Showing papers by "Katarzyna Wac published in 2015"

iSenseStress: assessing stress through human-smartphone interaction analysis

Abstract: Stress condition, if experienced for an extended amount of time, can negatively affect individual's health. Several external sensors monitoring different physiological states correlated with stress, or smartphone apps that monitor individuals context, have been leveraged to assess stress state in everyday life. The less intrusive “human-smartphone interaction” have been under-investigated so far. In our research we leverage ‘swipe’, ‘scroll’ and ‘text input’ interactions to assess the stress state of smartphone users. Based on data collected from 13 participants, we leverage ‘swipe’ and ‘scroll’ data to assess stress with an average F-measure of 79–85% for a within-subject model, and of 70–80% when building a global model. Moreover, ‘text input’ via a virtual keyboard has been analyzed, showing how several easy to calculate features enable to differentiate between stress and no-stress state. To the best of our knowledge, this is the first attempt to leverage human-smartphone interaction, and in particular ‘swipe’, ‘scroll’ and ‘text input’ interactions, to accurately assess stress state in individuals without using any external sensor or leveraging privacy-sensitive context information.

VLQoE: Video QoE instrumentation on the smartphone

Abstract: The usage of network-demanding applications is growing rapidly such as video streaming on mobile terminals. However, network and/or service providers might not guarantee the perceived quality for video streaming that demands high packet transmission rate. In order to satisfy the user expectations and to minimize user churn, it is important for network operators to infer the end-user perceived quality in video streaming. Today, the most reliable method to obtain end-user perceived quality is through subjective tests, and the preferred location is the user interface as it is the closest point of application to the end-user. The end-user perceived quality on video streaming is highly influenced by occasional freezes; technically the extraordinary time gaps between two consecutive pictures that are displayed to the user, i.e., high inter-picture time. In this paper, we present a QoE instrumentation for video streaming, VLQoE. We added functionality to the VLC player to record a set of metrics from the user interface, application-level, network-level, and from the available sensors of the device. To the best of our knowledge, VLQoE is the first tool of its kind that can be used in user experiments for video streaming. By using the tool, we present a two state model based on the inter-picture time, for the HTTP- and RTSP-based video streaming via 3.5G. Next, we studied the influence of inter-picture time on the user perceived quality through out a user study. We investigated the minimum user perceived inter-picture time, and the user response time.

Quality of Life Technologies: Experiences from the Field and Key Challenges

Abstract: Inevitably, as basic human needs are assured in any developed society, differentiating factors for quality of life (QoL) relate to a greater capacity to make informed decisions across daily life activities, especially those related to health. The availability of powerful, personalized, and wearable mobile devices facilitates the provision of ubiquitous computing applications that enable health monitoring and QoL improvements. Here, the authors discuss QoL technologies and present examples of currently researched mobile services for monitoring and improving individuals' physical and psychological health, social interactions, or environmental conditions. They also delineate future work areas for successfully deploying and adopting QoL technologies.

mQoL: Experiences of the ‘mobile communications and computing for Quality of Life’ Living Lab

Abstract: Widespread acceptance and use of personalized mobile devices facilitates the provision of the ubiquitous mobile communications and computing applications that enable the human Quality of Life (QoL) improvement. However, there are multiple human factors influencing these applications, stemming from their users' needs, expectations, and ways of maximizing their experience and the impact on their QoL. For a successful adoption of these applications, our mobile technologies lab, mQoL, employs an iterative, user-centric, Living Lab approach for the applications' design and evaluation. This paper introduces the concept of mobile technologies for QoL specifically aiming to first understand the individual's QoL from information available in mobile devices, i.e., assess physical, psychological, social or environmental aspects of a daily life of an individual, and, based on this understanding, provide services to improve this individual's QoL. This paper also explains the methodological aspects of our research, including transdisciplinarity aspects, and delineates the research challenges for a Living Lab approach at large.

Behind the NAT — A measurement based evaluation of cellular service quality

Abstract: Mobile applications such as VoIP, (live) gaming, or video streaming have diverse QoS requirements ranging from low delay to high throughput. The optimization of the network quality experienced by end-users requires detailed knowledge of the expected network performance. Also, the achieved service quality is affected by a number of factors, including network operator and available technologies. However, most studies focusing on measuring the cellular network do not consider the performance implications of network configuration and management. To this end, this paper reports about an extensive data set of cellular network measurements, focused on analyzing root causes of mobile network performance variability. Measurements conducted over four weeks in a 4G cellular network in Germany show that management and configuration decisions have a substantial impact on the performance. Specifically, it is observed that the association of mobile devices to a Point of Presence (PoP) within the operator's network can influence the end-to-end RTT by a large extent. Given the collected data a model predicting the PoP assignment and its resulting RTT leveraging Markov Chain and machine learning approaches is developed. RTT increases of 58% to 73% compared to the optimum performance are observed in more than 57% of the measurements.

ReNLoc: An anchor-free localization algorithm for indirect ranging

Abstract: Localization has been an important research issue in ubiquitous computing and wireless sensor networks (WSNs). From location-based services to autonomous mobile devices, location is prevalent in a wide range of applications. Localization methods for a mobile node vary from using GPS to localizing with respect to beacons with known locations, or using sensors like accelerometers and compasses. All of these solutions either require additional sensors in a node that reduce its battery life or require some kind of infrastructure and access to a database of anchor locations. Additionally, most solutions are for networks where nodes can communicate indiscriminately with each other. In this paper we introduce ReNLoc, a minimalistic anchor-free multilateration algorithm for 2D space (extendable to 3D space) with a centralized and a distributed version made for networks where the mobile nodes can only get range measurements to nodes with an unknown but fixed position that we call base nodes. The main assumption is that there is a minimum of three base nodes. ReNLoc takes advantage of geometric constraints that arise from the range measurements and represents them as sets on which we perform minimization over known geometric properties. We show that ReNLoc outperforms the commonly used multidimensional scaling (MDS) algorithm in a purely indirect ranging setup.

More mobile & not so well-connected yet: Users' mobility inference model and 6 month field study

Abstract: Smartphones assist their users throughout daily life activities. There is much emphasis on the user's mobility support in the research at large. However, we have a weak understanding about users mobility (are they really moving?) and how well connected are they across their typical day. First, to infer mobility state of users, we derived and evaluated the accuracy of a machine learning-based model, i.e., MobilitySensor, which is based solely on smartphone built-in sensors. It is a tree-based model, defined for each network operator and its average accuracy reaches 91%. Next, we leverage our algorithm to explore the mobility of 34 users served by 3 different Swiss operators (OP) during a period of six months, correlating it with their connectivity. The user study results showed that users are statistically significantly more mobile than we observed in the past (21±7% of the time, i.e., up to 4.3h vs. 13±12%, i.e., 2.7h in 2011) and when they are mobile, 4G network is available to them 38±12% of the time. Furthermore, when mobile, depending on their operator, they may be provided with up to around 10% of the time with 2.5G connectivity (for OP1 and OP2 vs. only 4% OP3), or provided mainly with 3G (49% for OP1 vs. 34% for OP3). Based on the results we provide a set of design implications for application providers, users and operators alike, all striving to improve the mobile users' quality of experience (QoE).

Smartphone users mobile networks quality provision and VoLTE intend: Six-months field study

Abstract: The emerging interactive mobile applications rely the effectiveness of their delivery and their users quality of experience (QoS) on the performance of the underlying heterogeneous networking infrastructures, i.e., their quality of service (QoS). However, the performance that the users will be provided with is a priori unknown, depending on their specific context (e.g., location, time, operator). Moreover, some interactive applications require a particular QoS to be provided, in order to assure their users QoE, e.g., a conversational voice (VoIP) and video-session requires Round Trip Time (RTT) a no higher than 150 ms. In this paper we report the results from a six-months field study involving 15 users of three Swiss network operators where we quantified their networks QoS and context on a minute basis. We then analyse the duration of time intervals and context in which the users are provided with ‘VoIP-friendly RTT’, thus emulating VoLTE. On average, in daily life environments, a mobile user would be able to use a VoIP for 8 minutes for all operators and would need to wait for 3 minutes in between the calls. These numbers reduce to 2–3 minutes each while user is a highly mobile state; only 20% of the VoIP calls over 3G/4G would be able to last 19 minutes. We discuss the implications for mobile network operators focusing on their intend for the deployment of VoLTE services, implications for users themselves, as well as implications for service providers striving to maximise users interactive mobile applications experience.

A Foresight Analysis of Pervasive Healthcare Technologies

Abstract: Inevitably, healthcare goes pervasive, yet its many potential future scenarios are still to be defined. We employ foresight techniques to define some of these scenarios, as relevant for the current and future state of healthcare in Geneva, Switzerland. We teach the methodology to undergraduate business administration students- potential e.g., managers and policymakers in the future healthcare system of Geneva. Our objective is twofold: to train students at scenario building and to develop scenarios for pervasive healthcare technologies and their social implications. Results include scenarios developed by the students as well as lessons learned with respect to the power of foresight techniques employed with novices in this field.

Emerging mHealth innovations for patient self-management support

Abstract: mHealth solutions enable connected patients to take care of their health and care needs while ‘on the move’. There exist a variety of emerging innovative technologies supporting them in their goal of symptoms tracking, medication adherence, or connecting with others, either peers suffering from the same disease or expert practitioners supervising the health status from away. In this article we first present and categorize some examples of such technologies for performance maximization, health maintenance, disease prevention and disease management. Then we discuss these technologies in terms of their design space supporting the patient's self-care, supporting the peer efforts in care, or supporting the patient-practitioner interaction. We discuss the technologies' strengths and weaknesses in terms of the barriers for adoption and scaling. We especially focus on discussion on the evidence of mHealth as an intervention, for its safety, efficiency, efficacy and effectiveness and provide some guidelines for future work areas to be completed, such that evidence can be provided with a sufficient power and emerging mHealth technologies can enable the support for patient health self-management.