Gait analysis and running biomechanics are key to understanding how we move. By breaking down the gait cycle and examining factors like ground reaction forces, we can see how our bodies adapt to different speeds and terrains.
Running economy plays a huge role in performance. From stride length to muscle fiber composition, many factors affect how efficiently we run. Footwear and surfaces also impact our biomechanics, influencing everything from impact forces to injury risk.
Gait cycle phases and biomechanics
Stance and swing phases
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Frontiers | Stance and Swing Detection Based on the Angular Velocity of Lower Limb Segments ... View original
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Human Gait Cycle Analysis Using Kinect V2 Sensor in: Pollack Periodica Volume 15 Issue 3 (2020) View original
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Frontiers | Stance and Swing Detection Based on the Angular Velocity of Lower Limb Segments ... View original
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Top images from around the web for Stance and swing phases
Frontiers | Stance and Swing Detection Based on the Angular Velocity of Lower Limb Segments ... View original
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Frontiers | The mental representation of the human gait in young and older adults View original
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Human Gait Cycle Analysis Using Kinect V2 Sensor in: Pollack Periodica Volume 15 Issue 3 (2020) View original
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Frontiers | Stance and Swing Detection Based on the Angular Velocity of Lower Limb Segments ... View original
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Gait cycle divides into stance phase (60%) and swing phase (40%), each with distinct biomechanical features
Stance phase subphases include initial contact, loading response, midstance, terminal stance, and pre-swing
Swing phase subphases encompass initial swing, midswing, and terminal swing
Joint kinematics during gait involve complex interactions between hip, knee, and ankle joints
Hip joint exhibits flexion during initial contact, extension during stance, and flexion during swing
Knee joint demonstrates flexion during loading response, extension during midstance, and flexion during swing
Ankle joint shows plantarflexion at initial contact, dorsiflexion during stance, and plantarflexion during push-off
Muscle activation patterns alternate between agonist and antagonist groups for efficient movement
Quadriceps activate during early stance for shock absorption
Hamstrings engage during late swing for deceleration
Gastrocnemius and soleus muscles activate during push-off for propulsion
Gait analysis parameters
Center of mass displacement follows sinusoidal pattern in vertical and lateral directions
Vertical displacement approximately 5 cm during normal walking
Lateral displacement about 2-3 cm from side to side
Temporal parameters quantify timing aspects of gait
Stride time measures duration of complete gait cycle (typically 1-1.2 seconds)
Stance time represents duration of foot contact with ground (about 60% of gait cycle)
Swing time indicates duration of foot in air (approximately 40% of gait cycle)
Spatial parameters assess distance-related aspects of gait
Step length measures distance between heel strikes of opposite feet (usually 60-80 cm)
Stride length represents distance between consecutive heel strikes of same foot (typically 120-160 cm)
Step width indicates lateral distance between feet during double support (around 5-15 cm)
Velocity combines temporal and spatial aspects, typically ranging from 1.2-1.5 m/s for normal walking
Running economy and performance factors
Biomechanical and physiological influences
Running economy defined as steady-state oxygen consumption for given submaximal running speed
Biomechanical factors affecting running economy
Stride length optimization balances energy cost of leg swing and ground contact
Ground contact time reduction generally improves economy (optimal range 150-200 ms)
Vertical oscillation minimization reduces energy expenditure (typical range 6-8 cm)
Arm movement patterns influence upper body stability and overall efficiency
Physiological factors impacting running economy
VO2max sets upper limit for aerobic capacity (elite runners often exceed 70 ml/kg/min)
Lactate threshold determines sustainable pace (typically 80-90% of VO2max in trained runners)
Muscle fiber composition affects efficiency (higher proportion of slow-twitch fibers generally improves economy)