Authors:
Jarich Braeckevelt
1
;
Jelle De Bock
2
;
Joke Schuermans
3
;
Steven Verstockt
2
;
Erik Witvrouw
3
and
Jeroen Dierckx
4
Affiliations:
1
IDLab, Ghent University - IMEC, AA Tower, Technologiepark-Zwijnaarde 19, 9052 Ghent, Belgium, Bioracer Motion, Industrieweg 114, 3980 Tessenderlo and Belgium
;
2
IDLab, Ghent University - IMEC, AA Tower, Technologiepark-Zwijnaarde 19, 9052 Ghent and Belgium
;
3
REVAKI, Ghent University, De Pintelaan 185, 9000 Ghent and Belgium
;
4
Bioracer Motion, Industrieweg 114, 3980 Tessenderlo and Belgium
Keyword(s):
Bike Fitting, Data-analysis, Subjectivity Study, Statistics.
Related
Ontology
Subjects/Areas/Topics:
Computer Systems in Sports
;
Multimedia and Information Technology
;
Sport Science Research and Technology
Abstract:
The number of cyclists is growing rapidly, for commuting but also as a sport. With this growth, there has been an increasing interest in cycling position. Trainers, athletes and bike vendors acknowledged this and started to perform bike fits. As these experts have different backgrounds and varying levels of expertise, it was hypothesised that this could have an influence on the outcome in terms of the advised position. In this research three cyclists were bike fitted by nine different bike fitting studios. It was hypothesised that, as different bike fitters use varying techniques and have different experience levels, the cyclist would be advised a different optimal position by these different bike fitters. The preconceived hypothesis was confirmed as the range of advised positions in both saddle height and setback was up to 3 cm. Data-driven bike fitting can help bring down these considerable differences amongst fitters and will be discussed in the last chapter.