Arjan Claassen

Media distribution in a pervasive computing environment

Distribution of media in the fast growing world of digital stored content and multimedia supporting devices with connectivity, calls for a new media distribution architecture. The user should be provided with the experience of having an overview of his full media collection, regardless of the time, the place, and the connectivity. The architecture presented in this paper, fulfils these needs and can cooperate furthermore with non-compliant devices.

Objectively Measured Physical Activity in European Adults: Cross-Sectional Findings from the Food4Me Study

Background Comparisons of objectively measured physical activity (PA) between residents of European countries measured concurrently with the same protocol are lacking. We aimed to compare PA between the seven European countries involved in the Food4Me Study, using accelerometer data collected remotely via the Internet. Methods Of the 1607 participants recruited, 1287 (539 men and 748 women) provided at least 3 weekdays and 2 weekend days of valid accelerometer data (TracmorD) at baseline and were included in the present analyses. Results Men were significantly more active than women (physical activity level = 1.74 vs. 1.70, p < 0.001). Time spent in light PA and moderate PA differed significantly between countries but only for women. Adherence to the World Health Organization recommendation to accumulate at least 150 min of moderate-equivalent PA weekly was similar between countries for men (range: 54–65%) but differed significantly between countries for women (range: 26–49%). Prevalence estimates decreased substantially for men and women in all seven countries when PA guidelines were defined as achieving 30 min of moderate and vigorous PA per day. Conclusions We were able to obtain valid accelerometer data in real time via the Internet from 80% of participants. Although our estimates are higher compared with data from Sweden, Norway, Portugal and the US, there is room for improvement in PA for all countries involved in the Food4Me Study.

Runners’ Experience of Implicit Coaching Through Music

In this paper we evaluate a music-based coaching system for runners, the SportsCoach. It measures the runner’s heart rate and increases music tempo when, for an optimal workout, the runner should speed up. Coaching is implicit, since the runner only needs to keep in sync with the music and no explicit instructions are given. We performed 2 experiments to evaluate how this implicit coaching was experienced in the actual context of running. The first experiment investigated how natural it is to keep running in sync with the music when the music tempo changes. We find that although runners are not naturally inclined to do so, a band of 10% below one’s natural tempo is mostly easily followed, especially by dancers. The second experiment evaluated the SportsCoach and contrasted its implicit form of coaching and synchronized music to explicit and absent forms of coaching and fixed tempo music. We find that the SportCoach concept scores well on most aspects, especially because of the synchronicity of music and running tempos.

Shorter Feedback Loops By Means of Continuous Deployment

Gathering early feedback on features is critical to many projects. Many Agile methodologies define feedback loops. Often, the feedback loop for completed features only closes after the iteration finishes. In this paper we will introduce a way of closing this feedback loop early, by means of continuous deployment. This also lowers the deployment effort for developers, increasing their happiness.

Abstract P4-08-02: PAPAyA – The genome informatics framework for oncology applications and other clinical domains

Background: Genomics is expected to transform oncology clinical practice. However, converting genomic data into clinically actionable information is a daunting task. Genomic high-throughput technologies produce massive amounts of raw data, and its complexity presents a formidable challenge for clinical adoption. While algorithms exist to convert genomic data into meaningful biological information, they are geared towards the bioinformatics expert user, lack clinical annotation and interpretation, and are not addressing the needs of clinical experts. Furthermore, the main problem is that sequencing results should not be treated like a test as they are geared towards precision diagnostics which require patient clinical data. Methods: We present PAPAyA, a genome informatics platform that provides an overall solution to the genomic data overload which includes analysis of whole transcriptome and exome data, secure storage and management of this data and the interactive presentation of patient genome information in a contextualized manner. It is a continuum of analytics and user experiences with deep understanding of the clinical questions and the workflow. PAPAyA is a framework for hosting multiple genome informatics applications that bring information that is Connected, Digital and in Real Time. Connected in many dimensions - across hospital systems, across time, across many hospitals and their affiliates. Digital means retrievable (without complicated SQL queries) not just stored bits across modalities (genomics is a single vertical that pulls other information towards precise treatment). Real time means up to date ACTGs get converted into actionable information fast, and get to the right clinical expert without manual actions and printing reports. The framework sits on top of a digital health platform that offers core capabilities such as: persisting data and provisioning service (elastic computing), security, auditing, business workflow engine, reports service, user management service, patient identity service, provider registry service. At its core, PAPAyA provides full pipelines that analyze genomic high-throughput data, and further extract and prioritize clinically-meaningful information from the patient9s genome. Furthermore, PAPAyA enables storage and secure management of this complex data which allows clinicians to query the data in a clinical action-oriented framework, as opposed to data aggregation and reporting framework. Results: We demonstrate the usability of PAPAyA using public data from TCGA breast cancer cohort. We show the utility of executing in-silico assays applied on RNAseq data, such as ER/PR/Her2, differential expression of long-noncoding RNAs, gene fusions, subtyping, hypoxia index, and other known signatures from the biomedical literature. In parallel, we annotate full exomes in order to find clinically relevant information for variants of unknown significance as well as variants with known disease and response phenotype using biological, functional, and clinical annotation resources. Conclusion: We have implemented an automated open learning system for processing genomic data to aid in clinical decision making. We already started the pilot phase and clinical evaluation with key academic collaborators. Citation Format: Nilanjana Banerjee, Konstantin Volyanskyy, Vartika Agrawal, Yong Mao, Yee-Him Cheung, Sitharthan Kamalakaran, Laurens Boekhorst, Arjan Claassen, Nevenka Dimitrova. PAPAyA – The genome informatics framework for oncology applications and other clinical domains [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-08-02.