The Transmission Control Protocol.

Recent developments and technological advancements in wireless communication, MicroElectroMechanical Systems (MEMS) technology and integrated circuits has enabled low-power, intelligent, miniaturized, invasive/non-invasive micro and nano-technology sensor nodes strategically placed in or around the human body to be used in various applications, such as personal health monitoring. This exciting new area of research is called Wireless Body Area Networks (WBANs) and leverages the emerging IEEE 802.15.6 and IEEE 802.15.4j standards, specifically standardized for medical WBANs. The aim of WBANs is to simplify and improve speed, accuracy, and reliability of communication of sensors/actuators within, on, and in the immediate proximity of a human body. The vast scope of challenges associated with WBANs has led to numerous publications. In this paper, we survey the current state-of-art of WBANs based on the latest standards and publications. Open issues and challenges within each area are also explored as a source of inspiration towards future developments in WBANs.

Wireless Body Area Networks: A Survey

In this Chapter, we imagine a decision maker (or a group of experts) trying to establish or examine fair procedures to combine opinions about alternatives related to different points of view.

Multiple criteria decision making

福祉関連職におけるMaslach Burnout Inventoryの因子構造の比較

The increasing use of wireless networks and the constant miniaturization of electrical devices has empowered the development of Wireless Body Area Networks (WBANs). In these networks various sensors are attached on clothing or on the body or even implanted under the skin. The wireless nature of the network and the wide variety of sensors offer numerous new, practical and innovative applications to improve health care and the Quality of Life. The sensors of a WBAN measure for example the heartbeat, the body temperature or record a prolonged electrocardiogram. Using a WBAN, the patient experiences a greater physical mobility and is no longer compelled to stay in the hospital. This paper offers a survey of the concept of Wireless Body Area Networks. First, we focus on some applications with special interest in patient monitoring. Then the communication in a WBAN and its positioning between the different technologies is discussed. An overview of the current research on the physical layer, existing MAC and network protocols is given. Further, cross layer and quality of service is discussed. As WBANs are placed on the human body and often transport private data, security is also considered. An overview of current and past projects is given. Finally, the open research issues and challenges are pointed out.

/pdf/a-survey-on-wireless-body-area-networks-f3nx5ii4yv.pdf

A survey on wireless body area networks

/pdf/context-aware-qos-provisioning-for-an-m-health-service-n1q7jx9uyb.pdf

Context-aware QoS provisioning for an M-health service platform

For most women of reproductive age, assessing menstrual health and fertility usually involves regular visits to a gynecologist or another clinician. While these exams provide critical information on an individual’s reproductive health status, they typically rely on personal memory, and the results are rarely, if ever, assessed at the population level. In recent years, mobile apps for menstrual tracking have become very popular, allowing us to evaluate the accuracy, reliability and tracking frequency of millions of self-observations, thereby providing an unparalleled view, both in detail and scale, on menstrual health and its evolution. We acquired self-observation data from two mobile apps dedicated to the application of the sympto-thermal fertility awareness method, resulting in a dataset of more than 30 million days of observations from over 2.7 million cycles, where up to 40% of the cycles in which users were seeking pregnancy had recordings every single day. We used a statistical and modeling approach to describe the collected data and investigate ovulation timing. We found that only 24% of ovulations occur at days 14 to 15, that ~20% of luteal phases last for only 10 days or shorter, and that pre-menstrual light bleeding is associated with earlier temperature drop in the late luteal phase. The digital epidemiology approach presented here can help to lead to a better understanding of menstrual health and its connection to women’s health overall, which has historically been severely understudied. Significance statement Over 200 million women track their menstrual cycles using mobile phone apps, but it is unclear if these digitally reported data can inform on menstrual health or fertility at the population level. Here we acquired and presented self-observation data of over 2.7 million cycles from two fertility awareness apps. We used a statistical and modeling approach to evaluate the accuracy, reliability and tracking frequency of millions of self-observations. As up to 40% of the cycles in which users were seeking pregnancy had recordings every single day, mobile self-tracking provides a high resolution and long-term view on individual women’s patterns, with a strong potential for improved clinical decision making.

/pdf/assessment-of-menstrual-health-status-and-evolution-through-2yobpa9qpk.pdf

Assessment of Menstrual Health Status and Evolution through Mobile Apps for Fertility Awareness

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 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 on 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 performance 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. Measurements of the response and page load times of popular websites lead to similar results, namely, a median increase of 40% between the worst and the best performing PoP.

/pdf/assessing-the-implications-of-cellular-network-performance-3faf0mkz4g.pdf

Assessing the Implications of Cellular Network Performance on Mobile Content Access

Inevitably, healthcare goes mobile. Recently developed mobile healthcare (i.e., m-health) services allow healthcare professionals to monitor mobile patient's vital signs and provide feedback to this patient anywhere at any time. Due to the nature of current supporting mobile service platforms, m-health services are delivered with a best-effort, i.e., there are no guarantees on the delivered Quality of Service (QoS). In this paper, we argue that the use of context information in an m-health service platform improves the delivered QoS. We give a first attempt to merge context information with a QoS-aware mobile service platform in the m-health services domain. We illustrate this with an epilepsy tele-monitoring scenario.

/pdf/context-aware-qos-provisioning-in-an-m-health-service-1fbo0dqfd7.pdf

Context-aware QoS provisioning in an m-health service platform

As a base for hypothesis formulation and testing, accurate, timely and reproducible data collection is a challenge for all researchers. Data collection is especially challenging in uncontrolled environments, outside of the lab and when it involves many collaborating disciplines, where the data must serve quality research in all of them. In this paper, we present own "mQoL Smart Lab" for interdisciplinary research efforts on individuals' "Quality of Life" improvement. We present an evolution of our current in-house living lab platform enabling continuous, pervasive data collection from individuals' smartphones. We discuss opportunities for mQoL stemming from developments in machine learning and big data for advanced data analytics in different disciplines, better meeting the requirements put on the platform.

Katarzyna Wac

Papers

Context-aware QoS provisioning for an M-health service platform

Assessment of Menstrual Health Status and Evolution through Mobile Apps for Fertility Awareness

Assessing the Implications of Cellular Network Performance on Mobile Content Access

Context-aware QoS provisioning in an m-health service platform

mQoL smart lab: quality of life living lab for interdisciplinary experiments