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John Cockcroft University of Stellenbosch

An evaluation of inertial motion capture technology for use in the optimization of road cycling kinematics. John Cockcroft University of Stellenbosch. Overview of Presentation. Background to inertial motion capture and road cycling Research motication objectives Experimental work

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John Cockcroft University of Stellenbosch

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  1. An evaluation of inertial motion capture technology for use in the optimization of road cycling kinematics John Cockcroft University of Stellenbosch

  2. Overview of Presentation • Background to inertial motion capture and road cycling • Research motication objectives • Experimental work • Analysis of magnetic interference • Analysis of cycling kinematics • Conclusions

  3. Inertial motion capture technology • The MVN BIOMECH system • Produced by Dutch company Xsens B.V • One of the fastest growing European technology companies • Track motion with accelerometers and gyroscopes attached to the body with a body fitting Lycra suit

  4. Portable storage Kinematic Analysis Digital model Body-fit Lycra suit Wireless data transmission Sensor to segment calculations

  5. FULL BODY KINEMATICS: BIOMECHANICAL MODEL Head Neck Upper arm Forearm Hand Shoulder T8 Sternum T12 L3 L5 Upper leg Lower leg Toe Foot 23 Segments, 22 joints Anthropometrical scaling

  6. INERTIAL MEASUREMENT UNITS • Inertial navigation system • Gyroscope provide angular data • Accelerometer provide linear data • Magnetometer provide heading in the global frame • Errors in sensor kinematics • Integration error in gyroscope and accelerometer data • Magnetic disturbances

  7. ELIMINATING GYROSCOPE INTEGRATION ERROR • Sensor drift • Gyroscope offset errors are cumulative over time • Orientation error can become very large in just a few seconds • Sensor fusion • Accelerometer is used as an inclinometer to stabilize gyroscope data in the vertical plane • Magnetometer data is used to stabilize gyroscope data in the horizontal plane

  8. REDUCING ACCELEROMETER DRIFT ERROR • Joint Updates • Joint constraints reduce error in joint centre estimation • Estimation of contact points • Decreased drift of biomechanical model in global frame

  9. REDUCING MAGNETIC INTERFERENCE • Permanent constant interference • E.g. prostheses, orthotics • Characterized as a priori by Kalman filter and removed • Temporary constant/varying interference • E.g. walking past a speaker or metal structure • Rejected by advanced Kalman filtering • Permanent varying interference (>30s) • E.g. metal beams in the floor • Kinetic Coupling algorithm for lower leg joint flexion

  10. Road Cycling • Goals of technique enhancement • Minimize power demand by increasing aerodynamic efficiency • Maximize power production by increasing biomechanical efficiency • Decreased risk of overuse injuries by improving technique • i.e. Optimize bike fit

  11. Fore-aft position Handlebar adjustment Saddle-heightadjustment Top tube Down tube Seat tube Seat tube angle

  12. Objectives • Objectives • Perform measurements of outdoor cycling kinematics • Investigate level ofmagnetic interference from road bikes • Compare indoor and outdoor results • Investigate the link between rider kinematics and optimal bike fit • Motivation • Sports science research has been slow to adopt motion capture • There is very little sports related work being done with the MVN • Outdoor measurements of cycling kinematics not yet been conducted

  13. Test Protocol • General suit setup • 10 male sub-elite cyclists using own bicycles • Two tests on separate days • Indoor on stationary trainer • Outdoor followed by pursuit vehicle • Three sessions per test • Low, medium and high intensity (2, 3.5 and 5.5 W.kg-1) • 1min long steady-state recordings using the MVN suit

  14. Test Protocol

  15. Test Protocol

  16. Test Protocol

  17. Magnetic Measurement Results • Test environments • The indoor results show significant disturbances • Outdoor tests were undisturbed • Road bicycles • Hand sensors experienced worst interference • Chains, sprockets and pedals disturbed foot sensors • Sensor fusion settings • Kinematic Coupling algorithm is immune to interference • Can only be used for lower body when moving

  18. Hip ΘH Knee ΘK Ankle ΘA Hip, knee and ankle flexion definitions

  19. Overview of outdoor kinematics • Flexion measurements are valid • Joint excursions correlate well with past studies • Significant variability in flexion between cyclists * (Bini RR, 2008) ** (R.J Gregor, 2000)

  20. Comparison of indoor/outdoor tests • Ecological validity of indoor testing • Is laboratory testing on a trainer realistic? • No wind resistance, rigid wheel fixtures etc. • Comparison of laboratory and road tests • Hip and knee values in outdoor tests higher on average • Ankle values in outdoor tests lower on average • However, no clear trend between indoor and outdoor tests

  21. Conclusions • Can the MVN system measure accurate outdoor cycling kinematics? • No. Road bikes cause unacceptable magnetic interference • Only lower body joint angles in the sagittal plane • Flexion values correlate well with other studies • What was learned from the kinematic data? • No clear difference between indoor and outdoor kinematics • High variability in hip, knee and ankle flexion suggest that bicycle fit should not be based on anthropometrical data

  22. THANK YOU

  23. M M M M M M PHYSICAL SETUP MARKER TRACKING DIGITAL MODEL M M M M M M Motion Capture • What is motion capture technology? • Converting analogue marker tracking to a digital model • Applications in entertainment (e.g. movies and games) • Used in movement science (e.g. medical research of gait)

  24. OVERVIEW OF MOTION CAPTURE PROCESS: MVN SENSOR FUSION SCHEME

  25. GYROSCOPE SENSOR FUSION: ERROR-STATE KALMAN FILTER QZM Accelerometer model Accelerometer signal + VA Orientation error θε Gyroscope offset error bε Magnetic disturbance error dε _ VG QZG, QHG, Qb, Qθ Gyroscope model Kalman filter Gyroscope signal _ HG HM + Magnetometer model QHM, Qd Magnetometer signal

  26. SEGMENT KINEMATICS: CALIBRATIONS N-pose T-pose Squat Hand-touch

  27. ESTIMATING SEGMENT KINEMATICS

  28. Effect of workload on kinematics • Relationship between cycling power and rider kinematics • Negligible change between low, medium and high power • Confirms the claims of current published literature

  29. Bilateral Asymmetry • What is bilateral asymmetry? • Difference between left and right sides of the body • Can be a difference in kinetics or kinematics • Can be caused by limb dominance, differences in joint characteristics, anatomical differences, lateral pelvic tilt etc. • Results • Over 30% of the cyclists displayed significant asymmetry • Greatest asymmetry in hip and knee during downstroke • Greatest asymmetry for the ankles during the upstroke

  30. Bilateral asymmetry of the knee joint at minimum flexion Right more flexed Left more flexed

  31. Knee overuse injuries • Knee overuse injuries very common in cycling • Over 33% of knee injuries are to the patellofemoral joint (PFJ) • Second most common is iliotibial band friction syndrome (ITBFS) • Results from analysis • 50% of the cyclists had knee flexion of over 120° and are at risk of PFJ pain • 30% of the cyclists went under 25° flexion and are at high risk of ITBFS

  32. Future Work • Improvements to test protocol • Design of ferromagnetic-free road bicycle • Protocol for clinical anthropometrical measurements • Avenues for future studies • Integration of MVN data with measurements of kinetic, neuromuscular and metabolic variables • Analysis of biomechanical efficiency using 3D joint angles • Study of fatigue effects on upper body kinematics • Dynamic bicycle fit interventions for prevention of injury

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