Self-logging is a critical component to many wellbeing systems. However, self-logging often is difficult to sustain at regular intervals over many weeks. We demonstrate the power of passive mobile notifications to increase logging of wellbeing data, particularly food intake, in a mobile health service. Adding notifications increased the frequency of logging from 12% in a one-month, ten-user pilot study without reminders to 63% in the full 60-user study with reminders included. We will discuss the benefits of passive notifications over existing interruptive methods.

People now have access to many sources of data about their health and wellbeing. Yet, most people cannot wade through all of this data to answer basic questions about their long-term wellbeing: Do I gain weight when I have busy days? Do I walk more when I work in the city? Do I sleep better on nights after I work out? We built the Health Mashups system to identify connections that are significant over time between weight, sleep, step count, calendar data, location, weather, pain, food intake, and mood. These significant observations are displayed in a mobile application using natural language, for example, "You are happier on days when you sleep more." We performed a pilot study, made improvements to the system, and then conducted a 90-day trial with 60 diverse participants, learning that interactions between wellbeing and context are highly individual and that our system supported an increased self-understanding that lead to focused behavior changes.

Mobile video content today generates more than half of the mobile data traffic.The increasing popularity of mobile video on demand services poses great challenges to mobile operators and content providers. Frontmost, how to reduce the mobile video traffic load, while delivering high quality video content to mobile users without perceived quality degradations for the same (or cheaper) price? Battery lifetime represents another key factor of a user’s Quality of Experience(QoE). A lot of device energy is consumed by mobile network signalling and data transmission over new generation mobile communication systems. This thesis focuses on: (1) reducing the size of the video that is delivered to the enduser in the maximum achievable video quality, thus optimizing the wireless network bandwidth and the user-perceived QoE, and (2) reducing the energy consumption of a mobile device that is associated to data transfer over the radio interface, thus increasing the device’s battery lifetime. The main contributions have been given in providing the Over-the-Top video optimization and delivery schemes and recommendations on tuning their parameters in order to minimize the bandwidth and energy consumption of mobile video delivery, while maximizing the predictable user-perceived QoE. By preventing the video to be prefetched on low data rates and tuning the datarate threshold according to statistical properties of available data rates, we show that 20-70% of energy cost can be reduced by opportunistic prefetching, depending on the user’s pattern of available data rates. The data rate values ordered in time that have a large amount of serial correlation and low noise variance, or low average valueand high peak-to-mean ratio, are likely to yield the highest energy gains from content prefetching. Moreover, we show that energy gains are the largest when the threshold data rate is set close to an average data rate, due to the highest availability of data rates around this value, and for longer sleep time between the prefetching periods, which increases the probability of moving away from the areas with low data rates. Next, we focus on QoE-aware mobile video delivery solutions that are more bandwidth efficient without compromising the user-perceived video quality. They deliver a video over a varying data rate channel that is optimized for viewing on a mobile device in the highest perceptual video quality that can be achieved in the given video and network conditions. An optimized video consists of short segments in the minimum resolutions that satisfy the target perceptual video quality and have up to 60% reduced size compared to the video in the corresponding fixed video resolution, without perceptible quality difference. The delivery is performed by on demand download, context-aware prefetching, or in real time using the QoE-aware adaptive video streaming that runs over Dynamic Adaptive video Streaming over HTTP (DASH). By limiting the maximum bitrates of the requested video segments and using the remaining throughput to prefetch optimized video segments in advance of playout, we show that QoE-aware adaptive video streaming maintains a more stable perceptual video quality than DASH despite the fluctuations of the channel bandwidth, while using fewer number of bits, which improves a user-perceived QoE. The results of this thesis can help operators and content providers to reduce their costs and provide more content to their users at the same (or cheaper) price.

The explosive growth of Over-the-top (OTT) online video strains capacity of operators’ networks, which severely threatens video quality perceived by end users. Since video is very bandwidth consuming, its distribution costs are becoming too high to scale with network investments that are required to support the increasing bandwidth demand. Content providers and operators are searching for solutions to reduce this video traffic load, without degrading their customers’ perceived Quality ofExperience (QoE). This paper proposes a method that can programmatically optimize video content for desired QoE accordingto perceptual video quality and device display properties, while achieving bandwidth and storage savings for content providers, operators, and end users. The preliminary results obtained with Samsung Galaxy S3 phone show that up to 60% savings can be achieved by optimizing movies without compromising the perceptible video quality, and up to 70% for perceptible, but not annoying video quality difference. Tailoring video optimization to individual user perception can provide seamless QoE delivery across all users, with a low overhead (i.e., 10%) required to achieve this goal. Finally, two applications of video optimization: QoE-aware delivery and storage, are proposed and examined.

This paper describes a novel QoE-aware adaptive video streaming method that enhances the viewing experience on mobile devices and reduces cellular network bandwidth consumed by Dynamic Adaptive Streaming over HTTP (DASH) by considering perceptual video quality and data rate channel conditions in the bitrate adaptation process. By streaming an optimized video for the particular video quality and channel conditions toa mobile device, we can improve the worst video qualities causedby DASH streaming and reduce quality variations using fewer number of bits.

The arrival of smartphones and tablets, along with a flat rate mobile Internet pricing model have caused increasing adoption of mobile data services. According to recent studies, video has been the main driver of mobile data consumption, having a higher growth rate than any other mobile application. However, streaming a medium/high quality video files can be an issue in a mobile environment where available capacity needs to be shared among a large number of users. Additionally, the energy consumption in mobile devices increases proportionally with the duration of data transfers, which depend on the download data rates achievable by the device. In this respect, adoption of opportunistic content pre-fetching schemes that exploit times and locations with high data rates to deliver content before a user requests it, has the potential to reduce the energy consumption associated with content delivery and improve the user's quality of experience, by allowing playback of pre-stored content with virtually no perceived interruptions or delays. This paper presents a family of opportunistic content pre-fetching schemes and compares their performance to standard on-demand access to content. By adopting a simulation approach on experimental data, collected with monitoring software installed in mobile terminals, we show that content pre-fetching can reduce energy consumption of the mobile devices by up to 30% when compared to the on demand download of the same file, with a time window of 1 hour needed to complete the content prepositioning.

This paper evaluates the energy cost reduction of Over-The-Top mobile video content prefetching in various network conditions. Energy cost reduction is achieved by reducing the time needed to download content over the radio interface by prefetching data on higher data rates, compared to the standard on demand download. To simulate various network conditions and user behavior, a stochastic access channel model was built and validated using the actual user traces. By changing the model parameters, the energy cost reduction of prefetching in different channel settings was determined, identifying regions in which prefetching is likely to deliver the largest energy gains. The results demonstrate that the largest gains (up to 70%) can be obtained for data rates with strong correlation and low noise variation. Additionally, based on statistical properties of data rates, such as peak-to-mean and average data rate, prefetching strategy can be devised enabling the highest energy cost reduction that can be obtained using the proposed prefetching scheme.

Movement-based interaction design is increasingly popular, with application domains ranging from dance, sport, gaming to physical rehabilitation. In a workshop at CHI 2016, a set of prominent artists, game designers, and interaction designers embarked on a research journey to explore what we came to refer to as "aesthetics in soma-based design". In this follow-up workshop, we would like to take the next step, shifting from discussing the philosophical underpinnings we draw upon to explain and substantiate our practice, to form our own interaction design theory and conceptualisations. We propose that soma-based design theory needs practical, pragmatic as well as analytical study - otherwise the felt dimension will be missing. We will consider how such tacit knowledge can be articulated, documented and shared. To ground the discussion firmly in the felt experience of our own practice, the workshop is organised as a joint practical design work session, supported by analytical study.

The explosion of traffic associated with video content poses significant challenges for mobile content provision. While, on the one hand, mobile video traffic surge is forecast-ed to require significant investments in bandwidth acquisition and infrastructure dimensioning and roll-out, on the other hand, users are not likely to be willing to pay significantly more than today. This increases the pressure to develop solutions capable of making the mobile provision of video more affordable without either affecting user experience or limiting usage. In this respect, this paper proposes a novel methodology for video content delivery which is based on a user video quality perception model. According to this scheme, the video quality of each scene in a movie is selected, from among a finite set of available qualities, with the purpose of reducing the overall bandwidth required to attain a given user experience level targeted by the system for each user and each video. This novel methodology also adopts a clustering approach to identify users with similar Quality of Experience (QoE) profiles and leverages this information for improving the accuracy of user perceived quality predictions. This approach has been validated through a crowd-sourced subjective test evaluation performed with real users using a novel method involving the Amazon Mechanical Turk platform. The results showed that the proposed method is capable of achieving a prediction accuracy in the order of ±0.5 MOS points. This approach can be effectively used to select the video qualities minimizing bandwidth costs while delivering predefined level of perceived quality to the end users.

The current content provision methods and associated pricing and business models are challenged by the traffic requirements anticipated for future 'data intensive' services. In order to deliver substantially higher peak rates operators will need to deploy a much denser infrastructure and/or acquire more spectrum, thus significantly increasing their CAPEX and OPEX and reducing revenues. To improve the utilization of available network resources this paper presents ActiveCast, a disruptive content delivery paradigm that supports opportunistic content pre-fetching by introducing semantic and context awareness in the currently 'agnostic' networking paradigm. The experimental investigations presented in the paper focus on mobile video provision and a content provider, integrated with Facebook and YouTube, has been developed and used to identify socially relevant content for a set of test users. Part of the studies presented in the paper aim at experimentally understanding the structure of the energy costs associated with pre-fetching and on defining a delivery strategy that allows controlling the amount of energy invested. A comparison between a centralized implementation, in which pre-fetching is coordinated by the mobile operators, and an Over-The-Top (OTT) implementation of ActiveCast are also presented. The results show that complementing the context information available at individual user terminals with traffic information, shared by mobile operators through the ActiveCast API, can substantially reduce the energy costs of content delivery, as compared with 'on demand' video streaming. Additionally, opportunistically exploiting connections with WiFi APs can amplify the gains already achievable by prefetching on wide area networks.

This paper explores the key tradeoffs for the design and optimization of eye-gaze based content provision for video streaming services. The proposed end-to-end solution, called "foveated content provision", uses real-time information from connected eye-trackers to dynamically deliver optimized video frames, with higher resolution in areas corresponding to the users' fovea while lowering the quality at the periphery. In this novel approach, the main system constraint is the achievable latency (RTT) in the communication link between content servers and user clients. To cope with various latency levels, several design choices are presented, including varying the size of the high quality region or the resolution for the areas in the user's peripheral field of view. The paper presents a set of experimental results, obtained with real users via a novel event-driven experience sampling method, which is specifically developed to address Quality of Experience (QoE) in foveated content delivery. The results show that several operating points within the system parameter space allows to deliver high levels of QoE, even at latency levels comparable to current 4G networks.

With the development of mobile networks, customer needs and behaviourshave changed. Mobile communications means so much more than simplevoice communication; there is now mobile Internet with web surfing, videophone,streaming media, and micro blogging. The objective of network optimizationhas gradually shifted from enhancing network performance to improvequality of experience (QoE). Therefore, assessing and optimizing QoEis the trend for optimizing future mobile networks.

Today, users want reliable access for their content, wherever they go inthe network. To deliver the best possible experience to mobile broadbandsubscribers, operators need new ways to assess performance that will enablethem to build and manage their networks in the most efficient way. The newparadigmatic eco system (user-interface-network-content) requires novel anddisruptive end-to-end considerations in order to enable and sustain the nextgeneration of services and user experience. Thus, the extraordinary adoptionof mobile connectivity by end users, and the need for optimized bandwidthmanagement network resource, on the one hand, and the growing interest forgood quality content delivery/consumption, is boosting the creation of newnetwork solutions.

We consider that by taking advantage of the capacity to support multimedia platforms and applications of mobile devices (e.g. smartphones, tablets,etc.) is possible to incorporate and provide awareness to the wireless infrastructuresin the context of cross-layer systems to manage the resource allocationaccording to expected QoE levels. In this thesis, we address the questionon how to implement QoE-aware mobile networks and evaluate differentschedulers oriented to take advantage of the proposed architecture. We showthat by providing QoE-awareness to the network infrastructure is possible toimprove user’s QoE and generate impacts in the utilization of the networkresources. With this study, we provide insights into the broader question ofwhether future mobile infrastructures can be deployed considering QoE besidesthe classical QoS considerations.

In this paper semantic-aware model for radio resource management in wireless networks is introduced and studied through simulation. By semantic-awareness, the network can selectively manage the radio resource allocation based on the evaluation of transferred content, and its associated processing, and prioritize users that are close to experience interruptions, in order to improve the wireless resource utilization and the user’s Quality of Experience (QoE). Different radio resource management (RRM) strategies are proposed and investigated, considering buffer capacity at the terminals and the experience of the users in time while watching a video and waiting for resource allocation. The simulation results show that the users can reduce the total duration, frequency and length of the interruptions during a playback by applying semantic-awareness in the radio resource allocation, which might affect positively user’s QoE.

This paper summarizes some of the initial research findings obtained in the SERMON project, funded by Wireless@KTH. The main focus of this paper is on video streaming transmission and the quantification of how much can be gained, in terms of user satisfaction and network resource utilization, by exploiting this semantic knowledge at network level. For this purpose, different QoE-centric RRM strategies are proposed and their performances evaluated in respect to a “classical” agnostic scheme, in a scenario where users have different QoE requirements for different content types and as a function of the device screen resolution during a live video streaming transmission.

This paper first traces the historic evolution of the Quality of Experience (QoE) concept, and then connects common points between the study of user experience as practiced within Human Computer Interaction (HCI) disciplines and recent efforts to understand how user perception can be incorporated into the definition and management of resources in the area of (ICT). After an analysis of the history of QoE and an examination of its current role in HCI, some research challenges are proposed that open doors to future research projects.

We present Communiplay, a public display media space. People passing by see their own contour mirrored on a public display and can start to play with virtual objects. At the same time, they see others playing at remote displays within the same virtual space. We are interested whether people would use such a public display media space, and if so, how and why. We evaluate Communiplay in a field study in six connected locations and find a remote honey-pot effect, i.e. people interacting at one location attract people at other locations. The conversion rate (percentage of passers-by starting to interact) rose by +136% when people saw others playing at remote locations. We also provide the first quantification of the (local) honey-pot effect (in our case it raised the conversion rate by +604% when people saw others playing at the same location). We conclude that the integration of multiple public displays into a media space is a promising direction for public displays and can make them more attractive and valuable.

The concept of playification has recently been proposed as an extension of, or alternative to, gamification. We present a playification design project targeting the re-design of physiotherapy rehabilitative sessions for elderly inpatients. The menial and repetitive nature of the physical exercises targeted for design might seem ideal for shallow widespread gamification approaches that add external rewards to entice usage. In the PhySeEar project, we introduced a "third agent" instead, in the form of technology that would take over some of the work typically carried out by the physiotherapist. This technological intervention triggered the emergence of playfulness, when inpatients and the therapist re-signified the ongoing activity by engaging in playful role-taking, such as blaming the technology for mistakes, or for sensitivity to the inpatient's inaccurate movements. Based on the experiences from this project, we discuss some of the major differences between playification and gamification.

Smart Eye-tracking Enabled Networking (SEEN) is a novel end-to-end framework using real-time eye-gaze information beyond state-of-the-art solutions. Our approach can effectively combine the computational savings of foveal rendering with the bandwidth savings required to enable future mobile VR content provision.

In recent years the growing popularity of mobile phones with the ability of accessing the Internet has increased the usage of video streaming services on the mobile phone devices. These devices can access the Internet using different technologies like Wi-Fi, Bluetooth or Wide Area cellular accesses like GPRS, 3G or 4G. Video streaming services typically consume more data than other successful services like e-mails, photo sharing and web-browsing, and their performances are limited by the bandwidth and data rates that can be provided by current mobile networks. Resource limitations in mobile networks are typically translated into data starvation and interruptions in the video streaming playbacks, leading to low user satisfaction levels. In order to evaluate the users’ satisfaction of the mobile video streaming services, in current heterogeneous mobile networks, it is necessary to introduce techniques to measure the users’ video streaming quality of experience which relates to how users perceive the quality of video streaming playback. In this paper we present an overview of various techniques for measuring the users’ QoE of mobile video streaming service.

This paper presents a novel experimental approach to quantify the performances of Quality of Experience (QoE)- aware resource management scheme in mobile network. The main goal of this paper is to improve network efficiency by exploiting knowledge of QoE information associated with online video streaming services. The investigations considered in the paper are performed using an innovative test-bed, developed to assess network efficiency for the provision of online video services of different qualities. The QoE model used in the proposed QoEaware allocation scheme assumes a MOS-like grading function whose grades depend on both the duration of playtime interruption and the streaming video quality (resolution). The results show that the proposed resource management scheme can deliver more than 40 percent higher QoE to the users of the system as compared to current agnostic (not aware of QoE requirement and content characteristics) service models.

Location-aware services and applications have be- come quite popular in the daily life of mobile users. Global Positioning System (GPS) is available in almost all new smart- phones as a mature and accurate positioning technique. GPS as a satellite-based navigation system, determines the current location of users by receiving signals from satellites. Satellite signals cannot propagate properly inside the buildings, which makes it unusable for indoor positioning. In addition, GPS consumes too much energy to be useful for many applications on mobile phones. There are many proposed alternatives for GPS but they are not as accurate. Combination of those alternatives can improve the accuracy, but varies widely depending on the user behavior and environment. This paper presents a novel architecture for semantic-aware positioning that chooses the best positioning method(s) by exploiting the semantic knowledge. 

In this paper, we present a novel experimental approach to quantify the performances of Quality of Experience (QoE)-aware resource management scheme in mobile networks. The main goal of this paper is to improve network efficiency by exploiting in the resource management the knowledge of QoE information associated with online video streaming services. The investigations considered in the paper are performed using an innovative test-bed, developed to assess network efficiency, as well as the impact on the energy consumption at mobile terminal (MT), for the provision of online video services of different qualities. The QoE model used in the proposed QoE-aware allocation scheme assumes a MOS-like grading function whose grades depend on both the duration of playtime interruption and the video quality (resolution). The results show that the proposed resource management scheme can deliver more than 40 percent higher QoE and energy saving at mobile terminal between 12% to 15% to the users of the system as compared to current agnostic (not aware of QoE requirement and content characteristics) service models.