Evaluation of a time-frequency low-pass filter method for assessing knee joint moments and ACL injury risk

Simon Augustus; Kieran Austin; Neal Smith

Evaluation of a time-frequency low-pass filter method for assessing knee joint moments and ACL injury risk

Simon Augustus
, Kieran Austin
, Neal Smith

Research output: Contribution to conference › Paper › peer-review

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.

Original language	English
Publication status	Published - 20 Jul 2022
Event	40th Conference of the International Society of Biomechanics in Sport (ISBS 2022) - Liverpool, U.K. Duration: 19 Jul 2022 → 23 Jul 2022

Conference

Conference	40th Conference of the International Society of Biomechanics in Sport (ISBS 2022)
Period	19/07/22 → 23/07/22

Bibliographical note

Organising Body: International Society of Biomechanics in Sports

Keywords

Allied health professions and studies
anterior cruciate ligament
fractional Fourier filter
inverse dynamics

Cite this

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title = "Evaluation of a time-frequency low-pass filter method for assessing knee joint moments and ACL injury risk",

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{\textquoteleft} Butterworth low-pass filter conditions (0.7 - 1.2 Nm/Kg) and larger than the 'matched{\textquoteleft} 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.",

keywords = "Allied health professions and studies, anterior cruciate ligament, fractional Fourier filter, inverse dynamics",

author = "Simon Augustus and Kieran Austin and Neal Smith",

note = "Organising Body: International Society of Biomechanics in Sports; 40th Conference of the International Society of Biomechanics in Sport (ISBS 2022) ; Conference date: 19-07-2022 Through 23-07-2022",

year = "2022",

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day = "20",

language = "English",

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TY - CONF

T1 - Evaluation of a time-frequency low-pass filter method for assessing knee joint moments and ACL injury risk

AU - Augustus, Simon

AU - Austin, Kieran

AU - Smith, Neal

N1 - Organising Body: International Society of Biomechanics in Sports

PY - 2022/7/20

Y1 - 2022/7/20

N2 - 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.

AB - 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.

KW - Allied health professions and studies

KW - anterior cruciate ligament

KW - fractional Fourier filter

KW - inverse dynamics

M3 - Paper

T2 - 40th Conference of the International Society of Biomechanics in Sport (ISBS 2022)

Y2 - 19 July 2022 through 23 July 2022

ER -

Evaluation of a time-frequency low-pass filter method for assessing knee joint moments and ACL injury risk

Abstract

Conference

Bibliographical note

Keywords

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Cite this