Self-organizing maps (SOM) are a type of artificial neural network for 1) clustering variables and visualizing large datasets and 2) quantifying coordination patterns. The purpose of this study was to use a SOM to investigate the effect of sex and speed on coordination patterns during running. Seventeen females and 15 males ran at their long-slow distance (LSD) training speed and at a speed 30% faster than LSD. Thirty-seven biomechanical variables (gait parameters, joint kinematics, coupling angle variability, EMG, and impact kinetics) were recorded and/or calculated, and analyzed with a SOM. The SOM analysis showed a significant shift in coordination pattern for males and females as running speed increased. This shift was characterized primarily by increases in the rate of ground reaction force loading, tibial impact shock, step lengths, and medial gastrocnemius muscle activation.
Aljohani, Marwan and Kipp, Kristof
"USE OF SELF-ORGANIZING MAPS TO STUDY SEX- AND SPEED-DEPENDENT CHANGES IN RUNNING BIOMECHANICS,"
ISBS Proceedings Archive: Vol. 37
, Article 64.
Available at: https://commons.nmu.edu/isbs/vol37/iss1/64