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markel vigo

A picture of myself at the Chinese Great Wall

I am interested in making data-intensive, complex and critical interactive systems easy to use. Little is known about how individuals interact with these kind of systems, mainly because the activities users carry out are not well understood.

I'm currently addressing this problem in three main spaces: in the health domain I explore how medication safety dashboards, patient portals and health tracking apps are used by clinicians and patients; in the software engineering domain I focus on how engineers construct knowledge artefacts (i.e. ontologies) and task models; and, finally, on the Web, I'm working in finding navigation activities that are proxies of usability problems and knowledge acquisition.

I received a PhD in Computer Science from the University of the Basque Country about web accessibility assessment, evaluation and measurement. I keep active in the accessibility field and publish papers about

I am a Lecturer in the Bio-Health Informatics Group at the School of Computer Science, University of Manchester. I am also a member of the Interaction Analysis and Modelling Lab.

CONTACT

markel . vigo at manchester . ac . uk

@markelvigo

+44 (0) 161 275 0143

2.32 Kilburn Building

School of Computer Science

M13 9PL, Manchester (UK)

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TEAM

Aitor Apaolaza (Post-doc)

Deemah Alqahtani (PhD student, Y2)

He Yu (PhD student, Y1)

Co-supervised PhD students

Julio Vega, Y4

Olu Matthews, Y3

Alaa Alahmadi, Y2

PhD opportunities

a cat

LATEST NEWS

April 2018 — Paper describing the MOVING platform accepted in IEEE Multimedia.

In this paper we argue how the MOVING EU H2020 Project addresses the need of interactive learning platforms that enable open innovation. We describe how our approach relies on the Big Data paradigm for content indexing and learner interaction analytics. The paper will be published in the Special Issue on 'Multimedia Big Data Analytics in Technology Enhanced Learning'.

February 2018Inferring Visual Behaviour from User Interaction Data on a Medical Dashboard will be presented at the Digital Health 2018 conference at WWW in Lyon, France.

We run a lab (N=6) and an observational remote study (N=35) on SMASH, a pharmacist-led intervention for safe prescribing of medications in primary care. Here, we address the question of whether we can infer visual behaviour through user interaction data. Our findings suggest that, there is indeed a relationship between the use of the mouse (in terms of clickstreams and mouse hovers) and visual behaviour in terms of cognitive load. We discuss the implications for the design of adaptive medical dashboards.

December 2017Britain Breathing: using the experience sampling method to collect the seasonal allergy symptoms of a country has been published at the Journal of the American Medical Informatics Association (JAMIA).

The contributions of the paper are twofold: first, we establish that the experience sampling method (i.e. users reporting their own symptoms) is a a reliable method to infer the incidence of seasonal allergies. This was suggested by the strong correlation between the number of antihistamines prescribed by General Practitioners and the lack of well-being reported by allergy sufferers. Second, we found that nasal symptoms reported (ie. a blocked up nose) were the factor most strongly related to overall well-being. Also those who had taken medication for their allergies still reported feeling worse compared with people who hadn't taken medication.

This analysis corresponds to 2016 data but the Britain Breathing project is still running and anybody can become a citizen scientist by participanting in the project. Download the app (Android and iOS) if you want to contribute!

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