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“Effects of Running Speed on a Probabilistic Stress Fracture Model” W. Brent Edwards. Clinical Biomechanics. 2010. PowerPoint Presentation
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Ellen Vanderburgh HSS 409 4/21/10. “Effects of Running Speed on a Probabilistic Stress Fracture Model” W. Brent Edwards. Clinical Biomechanics. 2010. Stress Fractures: What are They? . Over-use injury Cumulative mechanical trauma to bone or muscle Muscle strain causes bone damage

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ellen vanderburgh hss 409 4 21 10
Ellen Vanderburgh

HSS 409


“Effects of Running Speed on a Probabilistic Stress Fracture Model”W. Brent Edwards. Clinical Biomechanics. 2010.

stress fractures what are they
Stress Fractures: What are They?
  • Over-use injury
    • Cumulative mechanical trauma to bone or muscle
    • Muscle strain causes bone damage
  • Small crack within bone
    • Starts as microcrackand becomes macrocrack
    • “crack driving force” is greater than crack resistance
    • Cannot repair damage
  • In lower extremities-occur in load bearing bones
    • Metatarslas, femur, fibula and tibia
  • 15-20% overuse injuries tibial
who is at risk
Who is at Risk?
  • Athletes involved in repetitive, weight bearing, lower body activity
    • Ex: Runners
  • Low bone density
    • Bone cannot repair
    • Common in women
      • Female triad: abnormal eating, excessive exercising, amenorrhea
  • Poor footwear
  • Abrupt training increase
predicting tibial stress fracture probability with biomechanics
Predicting Tibial Stress Fracture Probability with Biomechanics
  • Crack driving force increases with loading magnitude (intensity) and crack length
    • Increases in speed
    • Increases in running cycles (aka strides)
  • High magnitude loading increases rate of microcracks- bone repair process cannot “catch up”
    • Crack resistance is less than crack driving force
  • Must identify loading patterns that cause bone strain
    • Loading magnitude, loading cycles, bone repair process, ground reaction forces, adaptation to activity
purpose and hypothesis of study
Purpose and Hypothesis of Study
  • Determine influence of running speed on the probability of tibial stress fracture during a new running regimen
    • Approximately 100 days
  • “Reducing running speed would decrease tibial strain enough to negate detrimental increased number of loading cycles associated with the reduction”
  • Prediction model!!
    • Use tibial strain measurement to predict relative risk for tibial fracture
  • Strain = Fracture risk
  • 10 males
  • Mean age=24.9
  • Mean mass=70.1
  • All participated in running or athletic activity on weekly basis
  • Injury free
  • Prior to study, no physical activity for 3 months
  • Established joint center locations
    • Anthropometric measurements and retroreflective markers on anatomical landmarks
    • Static motion capture trial, while standing in anatomical position
    • For each joint, x axis was anterior to posterior, y axis in axial direction, z axis was medial to lateral
  • Subjects ran over-ground at 2.5, 3.5 and 4.5 m/s (5.6, 7.8 and 10.1 mph)
    • Speed measured using motion capture of the horizontal component of L5S1 anatomical marker
    • 10 trials performed for each speed
  • Researcher measured time for 3 strides
    • Used to find subjects average stride frequency and stride length for each speed
data processing
Data Processing
  • Measured and averaged stride frequency for each speed
    • 2.5=20.3 Hz, 3.5=26.6 Hz, 4.5=32.8 Hz
  • Took three dimensional joint and segment angles
    • Used flexion/extension, abduction/adduction, internal/external rotation sequence
  • Joint reaction forces and net internal joint moments were determined using inverse dynamics
  • Body segment masses, moments of inertia and center of gravity locations were also calculated
data processing musculoskeletal modeling
Data Processing: Musculoskeletal Modeling
  • Joint angles were interpolated to 101 points into a musculo skeletal model (SIMM model) and scaled to each subjects segment lengths


developing the probalistic model for tibial stress fracture
Developing the Probalistic Model for Tibial Stress Fracture
  • Probability for Fracture=
    • Contact force – Reaction force
      • Contact force:
        • Ground reaction force due to loading intensity, speed and body weight
      • Reaction force:
        • Tibial strain damage, bone repair and bone adaptation
probalistic model for stress fracture tibial contact force
Probalistic Model for Stress Fracture: Tibial Contact Force
  • Used musculoskeletal data to determine contact force acting on tibia-cannot be directly calculated
    • Ankle joint contact force calculated as vector sum of reaction force and muscle forces crossing talocrural joint
    • Fibula absorbs 10% of ankle joint contact force
    • Therefore, contact force for tibia:
probalistic model of stress fracture bone damage fatigue life and adaptation
Probalistic Model of Stress Fracture: Bone Damage, Fatigue Life and Adaptation
  • Used probalistic model of bone damage, repair and adaptation
  • Due to scatter in the fatigue life of bone, probability of failure when there is scatter was calculated using
  • The cumulative probability for bone repair, taking into account for failure, repair and adaptation with respect to time was determined as
  • Joint contact force acting on distal tibia increased with running speed
    • Axial component across longitudinal axis of tibia was the dominant force
    • Mean peak instantaneous tibial contact forces were used to determine the instant of peak resultant force
  • The number of loading exposures decreased with a decrease in running speed due to positive relationship between speed and stride length
  • For 4.8 km/day, loading exposure (strides)for each speed:
    • 2.5 m/s=2435
    • 3.5 m/s=1829
    • 4.5 m/s=1549
  • Probability of failure peaked and leveled off after 40 days of training (within the 100 day new training regimen)
  • Decrease in speed resulted in a decrease in probability for fracture
    • From 4.5-3.5 m/s=7% decrease
    • From 3.5-2.5 m/s=10% decrease
  • Hypothesis of article was supported in that the probability for tibial stress fracture was decreased with a decrease in speed
    • This also supports the idea that a decrease in speed will negate the damage done by the increase in loading cycles with the decrease in speed
  • A decrease in run speed may reduce risk for tibial stress fracturing
  • Risk for fracturing plateaus after 40 days of new regimen
  • **Note: Does not consider biomechanical misalignments or abnormalities
significance to hss 409
Significance to HSS 409
  • Complexity of dynamic muscle equations and forces
    • Dealt only with single joints in static, non-weight bearing positions
    • Need to incorporate numerous angles, centers of gravity, limb lengths to characterize dynamic movements
      • Also not just x and y, but also z (3D)
significance to hss 4091
Significance to HSS 409
    • Physiological component + engineering component
  • Prediction modeling
    • In class- military scaling, back-pack equation
      • Development of derived constants
    • Based on anthropometric analysis, but needs to actually be tested
practical implications
Practical Implications
  • Speed is big factor in recovery and bone adaption
  • Important to consider gradual period during beginning of training
    • First time race: marathon, etc.
    • Recovering from injury: basically starting over
      • Injury potential= very fine line
  • Military
    • Extremely intense training
    • High risk and incidence of stress fracture