal areas, or wandering the hallways. A related problem is that people with dementia often have difficulty with social interactions and may become anxious or aggressive around people they do not recognize, or in situations they do not understand. Resulting responsive behaviours (e.g., hitting, screaming) may lead to overmedication and poor quality of life. Ambient Activity Technology (AAT) is a wall-mounted interactive tool designed for people with dementia. The AAT unit is available in the environment for easy access, and have been designed to augment existing programming and activities by providing self-accessed, engaging and personalized interactions at any time (24-hours per day, 7 days/week). AATs have been designed to reduce distress, in residents and caregivers, by substituting responsive behaviours and purposelessness with active and meaningful activities, distractions, and appropriate interventions. This paper describes the motivation behind the design and development of the AAT. The paper ends with a description of our summative evaluation research, which is currently in progress at several long-term care facilities in Ontario, Canada.

This study measured Session Quality of Experience (SQE) by letting people look at visual proxies of a video play bar without having to watch the actual video, with its associated impairments and/or failures. We supplemented a laboratory study of 10 participants with two further online samples of 14, and 20, participants respectively, obtained using online surveys. Cluster analysis was carried out on the entire data set of 44 participants and clusters were obtained representing differences in sensitivity to pricing and to types of disruption. Crucially, there was no significant dependency between samples and cluster demonstrating that visualization can be used in a crowdsourcing, as well as a laboratory, context. This study demonstrates the combined use of crowdsourcing, visualizations of service experience, and cluster analysis to create more efficient, and nuanced, interpretations of SQE.

Technology questionnaires can assist in developing profiles that characterize the ability of people to use new technologies. Technology profiles may also be related to physical and cognitive abilities, and may possibly serve as proxies for constructs that may be more difficult to measure. The purpose of the research reported in this paper was to examine possible relationships between responses to questions about use of technologies and functional and frailty status as measured using a digital, tablet-based test battery. A battery of digitized cognitive and functional assessments was administered on a tablet, along with a technology questionnaire, to Canadian adults over 65 years who called 911 for paramedic services or who presented to an emergency department. 330 people between the ages of 65 and 97 years (mean = 75.8 years, standard deviation = 7.6) participated in the study. We observed significant relationships between elderly adults’ responses to questions about their technology use and their functional status and frailty scores with more technology use implying better functional status and less frailty. It is suggested that the present findings may lead to the use of more detailed technology profiles as efficient proxy estimates of overall functional ability and frailty status in elderly adults.

Walking and cognitive function are interrelated, and thus normal control of gait is perturbed by cognitive impairment. Changes in gait, as measured by quantitative analysis, can be a useful mechanism for detecting early indicators of cognitive decline. Observing changes in gait in the dual-task paradigm, i.e. when the subject walks while performing an attention-demanding task, can be a more sensitive measure. In the study reported in this paper, we developed a mobile application to perform quantitative gait assessment in the single and dual-task condition, using a smartphone’s built in sensor system. We show that the gait parameters, as measured by a mobile device, are significantly related to the corresponding parameters reported by a gold-standard motion capture system. We also demonstrate that this approach may be comparable to previously validated assessments of cognition and executive functioning. Mobile technologies offer a platform for sensitive assessment of changes in cognitive function through gait analysis in dual-task conditions. This methodology opens the way for more frequent assessments of cognition, as part of physiotherapy and rehabilitation practice.

In previous research, we developed a serious target acquisition game (with moles as targets) for assessing cognitive speed. Tong, Chignell, Tierney, and Lee demonstrated that performance on the game may be a useful screening tool for risk of delirium onset. In this study, we validate a version of the game where there are not only targets (moles) that should be hit but also distractors (butterflies, or moles with hats) that should not be hit. We hypothesized that performance on the game should be a measure of response inhibition ability, which has been implicated as a factor in many types of psychopathology. We carried out an experiment (with 30 healthy participants) to test whether the serious game does in fact measure response inhibition by comparing game performance with a standard response inhibition task (the Go/No-Go discrimination task). Our results show that, with the distractors, the game does in fact assess response inhibition ability. We discuss the implications of this work for assessing executive functions in the elderly, and for evaluating recovery in neuro-rehabilitation, and declining ability to perform activities of daily living.

There has been considerable research on developing symptom clusters for cancer patients but finding a consistent and replicable typology of patients in terms of the kinds of symptoms they experience remains elusive (e.g., [1]). One reason for lack of consensus may be that analyses are unfocused, and use different combinations of clustering variables. This paper identifies subgroups of similar cancer patients within a sample of 18,535 patients, based on the Edmonton Symptom Assessment System (ESAS) and also a set of inpatient and outpatient variables using linked administrative sources of Ontario healthcare data. K-means cluster analysis was performed on cancer patients having only one primary cancer type, and who had at least one emergency department (ED) visit. Only variables that had a Pearson correlation of at least 0.1 with the number of days until visiting an ED, after an assessment, were included in the cluster analysis. While information about next emergency department visit was not included as a clustering variable, the number of patient types was chosen so as to minimize the mean absolute error of predictions of next emergency department visits by cancer patients. The next emergency department visit, after the last assessment date of each patient, was predicted for each cluster solution. The cluster solution with maximum accuracy/minimum MAE was used to derive the final set of patient types. With the help of physicians, and guided by the results of these analyses, a description of each patient type was created. Based on our results we grouped cancer patients into four types that differ in terms of type of cancer, stage of cancer, and symptomology. Implications for symptom management and reduction of ED visits are discussed.

Purpose. This study evaluates the predictive ability of patient types (clusters of similar patients) in identifying cancer patients at high risk for emergency department (ED) visits within one year (365 days) following their index date. A descriptive and retrospective cohort study of 45,356 unique cancer patients with only one primary cancer type and at least one ED visit was done using linked administrative sources of health care data. Methods. Three outcomes were investigated in this study. First, the time of ED visit following an index date was predicted using multiple linear regression. Second, those patients who visited an ED within seven days of their index date were detected using logistic regression. In addition to predicting an emergency department visit, vital status of patients was also predicted using logistic regression. We implemented the linear/logistic regression first on unclustered raw data and then on clustered data. The results of these two analyses were then compared. Conclusion. Clustering was found to contribute to a modest improvement in prediction accuracy for all three outcome variables. The results are discussed in terms of the predictive ability of patient types in development of clinical support tools with respect to privacy of patients and their implications for better allocation of resources to cancer patients.

In this paper, individually reported long-term care (LTC) quality indicators have been supplemented with the composite Qindex measure and applied to 614 homes in Ontario, Canada. This study (1) describes the overall quality performance of LTC homes across five years (2012-2017) and (2) determines if organizational factors impact quality performance. The results demonstrate significant, continuous sector-wide improvement in overall quality performance (as assessed by the Qindex) over time and significant differences in quality based on home size, operator size and ownership. This paper positions the Qindex, a global metric of quality, as a valuable tool for quality measurement and management in the LTC sector.

Curved displays are believed to create a feeling of immersiveness similar to virtual reality. However systematic studies are needed to demonstrate that this is, in fact, true and under what conditions. In an experimental study 24 participants compared five different displays (concave, convex, hemisphere, sphere and a flat display) in terms of their immersiveness and perceptibility, and they also rated their overall preferences. Both immersiveness and perceptibility affected overall preference ratings. Participants gave higher preference ratings to the convex and concave displays, which were rated high in immersiveness and perceptibility, but gave lower preference ratings to the hemisphere/spherical display which had high ratings on immersiveness but low ratings on perceptibility. The study results imply that curved displays do indeed create a feeling of immersiveness. Concave and convex displays were rated highly favorably and should receive more attention for applications where visual experience and a feeling of immersiveness is particularly important.

This thesis introduces a new method to measure subjective ratings of technical quality (TQ) in disrupted video (DV). Current measurement methods are subject to extraneous factors such as delays introduced by the streaming software/hardware and the impact of video content. The proposed method is designed to supplement current methods by avoiding the confounding effects of content on TQ ratings and by reducing the time and effort necessary to run experiments. The new method replaces actual video with images representative of videos that contain various disruptions. In the research reported in this thesis, I ran an experiment with 37 participants to explore the viability of assessing TQ using visualizations instead of actual videos. The experiment compared ratings made after actually watching videos that varied in TQ versus ratings made after viewing the TQ visualizations, without actually seeing corresponding videos with associated impairments or failures. The results of the experiment showed that, with appropriate training, ratings of TQ made, after viewing the visualizations only, were similar to TQ ratings made after actually watching videos with corresponding impairments or failures.%%%%M.A.S.

The rise in aging populations worldwide places a focus on shifting healthcare needs to match changing demographics. Older adults have a higher risk of becoming frail and losing functional abilities (e.g., walking and bathing) as well as the ability to perform daily activities such as shopping and cooking. Providing care and appropriate interventions to assist older adults with frailty is contingent upon identifying these individuals through effective screening. Frailty is often characterized by self-reports of exhaustion, weakness, slowing, and low physical activity. Older adults at risk of becoming frail often enter the healthcare system through emergency services (e.g., calling 911 or presenting at an emergency department), and screening should target these entry points. This paper discusses the design process, and usability findings associated with a tablet-based battery of frailty measures for assessing functional and cognitive states in elderly adults while being admitted to emergency care. This research is focusing on the use of digital technologies as a medium for physical and mental frailty assessment in emergency care. A diverse group of healthcare users is envisaged including paramedics, physicians, and research personnel, as well as end-users such as elderly patients and their caregivers. We describe the development and usability of the tablet-based frailty assessment system and we report on the concurrent validity of frailty measures.

Purpose: Although extensive research has been carried out on the determinants of mobile or wearable health care technology (mHealth), as well as on its acceptance by patients and other health care providers, very little research has been done on physiotherapists' perspectives on the use of mHealth in their current or future practice. The aims of this study were to (1) explore the attitudes of physiotherapists toward mHealth using a modified technology acceptance model questionnaire, (2) understand the applications and delivery paradigms that are most desirable, and (3) assess the content validity of the questionnaire. Method: The questionnaire was administered online. Participants (n=76) were recruited using snowball and convenience sampling. Data were analyzed using factor analysis and partial least-squares path modelling. Results: Results indicate that perceived usefulness and perceived ease of use were related to early adoptive behaviour among participants. We found no evidence that age, gender, experience, or practice setting influenced early adoptive behaviour. Participants demonstrated favourable attitudes toward mHealth tools in clinical practice. Conclusions: This article provides initial insights into factors that are likely to be significant determinants of adoption of mHealth among physiotherapists. Further work, including qualitative research, will help to identify personal and institutional factors that will improve the acceptance of mHealth.

Background Systematic reviews are infrequently used by health care managers (HCMs) and policy-makers (PMs) in decision-making. HCMs and PMs co-developed and tested novel systematic review of effects formats to increase their use. Methods A three-phased approach was used to evaluate the determinants to uptake of systematic reviews of effects and the usability of an innovative and a traditional systematic review of effects format. In phase 1, survey and interviews were conducted with HCMs and PMs in four Canadian provinces to determine perceptions of a traditional systematic review format. In phase 2, systematic review format prototypes were created by HCMs and PMs via Conceptboard©. In phase 3, prototypes underwent usability testing by HCMs and PMs. Results Two hundred two participants (80 HCMs, 122 PMs) completed the phase 1 survey. Respondents reported that inadequate format (Mdn = 4; IQR = 4; range = 1–7) and content (Mdn = 4; IQR = 3; range = 1–7) influenced their use of systematic reviews. Most respondents (76%; n = 136/180) reported they would be more likely to use systematic reviews if the format was modified. Findings from 11 interviews (5 HCMs, 6 PMs) revealed that participants preferred systematic reviews of effects that were easy to access and read and provided more information on intervention effectiveness and less information on review methodology. The mean System Usability Scale (SUS) score was 55.7 (standard deviation [SD] 17.2) for the traditional format; a SUS score

–The Association of Computing Machinery (ACM) Special Interest Group on Computer-Human Interaction (SIGCHI) has been supporting research into HCI education for many years, most actively in the last six years. At its CHI2014 conference, a workshop on developing a new Human-Computer Interaction (HCI) living curriculum was held, building on three years of research and collaboration. We believe the time is now right to design and build the proposed HCI living curriculum. This paper proposes the preliminary framework for a concrete active social network of HCI scholars and educators, sharing and collaborating to develop course outlines, curricula, and teaching materials. In particular, this paper presents the use cases and design requirements of the HCI living curriculum, based on data collected from HCI educators and practitioners. Future initiatives to move the designforward by prototyping a first version of the living curriculum are also discussed.

Current cognitive testing methods in the elderly rely on clinical assessments, which are time consuming, costly, and require highly trained staff (Kueider, Parisi, Gross, & Rebok, 2012). We are developing a serious game with the goal of improving the ergonomics of cognition assessment. Instead of pencil and paper, or a computer, we are using touch-based tablets in order to provide a highly mobile and usable form of cognitive assessment. We are currently conducting usability studies on elderly adults in different healthcare environments to evaluate the technology. This paper presents work on customizing the game for use by elderly adults in a hospital emergency department (ED) and it will discuss some of the results obtained thus far, focusing on the usability of the game for this clinical population. In addition to usability results we will also report on the validity of the game in terms of how well it agrees with existing methods of cognitive assessment that are used in the ED.

The needs of vulnerable populations have been addressed, traditionally, by an ecosystem of private and public agencies that rely on donations (goods, money and services) which they re-distribute based on their perception of what is needed and where. This approach lacks a comprehensive understanding of the demand side as well as the ability to coordinate between various suppliers of goods and services, predict future demand and identify latent supply. We present a knowledge-based platform that utilizes advances in several Artificial Intelligence fields for a more efficient and effective way of provisioning goods and services to people in need.

This paper introduces research that addresses the subjective assessment of Quality of Experience (QoE) during the entire life cycle of a video session. We define a video session life cycle as the time from when a user attempts to initiate playback, until such time that the video ends either from normal video conclusion or through a network-induced failure. We provide a detailed description of our assessment methodology designed to discern whether a user's QoE would be impacted by the presence of failures. To accomphsh this, we carefully select various test conditions to take into consideration the rating scale used, the types of impairments and failures seen by the user, and whether impaired videos are seen together with failed videos in multi-video sessions. The selection and creation of source video sequences are also discussed, as well as the use of between-subjects and within-subjects approaches for running our experiments in a controlled laboratory setting. Statistical analysis was carried out to interpret our experimental results. We compared the results of the between-subjects measures and the results of the within-subjects measures, and concluded that the introduction of a scale with an extended lower bound enabled subjects to more clearly express their dissatisfaction of videos with failures when compared to the traditional ITU 5-point rating scale. In addition, we observed that videos that were simply impaired but concluded normally did not have a statistically significant difference when an extended scale was used.

In this paper we describe the development of a user interface for a liquid handling robot. We describe the user interface design process that we carried out, beginning with requirements analysis and rapid prototyping, followed by heuristic evaluation. We then demonstrate the resulting cloud interface where the robot is controlled remotely in a teleoperation mode to program common protocols in chemistry, and biology, laboratories. We describe the main characteristics of the web interface, focusing on solution strategies used to expose features for programming experiments, remotely. We also report on the System Usability Scale (SUS) scores obtained by testing the interface with 15 experts in the fields of chemistry, and biology.

With the current phenomenon of aging populations in most parts of the world, there are corresponding increases in age-related conditions associated with impaired cognitive status, such as dementia and delirium. Cognitive status is a key component in carrying out activities of daily living such as walking and bathing, and departures from normal cognitive status may be indicators of acute (e.g., delirium) or chronic (e.g., dementia) conditions. Individuals with cognitive impairments may benefit from playing serious games, which are games designed for a primary purpose other than entertainment. Serious games can potentially assess a variety of factors associated with cognitive decline in dementia, while keeping individuals active and stimulated, thereby potentially slowing down or furthering cognitive decline. In this workshop paper, we discuss the development and use of serious games focusing on cognitive functions that are affected by the progression of dementia.

Many countries are aging societies. Since abilities generally deteriorate with age, technologies can assist older adults in their daily life. Loss of cognitive status is particularly severe in cases of dementia, with around 70% (according to Alzheimers.net) of dementia cases involving Alzheimer's Dementia (AD), a progressive and currently incurable disease. There is considerable research on AD with thousands of relevant publications being added to the PubMed online database every year. The knowledge incorporated in this large body of work is spread across hundreds of thousands of pages of text, making it difficult to distill and mobilize that knowledge in terms of treatments and guidelines. Text mining technology may assist in distilling knowledge from the vast corpus of research literature on Alzheimer's dementia. In this paper, we apply the Named Entity Recognition (NER) system, a text mining (TM) method used to group words into classes, in order to extract useful information from free texts. We present findings concerning how well NER can extract information from a corpus of AD research publications.

Response time and accuracy are two of the most frequently collected dependent measures. Tradeoffs between speed and accuracy are often observed, both between people, and between experimental conditions. In this paper we consider how speed, and accuracy, can be combined into a single, overall measure of performance. We consider two different approaches that adjust accuracy scores based on observed speed of responding and we examine how well those measures work with different data sets. We then present a third approach that combines standardized speed and accuracy scores. We show how this latter approach can represent the data fairly well regardless of which (if any) speed-accuracy tradeoff occurs in the data. We also show how this measure can be further generalized by applying differential weightings to the standardized scores of speed, and accuracy, respectively. We conclude by discussing the value of the measure for use in analyzing human performance data where continuous indicators of accuracy or error can be collected or constructed relatively easily. Our goal in developing the global measure of performance is not to accurately model the speed-accuracy relationship, but rather to create a measure that is more sensitive to experimental differences and causal relationships than either speed or accuracy alone.

We conducted an experiment with 16 participants to investigate the effect of cognitive distraction on performance of a 1-D tracking task that simulated gap control in driving. Participants operated the tracking task with a foot pedal while performing a secondary task (an auditorily presented N-back task) under eight conditions involving all possible (2x2x2) combinations of degree of secondary task difficulty (1-back vs. 2-back), pedal tracking difficulty (hard vs. easy amounts of lag) and presence vs. absence of visual occlusion. In conditions involving occlusion participants could press a button to get rid of the occlusion for a short period of time, i.e., they used Voluntary Interruption of Occlusion (VIO). Our results showed that use of VIO is associated with updating ability and that it trades off against pedal tracking performance. We also found evidence that cognitive distraction due to the impact of updating requirements in the secondary N-Back task affects performance on the primary, pedal tracking, task.

Results of an empirical study on the privacy concerns, attitudes, and behaviour of personal health record (PHR) users are presented. The study addressed the following questions: (1) What are the factors influencing privacy concerns of PHR users? (2) To what extent do PHR users read privacy agreements and which factors are in play when they fail to read them. (3) Are the behaviour and attitudes of PHR users consistent with respect to reading privacy agreements and using privacy settings? We infer from the study results that the factors influencing privacy concerns of general online users (as reported in literature) also apply to PHR users. In spite of privacy concerns, 60% of the respondents in our study reported not reading privacy agreements. PHR users who were highly concerned about privacy did not report changing their default privacy settings (as offered in a typical social networking website) in a manner consistent with their stated attitudes towards privacy. Based on the issues identified in the study we conclude with a number of design recommendations for privacy-friendly PHR systems.

Simple tools are needed to support differential diagnosis in a cognitively complex setting. Tools that show similar patients' diagnoses and treatment trajectories might provide useful clinical decision support for emergency physicians who use a case-based reasoning approach. However, privacy concerns that arise with indirect use of electronic health records (EHRs) must be addressed. The authors present a method to abstract a collection of EHRs into a set of summarized patient types and demonstrate its use on a database of medical records.

We conducted an experiment with 22 participants to investigate the effect of presentation style of a secondary task on a 1-D tracking task that simulated gap control in driving. Participants operated the tracking task with a foot pedal while performing a secondary task (counting vowels in a list of multiple letters) under conditions involving different modalities (audio/ visual), presentation styles (simultaneous/ sequential), task complexity (the number of distractors), and time dependency (list length). Our results showed that audio conditions with a longer and/or more complex secondary task did not improve primary (tracking) task performance, even though eye gaze dwelling time on the primary monitor in these cases tended to be substantially longer than the corresponding times in visual conditions. For a more complex version of the secondary task (longer list lengths) visual presentation of the task all at once (simultaneously) led to better performance then sequential presentation (whether visual or auditory). When given a choice people also tended to prefer simultaneous visual presentation of the secondary task. We discuss the effect of presentation modality of the secondary task in terms of its implications for user interface design in vehicles.

Audio and visual modalities are two common output channels in the user interfaces embedded in today’s mobile devices. However, these user interfaces typically center on the visual modality as the primary output channel, with audio output serving a secondary role. This paper argues for an increased need for shared input multimodal user interfaces for mobile devices. A shared input multimodal interface can be operated independently using a specific output modality, leaving users to choose the preferred method of interaction in different scenarios. We evaluate the value of a shared input multimodal menu system in both a single-task desktop setting and in a dynamic dual-task setting, in which the user was required to interact with the shared input multimodal menu system while driving a simulated vehicle. Results indicate that users were faster at locating a target item in the menu when visual feedback was provided in the single-task desktop setting, but in the dual-task driving setting, visual output presented a significant source of visual distraction that interfered with driving performance. In contrast, auditory output mitigated some of the risk associated with menu selection while driving. A shared input multimodal interface allows users to take advantage of multiple feedback modalities properly, providing a better overall experience.

Customer satisfaction is an important factor governing adoption and retention of multimedia products and services, such as Over-The-Top(OTT) video transmission. Quality of Experience involves user-centric evaluation of various services. However, users differ in terms of their ratings of service quality. Some rating differences are due to unreliability (outlier users who are not motivated, or are not sensitive to differences in quality), but others are systematic differences in rating that may reflect different perspectives on quality. In this paper, we explore the use of outlier analysis and clustering as tools for interpreting QoE data. We report on experimental results demonstrating the use of outlier analysis and clustering. In interpreting the clusters, we examine users' opinions on different types of video disruption, and their ability to distinguish the different levels of impairments/failures.

In this paper, we describe an Over-The-Top (OTT) video Quality of Experience (QoE) subjective evaluation experiment that was carried out to examine variations in the way subjects assess viewing experiences. The experiment focuses on different level of impairment and failure types, using 5-point measurement scales. Clustering is used to differentiate between unreliable and reliable participants, where reliability is defined in terms of criteria such as consistency of rating and ability to distinguish between qualitative differences in level of impairments. The results show that clustering a data set that is augmented with unreliable pseudo-participants can provide a new and improved perspective on individual differences in video QoE assessment.

The study reported in this paper demonstrated, for the first time, that the peak-end effect, commonly found with respect to memories of experience, also applies to overall Quality of Experience (QoE) measures obtained after participants view a sequence of videos. Sequences of videos shown in an experiment varied according to the sequencing and grouping of videos with better or worse Technical Quality (TQ). An end effect was found for both better TQ and worse TQ videos. However the peak effect was found for bad, but not good, videos. These results provide an important first step towards the development of models of Likelihood to Recommend (L2R) based on accumulated experience with a service.

In this paper, we study the relationships between Quality of Service (QoS) and Quality of Experience (QoE) in a session-based Over-The-Top (OTT) video service. A number of Performance Metrics (PMs) with and without the existence of failures during a video are examined. As QoE factors, Technical Quality (TQ) and Acceptability are used. We analyze the correlation between QoS performance metrics and QoE factors, and find new PMs should be employed because failures are included in QoE evaluation. We also summarize the relationships between QoS metrics and QoE factors through machine learning approaches. Using decision tree, we have a general idea about the relationships between PMs and QoE factors. We also understand the impact caused by failures and the value of rating scales.

Sharing of personal health information is subject to multiple constraints, which may dissuade some organizations from sharing their data. Summarized deidentified data, such as that derived from k -means cluster analysis, is subject to far fewer privacy-related constraints. In this paper, we examine the extent to which analysis of clustered patient types can match predictions made by analyzing the entire dataset at once. After reviewing relevant literature, and explaining how data are summarized in each cluster of similar patients, we compare the results of predicting death, and length of stay (LOS) in the ICU 1 1 ICU: Intensive care unit.

Quality of Experience (QoE) is a crucial guiding factor for network management of an end-to-end service session. The network provider can control the resources allocated to sessions and in doing so, influence the Technical Quality (TQ), which covers the technical aspects of signal quality during the session. On the other hand, the network provider has no control over the Content Quality (CQ), which pertains to the user's level of interest in a particular video. Together TQ and CQ influence the Overall eXperience (OX) in a session. In this paper, we present results from a user subjective study in which the impact of TQ and CQ on OX was investigated for Over-The-Top (OTT) video sessions from the perspective of a network provider. This perspective places a focus on those elements of QoE that can be controlled by the provider. Various studies have shown that very high interest in a content can strongly influence QoE independent of other factors, so our study uses videos that are neutral with respect to content. We assess the TQ, CQ and OX for video sessions that contain Integrity impairments (in the form of image freezing) and failures in terms of session Accessibility and Retainability. Our findings indicate that TQ and CQ have a strong impact on OX in the presence of impairments, but no failures. On the other hand, TQ is the main determinant of OX when failures are present.

Memories of experience are influenced by a peak-end effect [13]. Memories are modified to emphasize the final portions of an experience, and the peak positive, or negative, portion of that experience. We examine peak-end effects on judged Technical Quality (TQ) of online video. In two studies, sequences of different types of video disruption were varied so as to manipulate the peak-end effect of the experiences. The first experiment demonstrated an end effect, plus a possible peak effect involving negative, but not positive, experience. The second study manipulated payment conditions so that some sessions were structured as requiring payment to watch the video. The second study also distinguished between a peak effect and a possible sequence effect. Evidence was again found for an end effect, with a secondary effect of sequence, but no evidence was found for a peak effect independent of sequencing.

Emotion is critical to how health-related information is perceived and acted upon. This paper shares empirical and methodological insights from an eHealth multimedia usability study involving participants with type 2 diabetes, using a typical sample size for usability studies: n=10. Skin conductance sensors and a slider were used to assess emotional responses toward videos on disease complications. The videos featuring peers elicited trends of stronger emotional responses compared to the other video formats, for both emotion measures. Clustering was used to investigate patterns in slider usage; participants clustered into types characterized as: ‘responsive’, ‘judging’, and ‘unresponsive’. We examined slider and arousal data to estimate immersion and found that half of participants who moved the slider minimally experienced skin conductance spikes, indicating high immersion. We discuss implications for understanding high-impact eHealth multimedia and for measuring immersion and emotions using small samples common in usability studies.

Measures of emotion should accurately characterize the nature of an emotional experience and determine whether that experience is universal or unique to a subgroup or culture. We investigated the value of assessing emotion through skin conductance (an easy-to-interpret physiological measure) and sliders (frequently used and direct measures of perceived emotion). This paper describes findings from two experiments. The first evaluated various slider configurations and found that measured emotions successfully characterized the emotional nature of short videos. The second experiment collected the slider and skin conductance measures of emotion while one sample of Japanese participants and another sample of Canadian participants viewed longer videos. The measures were sensitive enough to identify cultural differences consistent with existing literature and were also able to identify parts of the experience where members from different cultures reacted consistently, pinpointing content that provoked a universal experience. We offer a toolkit of data interpretation techniques to gain more insight into the implicit and explicit emotion data: analyses for expressiveness and agreement that can infer states such as engagement and fatigue. We summarize the aspects of our measurement approach and toolkit in a model: the ability to distinguish the emotional nature of stimuli, individuals, and affective interaction.