Visualizing pain data for wheelchair users: A ubiquitous approach

Copyright @ 2005 Rinton PressWe describe a wireless enabled solution for the vizualisation of pain data. Our approach uses pain drawings to record spatial location and type of pain and enables data collection with appropriate time stamping, thus providing a means for the seldom-recorded (but often attested) time-varying nature of pain, with consequential impact on monitoring the effectiveness of patient treatment regimes. Moreover, since the implementation platform of our solution is that of a Personal Digital Assistant (PDA), data collection takes place ubiquitously, providing back pain sufferers with mobility problems (such as wheelchair users) with a convenient means of logging their pain data and of seamlessly uploading it to a hospital server using WiFi technology. Stakeholder results show that, notwithstanding problems related to PDA data input, our approach is generally perceived to be an easy to use and convenient solution to the challenges of anywhere/anytime data collection

MINDtouch embodied ephemeral transference: Mobile media performance research

This is the post-print version of the final published article that is available from the link below. Copyright @ Intellect Ltd 2011.The aim of the author's media art research has been to uncover any new understandings of the sensations of liveness and presence that may emerge in participatory networked performance, using mobile phones and physiological wearable devices. To practically investigate these concepts, a mobile media performance series was created, called MINDtouch. The MINDtouch project proposed that the mobile videophone become a new way to communicate non-verbally, visually and sensually across space. It explored notions of ephemeral transference, distance collaboration and participant as performer to study presence and liveness emerging from the use of wireless mobile technologies within real-time, mobile performance contexts. Through participation by in-person and remote interactors, creating mobile video-streamed mixes, the project interweaves and embodies a daisy chain of technologies through the network space. As part of a practice-based Ph.D. research conducted at the SMARTlab Digital Media Institute at the University of East London, MINDtouch has been under the direction of Professor Lizbeth Goodman and sponsored by BBC R&D. The aim of this article is to discuss the project research, conducted and recently completed for submission, in terms of the technical and aesthetic developments from 2008 to present, as well as the final phase of staging the events from July 2009 to February 2010. This piece builds on the article (Baker 2008) which focused on the outcomes of phase 1 of the research project and initial developments in phase 2. The outcomes from phase 2 and 3 of the project are discussed in this article

Is identifying boredom the answer to controlling the bombardment of notifications on mobile devices?

Mobile notifications have become ubiquitous in modern life, yet excessive volumes contribute to interruption overload. This paper investigates intelligent notification management leveraging user context. A three-stage methodology employed a focus group, survey, and in-the-wild data collection app. The focus group (n=12) provided preliminary insights into notification perceptions during boredom which informed survey design. The survey (n=106) probed usage habits across times, days, and app categories. The SeektheNotification app gathered real-world notification data from 20 Android users over 3 months.Analysis revealed social and personal apps dominate notification volumes (91% combined). Shorter response delays occurred on weekends and after 12 pm, suggesting heightened user receptivity during boredom. Random Forest classification achieved 88% accuracy, outperforming 13 other algorithms, underscoring machine learning’s potential for context-aware notification systems.Our exploratory findings indicate notifications could be optimized by considering situational factors like boredom. Further research should expand context beyond boredom and employ advanced deep learning techniques. This preliminary study demonstrates the promise of leveraging user psychology and machine intelligence to develop smarter interruption management systems to combat notification overload

Health Figures: An Open Source JavaScript Library for Health Data Visualization

The way we look at data has a great impact on how we can understand it, particularly when the data is related to health and wellness. Due to the increased use of self-tracking devices and the ongoing shift towards preventive medicine, better understanding of our health data is an important part of improving the general welfare of the citizens. Electronic Health Records, self-tracking devices and mobile applications provide a rich variety of data but it often becomes difficult to understand. We implemented the hFigures library inspired on the hGraph visualization with additional improvements. The purpose of the library is to provide a visual representation of the evolution of health measurements in a complete and useful manner. We researched the usefulness and usability of the library by building an application for health data visualization in a health coaching program. We performed a user evaluation with Heuristic Evaluation, Controlled User Testing and Usability Questionnaires. In the Heuristics Evaluation the average response was 6.3 out of 7 points and the Cognitive Walkthrough done by usability experts indicated no design or mismatch errors. In the CSUQ usability test the system obtained an average score of 6.13 out of 7, and in the ASQ usability test the overall satisfaction score was 6.64 out of 7. We developed hFigures, an open source library for visualizing a complete, accurate and normalized graphical representation of health data. The idea is based on the concept of the hGraph but it provides additional key features, including a comparison of multiple health measurements over time. We conducted a usability evaluation of the library as a key component of an application for health and wellness monitoring. The results indicate that the data visualization library was helpful in assisting users in understanding health data and its evolution over time.Comment: BMC Medical Informatics and Decision Making 16.1 (2016

Crisis Analytics: Big Data Driven Crisis Response

Disasters have long been a scourge for humanity. With the advances in technology (in terms of computing, communications, and the ability to process and analyze big data), our ability to respond to disasters is at an inflection point. There is great optimism that big data tools can be leveraged to process the large amounts of crisis-related data (in the form of user generated data in addition to the traditional humanitarian data) to provide an insight into the fast-changing situation and help drive an effective disaster response. This article introduces the history and the future of big crisis data analytics, along with a discussion on its promise, challenges, and pitfalls

The Spatial Self: Location-Based Identity Performance on Social Media

This is the author's final manuscript. Copyright 2014 SAGE PublicationsAs a growing number of social media platforms now include location information from their users, researchers are confronted with new online representations of individuals, social networks, and the places they inhabit. To better understand these representations and their implications, we introduce the concept of the “spatial self”: a theoretical framework encapsulating the process of online self-presentation based on the display of offline physical activities. Building on previous studies in social science, humanities, and computer and information science, we analyze the ways offline experiences are harnessed and performed online. We first provide an encompassing interdisciplinary survey of research that investigates the relationships between location, information technology, and identity performance. Then, we identify and characterize the spatial self as well as examine its occurrences through three case studies of popular social media sites: Instagram, Facebook, and Foursquare. Finally, we offer possible research directions and methodological considerations for the analysis of geocoded social media data

Challenges in using cryptography - End-user and developer perspectives

"Encryption is hard for everyone" is a prominent result of the security and privacy research to date. Email users struggle to encrypt their email, and institutions fail to roll out secure communication via email. Messaging users fail to understand through which most secure channel to send their most sensitive messages, and developers struggle with implementing cryptography securely. To better understand how to support actors along the pipeline of developing, implementing, deploying, and using cryptography effectively, I leverage the human factor to understand their challenges and needs, as well as opportunities for support. To support research in better understanding developers, I created a tool to remotely conduct developer studies, specifically with the goal of better understanding the implementation of cryptography. The tool was successfully used for several published developers studies. To understand the institutional rollout of cryptography, I analyzed the email history of the past 27 years at Leibniz University Hannover and measured the usage of email encryption, finding that email encryption and signing is hardly used even in an institution with its own certificate authority. Furthermore, the usage of multiple email clients posed a significant challenge for users when using S/MIME and PGP. To better understand and support end users, I conducted several studies with different text disclosures, icons, and animations to find out if users can be convinced to communicate via their secure messengers instead of switching to insecure alternatives. I found that users notice texts and animations, but their security perception did not change much between texts and visuals, as long as any information about encryption is shown. In this dissertation, I investigated how to support researchers in conducting research with developers; I established that usability is one of the major factors in allowing developers to implement the functions of cryptographic libraries securely; I conducted the first large scale analysis of encrypted email, finding that, again, usability challenges can hamper adoption; finally, I established that the encryption of a channel can be effectively communicated to end users. In order to roll out secure use of cryptography to the masses, adoption needs to be usable on many levels. Developers need to be able to securely implement cryptography, and user communication needs to be either encrypted by default, and users need to be able to easily understand which communication' encryption protects them from whom. I hope that, with this dissertation, I show that, with supporting humans along the pipeline of cryptography, better security can be achieved for all

The Role of Gender in Social Network Organization

The digital traces we leave behind when engaging with the modern world offer an interesting lens through which we study behavioral patterns as expression of gender. Although gender differentiation has been observed in a number of settings, the majority of studies focus on a single data stream in isolation. Here we use a dataset of high resolution data collected using mobile phones, as well as detailed questionnaires, to study gender differences in a large cohort. We consider mobility behavior and individual personality traits among a group of more than $800$ university students. We also investigate interactions among them expressed via person-to-person contacts, interactions on online social networks, and telecommunication. Thus, we are able to study the differences between male and female behavior captured through a multitude of channels for a single cohort. We find that while the two genders are similar in a number of aspects, there are robust deviations that include multiple facets of social interactions, suggesting the existence of inherent behavioral differences. Finally, we quantify how aspects of an individual's characteristics and social behavior reveals their gender by posing it as a classification problem. We ask: How well can we distinguish between male and female study participants based on behavior alone? Which behavioral features are most predictive