Abstract: In computing science, much attention has been paid to generic methods for sharing data in secure infrastructures. These sorts of methods and infrastructures are, of course, necessary for sharing healthcare data. The authors are, however, a long way away from being able to realise the potential of medical and healthcare data to support the sorts of extensive, data-intensive experiments being demanded by precision and stratified medicine. A key architectural problem remaining to be solved is how to maintain control of patient data within the governance of local data jurisdictions, while also allowing these jurisdictions to engage with experiment designs that (because of the need to scale to large population sizes) may require analyses across several jurisdictions. This study provides a snapshot of architectural work underway to provide a clear, effective structure of data safe havens within jurisdictions. It then describes how formally specified experiment designs can be used to enable jurisdictions to work together on experiments that no single jurisdiction could tackle alone. The authors’ current work relates to two jurisdictions (in Scotland and in Italy), but the architecture and methods are general across similar jurisdictions.

Citation: David Robertson, Fausto Giunchiglia, Stephen Pavis, Ettore Turra, Gabor Bella, Elizabeth Elliot, Andrew Morris, Malcolm Atkinson, Gordon McAllister, Areti Manataki, Petros Papapanagiotou, and Mark Parsons (2016). Healthcare data safe havens: towards a logical architecture and experiment automation. The Journal of Engineering, Institution of Engineering and Technology, October, 2016. This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), http://digital-library.theiet.org/content/journals/10.1049/joe.2016.0170.

Download: http://bit.ly/2j3khFT

Our paper “Recognizing Hospital Care Activities with a Pocket Worn Smartphone” received the Best Paper Award at the 6th International Conference on Mobile Computing, Applications and Services (MobiCASE 2014).

This has been a joint effort of the German Research Centre for Artificial Intelligence and the University of Trento, and concerns the problem of “semantic gap” between machine and human semantics.

Abstract: In this work, we show how a smart-phone worn unobtrusively in a nurses coat pocket can be used to document the patient care activities performed during a regular morning routine. The main contribution is to show how, taking into account certain domain specific boundary conditions, a single sensor node worn in such an (from the sensing point of view) unfavorable location can still recognize complex, sometimes subtle activities. We evaluate our approach in a large real life dataset from day to day hospital operation. In total, 4 runs of patient care per day were collected for 14 days at a geriatric ward and annotated in high detail by following the performing nurses for the entire duration. This amounts to over 800 hours of sensor data including acceleration, gyroscope, compass, wifi and sound annotated with groundtruth at less than 1min resolution.

Index Terms: Activity Recognition, health care documentation, real-world study

Citation: Gernot Bahle, Agnes Gruenerbl, Enrico Bignotti, Mattia Zeni, Fausto Giunchiglia and Paul Lukowicz (2014): “Recognizing Hospital Care Activities with a Pocket Worn Smartphone”, 6th International Conference on Mobile Computing, Applications and Services (MobiCASE 2014, http://mobicase.org/2014/show/home)

You can find the complete list of proceedings here: http://proceedings.dev.icstweb.eu/2014/mobicase2014/file-storage/index.html#submissions

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Social computing broadly refers to computing-supported approaches that facilitate interactions among people and organizations. Social computing has emerged as an exciting multidisciplinary area of research, driven by the wealth of easily available information and the success of online social networks and social media. Social computing applications are characterized by high interactivity among users, user-generated content, and in cases such as Wikipedia, more open governance structures. Much of the recent excitement in social computing is driven by data analytics and business models. What is still lacking, however, is a deeper conceptual understanding of social computing — e.g., relating to its conceptual bases, information and abstractions, design principles, and platforms. This event invites papers that take an explicitly multiagent perspective in addressing these gaps and do so in thought-provoking ways.

The First International Workshop on Multiagent Foundations of Social Computing is Co-located with AAMAS 2014

Important Dates

• Submission: January 22, 2014
• Notification: February 19, 2014
• Camera-ready due: March 5, 2014