A novel training bike and camera system to evaluate pose of cyclists

Conference paper (2021)

Authors

Raman Garimella Voxdale Bv
koen Beyers Voxdale Bv
T.H. Peeters Universiteit Antwerpen
Stijn Verwulgen Universiteit Antwerpen
Seppe Sels Universiteit Antwerpen
T. Huysmans Applied Ergonomics and Design - IDE
Research Group
Applied Ergonomics and Design (IDE) (TU Delft)
Training Aerodynamics Cycling Motion capture
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Published Date

2021

Language

English

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Faculty

Industrial Design Engineering

Department

Human-Centered Design

Research Group

Applied Ergonomics and Design

Abstract

Aerodynamic drag force can account for up to 90% of the opposing force experienced by a cyclist. Therefore, aerodynamic testing and efficiency is a priority in cycling. An inexpensive method to optimize performance is required. In this study, we evaluate a novel indoor setup as a tool for aerodynamic pose training. The setup consists of a bike, indoor home trainer, camera, and wearable inertial motion sensors. A camera calculates frontal area of the cyclist and the trainer varies resistance to the cyclist by using this as an input. To guide a cyclist to assume an optimal pose, joint angles of the body are an objective metric. To track joint angles, two methods were evaluated: optical (RGB camera for the two-dimensional angles in sagittal plane of 6 joints), and inertial sensors (wearable sensors for three-dimensional angles of 13 joints). One (1) male amateur cyclist was instructed to recreate certain static and dynamic poses on the bike. The inertial sensors provide excellent results (absolute error = 0.28?) for knee joint. Based on linear regression analysis, frontal area can be best predicted (correlation 0.4) by chest anterior/posterior tilt, pelvis left/right rotation, neck flexion/extension, chest left/right rotation, and chest left/right lateral tilt (p 0.01)..