FARSEEING at MobEx 2014 Cologne

Wiebren and Chris1

The work of the FARSEEING partners was presented at the MobEx (Mobility and Exercise) meeting on 17th and 18th January in Cologne. The meeting was hosted by the Deutsche Sporthochschule (DSHS) Köln, at the Institute of Sport Gerontology. Presentations were given by researchers from DSHS, EPFL, NTNU, RBMF, the University of Bologna and the University of Manchester.



Pierpaolo MobEx 1

Pierpaolo Palumbo (University of Bologna) presented the development and validation of a prognostic tool for falls, using data from the InCHIANTI epidemiological study.This work is informing the development of the FARSEEING Falls Risk Assessment Tool.


Lars MobEx1

Lars Schwickert (RBK, Stuttgart) reported on the work undertaken to identify the different stages of recovery from a fall. Common movement strategies and key points of different recovery phases were presented, derived from video analyses.





Chris MobEx2

Christopher Moufawad el Achkar (EPFL, Lausanne) presented a complexity analysis of physical activity, using barcode reduction techniques. This work demonstrates promise for the use of a single sensor to measure complexity in physical activity.



Nina MobEx1Nina Skjæret (NTNU, Trondheim) presented the usability testing of three off-the-shelf stepping exergames. Participants played an adapted version of Dance Dance Revolution, LightRace from XBox and The Mole from Silverfit. Although The Mole was the most popular game, none of the games were considered optimal for long term training.




Lorenzo MobEx Web

Lorenzo Chiari (University of Bologna) presented an overview of the FARSEEING project work to date, before demonstrating the Falls Risk Assessment Tool web application. This evidence based web tool will enable practitioners and clinicians to assess a person’s risk of falling, based on known answers or known prevalence of risk factors.



Taxonomy screen shot


Lis Boulton (University of Manchester) delivered a demonstration of the FARSEEING Taxonomy of Technologies. This has been developed as a web application to enable researchers to classify and categorise research studies that include the use of information communication technologies (ICT) to prevent falls and promote independent living.



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