Synchronization dynamics between rider and saddle motion across gaits revealed by IMU analysis.

Overview

• This study investigated how the movements of a rider’s body synchronize with the saddle’s motion (representing the horse’s trunk movement) at different horse gaits (walk, trot, canter) using wearable sensors (IMUs).
• It aimed to objectively measure synchronization patterns across various riding conditions and body segments to better understand rider-horse coordination.

Background and Objective

• Effective coordination between horse and rider is important for both performance in riding and the welfare of horse and rider.
• Traditional assessments of rider-saddle synchronization have lacked objective, field-friendly measurement methods.
• The study sought to quantify synchronization dynamics between rider and saddle movement across different gaits (walk, trot, canter).
• The saddle’s motion was used as a proxy for horse trunk oscillations, as it provides a stable platform closely coupled to the horse’s movements.
• The study also investigated whether synchronization patterns vary between different rider body segments (pelvis, trunk, head).

Methods

• Participants: Two experienced riders (with 8–20 years of experience) riding their own or familiar Warmblood horses aged 6 to 14 years.
• Conditions: Horses were ridden at three gaits – walk, trot, and canter – under three riding frame conditions: collected, medium, and extended, reflecting different levels of horse posture and stride length.
• Data Collection: Four wireless inertial measurement units (IMUs) were attached to the rider’s pelvis, trunk, head, and the horse’s saddle.
• Measures: Tri-axial vertical acceleration data were recorded at 60 Hz from all sensors.
• Analysis Techniques: Synchronization between rider body segments and saddle motion was quantified by:
  • Cross-correlation coefficients (measuring strength of linear relationship between acceleration signals)
  • Phase lag (time delay between the signals)
  • Phase-locking values (PLV) (a measure of phase synchronization between signals over time)
• Data were averaged across repeated trials for consistency and reliability.

Key Results

• Effect of Gait Speed:
  • Synchronization strength increased as gait speed increased from walk to trot to canter.
  • Pelvis-saddle cross-correlation: 0.64 at walk (moderate), 0.92 at trot (high), 0.96 at canter (very high).
  • Phase lag for pelvis-saddle reduced from 22 ms at walk to almost zero at trot and canter, indicating nearly simultaneous vertical motion at higher speeds.
• Segment Differences:
  • Pelvis showed the strongest synchronization with saddle motion across all gaits (supports its role as the key mechanical link transmitting horse movement to rider).
  • Trunk and head had lower synchronization at walk (correlation coefficients between 0.62-0.65), but synchronization increased significantly during trot (0.88-0.93) and canter (0.91-0.95).
  • PLV values (indicating phase consistency in synchronization) also increased from about 0.52-0.55 at walk to above 0.90 at trot and canter for all segments, further confirming increased coordination at faster gaits.
• Influence of Riding Frame:
  • Riding frame condition (collected, medium, extended) affected synchronization primarily at the walk.
  • Extended riding frame at walk led to lower correlation and PLV values, suggesting reduced or less consistent rider-saddle coordination in this condition.
  • At trot and canter, riding frame had less influence on synchronization metrics.

Conclusions and Implications

• Rider-saddle synchronization is gait-dependent and progressively strengthens with gait speed.
• The pelvis plays a central mechanical role in transmitting horse trunk motion to the rider’s body during riding.
• A minimal sensor setup using only four IMUs can reliably capture detailed, segment-specific synchronization patterns in real-world riding conditions.
• Findings provide objective, quantitative benchmarks for rider-horse coordination that could enhance training, performance analysis, and welfare assessments.
• Variation in synchronization with riding frame suggests rider posture adjustments and horse biomechanics jointly influence rider-horse motion coupling, especially at slower gaits.

Overall Significance

• This study delivers a practical, non-invasive method to measure dynamic rider-horse interaction with potential application in equestrian sports, rehabilitation, and research.
• Understanding synchronization patterns could guide riders and coaches to optimize movement harmony, potentially reducing injury risk and improving comfort and effectiveness.