Stuart McErlain-Naylor

Senior Lecturer in Sport and Exercise Biomechanics

University of Suffolk


Dr Stuart McErlain-Naylor is a Senior Lecturer in Sport and Exercise Biomechanics and Co-Lead of the Sport Performance and Exercise Sciences Research Interest Group at the University of Suffolk, UK.

His research interests include kinetic and kinematic analysis of sporting techniques (mostly ball striking sports), analysis of post-impact accelerations, and the mechanics of flywheel resistance exercise.

Stuart organised and hosted the ISBS Sports Biomechanics Lecture Series and is Social Media Editor for the journal Sports Biomechanics.

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  • sporting technique
  • impact accelerations
  • flywheel exercise


  • PhD in Sports Biomechanics, 2018

    Loughborough University

  • Postgraduate Certificate in Academic Practice (Fellow of the Higher Education Academy), 2020

    University of Suffolk

  • BSc in Sport and Exercise Sciences, 2013

    Loughborough University

About Me

Research Projects

Cricket Batting

The biomechanical determinants of cricket batting performance


The biomechanical determinants of badminton jump smash performance

Flywheel Exercise

Flywheel (isoinertial) eccentric overload exercise induced post-activation performance enhancement

Impact Accelerations

The effect of compliance on post-impact elastic wave accelerations

Most Recent Publications

A Review of Forward-Dynamics Simulation Models for Predicting Optimal Technique in Maximal Effort Sporting Movements

The identification of optimum technique for maximal effort sporting tasks is one of the greatest challenges within sports biomechanics. A theoretical approach using forward-dynamics simulation allows individual parameters to be systematically perturbed independently of potentially confounding variables. Each study typically follows a four-stage process of model construction, parameter determination, model evaluation, and model optimization. This review critically evaluates forward-dynamics simulation models of maximal effort sporting movements using a dynamical systems theory framework. Organismic, environmental, and task constraints applied within such models are critically evaluated, and recommendations are made regarding future directions and best practices. The incorporation of self-organizational processes representing movement variability and “intrinsic dynamics” remains limited. In the future, forward-dynamics simulation models predicting individual-specific optimal techniques of sporting movements may be used as indicative rather than prescriptive tools within a coaching framework to aid applied practice and understanding, although researchers and practitioners should continue to consider concerns resulting from dynamical systems theory regarding the complexity of models and particularly regarding self-organization processes.

Inter-unit reliability of IMU Step metrics using IMeasureU Blue Trident inertial measurement units for running-based team sport tasks

The aim of this study was to determine the inter-unit reliability of IMU Step biomechanical load monitoring metrics using IMeasureU Blue Trident inertial measurement units in tasks common to running-based team sports. Knowledge of variability between units is required before researchers and practitioners can make informed decisions on “true” differences between limbs. Sixteen male college soccer players performed five running-based tasks, generating 224 trials and 17,012 steps. Data were analysed for each task and for the whole session, investigating six IMU Step metrics: step count; impact load; bone stimulus; and low, medium and high intensity steps. Inter-unit reliability was excellent (ICC ≥ 0.90) for 21 out of 26 metrics, and good (0.83 ≤ ICC ≤ 0.86) for all other metrics except for Yo-Yo impact load (ICC = 0.79) which was acceptable. These findings confirm the inter-unit reliability of IMU Step metrics using IMeasureU Blue Trident inertial measurement units for running-based team sports. Now that inter-unit variability has been quantified, researchers and practitioners can use this information when interpreting inter-limb differences for monitoring external biomechanical training load.

Surface acceleration transmission during drop landings in humans

The purpose of this study was to quantify the magnitude and frequency content of surface-measured accelerations at each major human body segment from foot to head during impact landings. Twelve males performed two single leg drop landings from each of 0.15 m, 0.30 m, and 0.45 m. Triaxial accelerometers (2000 Hz) were positioned over the: first metatarsophalangeal joint; distal anteromedial tibia; superior to the medial femoral condyle; L5 vertebra; and C6 vertebra. Analysis of acceleration signal power spectral densities revealed two distinct components, 2-14 Hz and 14-58 Hz, which were assumed to correspond to time domain signal joint rotations and elastic wave tissue deformation, respectively. Between each accelerometer position from the metatarsophalangeal joint to the L5 vertebra, signals exhibited decreased peak acceleration, increased time to peak acceleration, and decreased power spectral density integral of both the 2-14 Hz and 14-58 Hz components, with no further attenuation beyond the L5 vertebra. This resulted in peak accelerations close to vital organs of less than 10% of those at the foot. Following landings from greater heights, peak accelerations measured distally were greater, as was attenuation prior to the L5 position. Active and passive mechanisms within the lower limb therefore contribute to progressive attenuation of accelerations, preventing excessive accelerations from reaching the torso and head, even when distal accelerations are large.

Post flywheel squat potentiation of vertical and horizontal ground reaction force parameters during jumps and changes of direction

(1) Background: The aim of the study was to determine the post-activation performance enhancement (PAPE) of vertical and horizontal ground reaction force parameters during jumps and change of direction following flywheel squat exercise using two different flywheel inertias. (2) Methods: Eleven male athletes performed a countermovement jump (CMJ), standing broad jump (SBJ), and “modified 505” change of direction (COD) in a control condition and 6 minutes following three sets of six repetitions of flywheel half squats at one of two inertias (0.029 kg·m2 and 0.061 kg·m2). Peak directional ground reaction force, power, and rate of force development were calculated for each test. (3) Results: Higher inertia flywheel squats were able to acutely enhance CMJ peak vertical force (Bayes Factor (BF10) = 33.5, very strong; δ = 1.66; CI: 0.67, 2.70), whereas lower inertia flywheel squats were able to acutely enhance CMJ peak vertical power (BF10 = 3.65, moderate; δ = 0.93; CI: 0.11, 1.88). The vertical squat exercise induced no PAPE effect on resultant SBJ or horizontal COD ground reaction force parameters, nor were any differences observed between the inertias. (4) Conclusions: Researchers and practitioners should consider the kinetic and kinematic correspondence of a pre-load stimulus to the subsequent sport-specific activity (i.e., flywheel squat to CMJ).

Concentric and eccentric inertia-velocity and inertia-power relationships in the flywheel squat

The aim of this study was to evaluate the effects of varying flywheel inertia on velocity and power during flywheel squats. Fifteen healthy physically active males performed 6 maximal effort flywheel half-squats at each of 0.029, 0.061, 0.089, and 0.121 kg·m2, with velocity recorded via 3D motion capture and power recorded via inbuilt transducer. Peak concentric velocity (χ² = 37.9; p < 0.001), peak eccentric velocity (χ² = 24.9; p < 0.001), mean concentric velocity (F(3) = 52.7; p < 0.001), and mean eccentric velocity (χ² = 16.8; p < 0.001) all tended to decrease with increases in flywheel inertia, whereas the ratio of peak eccentric to peak concentric power (F(3) = 4.26; p = 0.010) tended to increase. Flywheel inertia had no significant effect on peak concentric or eccentric power, or the ratio of eccentric to concentric peak or mean velocities. The best fit subject-specific inertia-velocity relationships were reported for peak concentric velocity (median linear R2 = 0.95, median logarithmic R2 = 0.97). The results suggest that velocity, rather than power, should be used to prescribe and monitor flywheel squat exercise intensities, and that individualized linear relationships between inertia and peak concentric velocity can be used for this purpose.