Functional data analysis as a means of evaluating kinematic and kinetic waveforms

Abstract

Researchers use peak and mean characteristics to quantify changes in kinematics and kinetic loading patterns. The variability of human motion warrants a more complex method of analysis. This paper will demonstrate that functional data analysis (FDA) can quantify differences throughout a lifting waveform that would not be evident when applying standard statistical methods to discrete variables. A functional ANOVA was used to identify variation in kinematic and kinetic waveforms resulting from fatigue experienced over a 45-min lifting task. Only trunk angular motion and hip angular velocity were significantly different across the work task using discrete peak values. FDA was able to demonstrate that additional areas outside of the peaks were significantly different in the late phase for several waveforms. FDA was able to demonstrate significant variation across the work period for kinetic and kinematic variables when statistics performed on discrete variables reported no variation. More robust methods for follow-up procedures were recommended.

Keywords:

• functional data analysis
• lifting
• variability
• lumbar moment
• lifting technique