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

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Presentation on theme: "Predicting future injury in runners using participant-specific models of internal structural loading."— Presentation transcript:

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

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

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

4 Background

5

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

7 Background Limitations 2.Cross-sectional and retrospective designs

8 Background Overcoming previous limitations o Estimates internal loading o Prospective design

9 Presentation aims Discuss methods and analyses

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

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

12 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.

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

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

15 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

16 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)

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

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

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

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

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

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

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

24 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…

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

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

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

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

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

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

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

32 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

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

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

35 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

36 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

37

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

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

40

41 ~500 columns per participant per survey 102 participants x 26 surveys ~ 2600 surveys

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

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

44 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

45 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

46 Analysis Injury # reported Days missed Pain Proposed internal variable

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

48 Analysis Proposed internal variable Estimated strides/week

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

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

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