Predicting future injury in runners using participant-specific models of internal structural loading.

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Presentation transcript:

Predicting future injury in runners using participant-specific models of internal structural loading

Background Incidence of running injury is high o 18.2 – 92.4% No decline despite years of research

Background Limitations 1.External variables  vGRF  Pronation  Footwear  Strike

Background

ΔITBσ/t PFCF or ΔPFCF/t AJCF or ΔAJCF/t PLσ or ΔPLσ/t ? AJCF or ΔAJCF/t ?

Background Limitations 2.Cross-sectional and retrospective designs

Background Overcoming previous limitations o Estimates internal loading o Prospective design

Presentation aims Discuss methods and analyses

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis

Recruitment n = 102 o >18 yrs. old o run ≥3 per wk. o no running-related/lower-limb injury within 6 mos. o no other sports at competitive level, or >2 per wk.

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis

MoCap 45-marker set 50m indoor track 8 Kistler force plates o Embedded in series 12 Vicon cameras (T-40, T-160) 4 Hyun-Joon laser speed gates

MoCap 2 conditions o Constrained  3m/s±5%  5 min.  ~18 to 20 laps (~3 to 3.3m/s) o Typical  “Use the pace that you run for the majority of your mileage”  5 min.  ~17 to 26 laps (~2.8 to 4.3m/s)

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis

Vicon Nexus Next steps… o Label data o ~40 trials / participant x 102 participants ~4000 trials

Vicon Nexus Next steps… o Label data o ~40 trials / participant x 102 participants ~4000 trials S’up undergrads?

Vicon Nexus Next steps… o Label data o ~40 trials / participant x 102 participants ~4000 trials  Auto-labelling?

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis

Visual3D Next steps… o Export labelled data o Correct coordinate systems o Build an Inverse Kinematics model o Calculate external variables o joint forces and moments o vGRF, ΔvGRF/t o pronation o etc…

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis External variables

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis External variables

Strength testing Biodex o Isotonic  Ankle, knee, hip  2 trials: 10°/s “away,” 60°/s “toward”  2 trials: 60°/s “away,” 10°/s “toward”

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis External variables

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis External variables

MatLab: Strength Next steps… o Participant-specific strength parameters o Write into OpenSim

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis External variables

OpenSim Next steps… o Build model…  Arnold et al., 2010  Lenhart et al., 2014  44 muscle lower-limb with patella o Import…  V3D IK models  Strength parameters

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis External variables Internal variables

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis External variables Internal variables

Surveys Baseline o Sex o Experience  years  competitive level o Past habits  other PA  mileage  location  warm up o Footwear  shoes  orthotics o Lower-limb and running injury history

Surveys 26 weekly o Other PA o Mileage, time per day o Changes in footwear o Pain/Injury  Location  Pain severity  Differential diagnosis  Changes in running/PA

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis External variables Internal variables

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis External variables Internal variables

~500 columns per participant per survey 102 participants x 26 surveys ~ 2600 surveys

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis External variables Internal variables Baseline and Prospective variables

Recruitment Strength Testing MoCap Surveys Nexus Visual3D OpenSim Arnold 2010 Lenhart 2014 MatLab or Excel Analysis External variables Internal variables Baseline and Prospective variables

Analysis External variables o Δ vGRF/t o Pronation o Footstrike Internal variables o PLσ o ΔPLσ/t o PFCF o ΔPFCF/t o AJCF o ΔAJCF/t o ΔITBσ/t o Achilles…? o Plantar fascia…? Baseline and prospective variables o Sex o Experience o History of injury o Footwear o Frequency  Mileage  Estimated strides o Injury  # reported  Time off/altered  Pain

Analysis External variables o Δ vGRF/t o Pronation o Footstrike Internal variables o PLσ o ΔPLσ/t o PFCF o ΔPFCF/t o AJCF o ΔAJCF/t o ΔITBσ/t o Achilles…? o Plantar fascia…? Baseline and prospective variables o Sex o Experience o History of injury o Footwear o Frequency  Mileage  Estimated strides o Injury  # reported  Time off/altered  Pain

Analysis Injury # reported Days missed Pain Proposed internal variable

Analysis Covariates...? More complex or hierarchical models…? Fitting data to theoretical curve…?

Analysis Proposed internal variable Estimated strides/week

Analysis Aggregate loading metric…? o Average z-score of each injury-related variable

Analysis Group-wise comparisons…? o Footstrike (fore vs. rear) o Footwear (minimal vs. support)