Integrated inertial sensors and mobile computing for real-time cycling performance guidance via pedaling profile classification.
Today, the bicycle is utilized as a daily commute tool, a physical rehabilitation asset, and sporting equipment, prompting studies into the biomechanics of cycling. Of the number of important parameters that affect cycling efficiency, the foot angle profile is one of the most important as it correlates directly with the effective force applied to the bike. However, there has been no compact and portable solution for measuring the foot angle and for providing the cyclist with real-time feedback due to a number of difficulties of the current tracking and sensing technologies and the myriad types of bikes available. This paper presents a novel sensing and mobile computing system for classifying the foot angle profiles during cycling and for providing real-time guidance to the user to achieve the correct profile. Continuous foot angle tracking is firstly converted into a discrete problem requiring only recognition of acceleration profiles of the foot using a single shoe mounted tri-axial accelerometer during each pedaling cycle. A classification method is then applied to identify the pedaling profile. Finally, a mobile solution is presented to provide real-time signal processing and guidance.
James Y
JY
Xu
Xiaomeng
X
Nan
Victor
V
Ebken
Yan
Y
Wang
Greg J
GJ
Pottie
William J
WJ
Kaiser
D061725:Accelerometry / Q000295:instrumentation / Q000379:methods; D000465:Algorithms; D054874:Athletic Performance / Q000502:physiology*; D001642:Bicycling / Q000502:physiology*; D001696:Biomechanical Phenomena / Q000502:physiology; D005260:Female; D005528:Foot / Q000502:physiology*; D006801:Humans; D008297:Male; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D017216:Telemedicine / Q000295:instrumentation