Bootcamp on Mobile Devices

Mobile devices as research tools in Cognitive Science

2017.01.10 | Anne-Mette Pedersen

Date Tue 10 Oct
Time 09:00 16:00
Location IMC Meeting Room, Jens Chr. Skous Vej 4, Building 1483-312
Registration has closed

Mobile devices are revolutionizing every sphere of life and provide new ways of understanding physiology and behaviour beyond the laboratory. New biosensors, coupled with smartphones, coupled with mobile devices are now available at low cost, and allow rich multi-modal psychophysiological information to be gathered. In the IMC Bootcamp, we will discuss the promise of these devices for cognitive studies, along with methodological considerations for ‘real world’ use.

The workshop will present a set of four linked talks around these themes. There will plenty of opportunity for questions and discussion. All are welcome. 



Prof. Antti Oulasvirta, Aalto University

Professor Anna Cox, Reader and Deputy Director of UCL Interaction Center

Dr. Fiona McNab, Lecturer, University of York

Dr. med. Sebastian Herberger, Munich, Cardiologist at Klinikum Bogenhausen / Founder of Mentalab 


For more information, please contact: Christine Parsons



Crowdsourcing Cognitive Science Studies: Influencing and measuring behaviour in crowdsourced activities

Prof Anna Cox – UCL

Crowdsourcing psychometric data is common in some areas of Human-Computer Interaction. In some areas of the social sciences, it is now considered standard. In this talk I will explore the collection of data in this manner, beginning by describing the variety of approaches that can be used to crowdsource data. Based on literature that compares the results of these approaches to more traditional data-collection techniques, I will propose a set of design and implementation guidelines for crowdsourcing studies.



Smartphones, a smart way to study memory

Dr. Fiona McNab – University of York

Smartphone technology presents exciting opportunities for cognitive science as a medium for rapid, large-scale experimentation and data collection. At present, cost and logistics limit most study populations to small samples, restricting the experimental questions that can be addressed. We investigated whether the mass collection of experimental data using smartphone technology is valid, given the variability of data collection outside of a laboratory setting. We presented four classic experimental paradigms as short games, available as a free app and over the first month 20,800 users submitted data. We found that the large sample size vastly outweighed the noise inherent in collecting data outside a controlled laboratory setting, and show that for all four games canonical results were reproduced. We provide experimental validation for the use of smartphones for data collection in cognitive science, which has led to the collection of richer data sets and novel findings that may not have been possible within a laboratory setting



Inverse Modeling for Cognitive Science "In the Wild"

Prof. Antti Oulasvirta – Aalto University

An important problem for cognitive science is to estimate the parameter values of a model from behavioral data. This is technically challenging, however, because of the remarkable complexity and variety in human behavioral strategies. Data collected "In the Wild" introduces further complications. I discuss a new approach using approximate Bayesian computation (ABC) to condition model parameters to data and prior knowledge. ABC can improve estimates of model parameter values, enable meaningful comparisons between model variants, and support fitting models to individual users. ABC provides novel opportunities for cognitive science research by allowing principled inference of model parameter values and their uncertainty.




Developing Mobile biosignal hard- and software - a "hands-on" perspective

Dr. Sebastian Herberger


The advent of mobile computing has opened up new horizons for human biosignal recording. Currently available solutions in research and the clinic are lagging behind the possibilities of truly mobile, wearable systems. We set out to explore the frontiers of miniaturisation and mobility in biosignal recording systems. For the past 3 years, together with a group of electrical engineers, computer scientists and designers, I have been bootstrapping a biosignal hardware startup that builds a high-precision biosensor in a compact embedded mobile design. It can send up to 8 Ch. of research-grade biosignal data (EEG, ECG, EOG), along with movement and environment data via bluetooth to a mobile device or computer, with the possibility of real-time data interaction. We are working in early tests with local researchers in anaesthesiology and neurology at several German universities (Munich, Giessen, Berlin). We are evolving the mobile software, while evaluating possibilities for future system design in several directions, spanning from novel research paradigms and brain-computer-interfaces based on biosignal fusion of EEG, EOG and movement data, to solutions for mental training or wearable cardiorespiratory biosignal monitoring. I would like to present the development process, give an overview of the system, discuss applications and possibilities, and demo our prototypes. (