TESTING PRACTICES AND APPLICATIONS OF FLYWHEEL RESISTANCE TECHNOLOGIES - IMPLICATIONS FOR PERFORMANCE ASSESSMENT AND INJURIES FROM A SURVEY STUDY

Author(s): MAK, M.C.W., BEATO, M., DE KEIJZER, K., TURNER, A., WELDON, A., BISHOP, C., Institution: MIDDLESEX UNIVERSITY, Country: HONG KONG, Abstract-ID: 137

INTRODUCTION:
This study explores current practices and applications associated with flywheel resistance
technologies in performance assessment, asymmetry, and injury risk.
METHODS:
A cross-sectional online
survey was conducted among sports scientists, strength and conditioning coaches, and medical
professionals.
RESULTS:
The findings showed that monitoring and testing frequency among practitioners
(n = 42) is low, with 70% (n = 29) conducting it less than once a month. Monitoring and testing
are crucial for adjusting training modalities, allowing practitioners to make informed decisions
to condition athlete performance. Currently, practitioners reported using 2.38±0.87
familiarization sessions and 29.0±21.8 (range:3–75) maximal intent repetitions. It is
recommended to continuously assess both reliability to ensure the data remains reliable and
valid, as the actual familiarization period can be influenced by various factors. The flywheel
squat was the most commonly used exercise (89.9% with rotary encoders), while practitioners
suggested hamstring-focused exercises (e.g., straight leg hip extensions) as having high
potential for injury risk assessment. The most commonly used metrics for monitoring and
testing include: 1)eccentric(E) peak power, 2)concentric(C) peak power, and 3)the E: C ratio.
CONCLUSION:
Overall, the findings suggest that flywheel testing is still underexplored in practice; there is a
clear need for standardized, evidence-based protocols to bridge the gap between its potential
and current implementation. Future research directions should focus on: (i)testing reliability at
higher moments of inertia (>0.15 kg·m²), (ii)evaluating the feasibility of assessing asymmetry
via flywheel, (iii)investigating predictive links between flywheel metrics and field
performance, and (iv)developing validated assessment protocols for a broader range of
exercises.