Category
Methods / Statistics
Document Type
Paper
Abstract
Time-frequency low-pass filters may enable more precise assessment of knee joint kinetics and help identify athletes at risk of ACL injury. The aim of this study was thus to evaluate use of a fractional Fourier filter (FrFF) for estimating knee joint moments during unanticipated sidestepping. 3D kinematic and GRF data were collected from 11 team sports athletes performing 45° cutting manoeuvres and knee moments were derived in five different low-pass filter conditions. The FrFF produced peak abduction moments similar to ‘unmatched’ Butterworth low-pass filter conditions (0.7 – 1.2 Nm/Kg) and larger than the ‘matched’ conditions (0.1 – 0.5 Nm/Kg). This preliminary evidence suggests time-frequency filters can help researchers identify athletes at risk from sustaining ACL injury.
Recommended Citation
Augustus, Simon; Austin, Kieran; and Smith, Neal
(2022)
"EVALUATION OF A TIME-FREQUENCY LOW-PASS FILTER METHOD FOR ASSESSING KNEE JOINT MOMENTS AND ACL INJURY RISK,"
ISBS Proceedings Archive: Vol. 40:
Iss.
1, Article 11.
Available at:
https://commons.nmu.edu/isbs/vol40/iss1/11
