Execution velocity modulates motor variability in distinct ways: faster executions amplify mechanical fluctuations, whereas slower executions increase the temporal complexity of the movement pattern during resistance exercise.
Key Findings
Results
Maximal intended velocity significantly increased the magnitude of motor variability (standard deviation) during parallel back squats compared to preferred and slow velocity conditions.
72 resistance-trained participants performed parallel back squats at 50% of one-repetition maximum under three velocity conditions: preferred velocity, slow velocity, and maximal intended velocity
Standard deviation was used to quantify the magnitude of variability from both an inertial measurement unit (IMU) at the lumbar region and a force platform
Effect sizes for standard deviation were very large: η²p = 0.937 for the IMU and η²p = 0.882 for the force platform
Repeated-measures ANOVAs revealed significant effects of execution velocity on standard deviation in both measurement systems
Results
Slow velocity execution produced higher movement complexity values, particularly as measured by Fuzzy Entropy, compared to faster velocity conditions.
Movement complexity was assessed through Fuzzy Entropy and Detrended Fluctuation Analysis (DFA)
Fuzzy Entropy effect sizes were η²p = 0.738 for the IMU and η²p = 0.712 for the force platform
Repeated-measures ANOVAs revealed significant effects of execution velocity on Fuzzy Entropy in both measurement systems
Slow velocity was associated with higher temporal complexity of the movement pattern
Results
Detrended Fluctuation Analysis (DFA) showed a significant effect of execution velocity only in force platform data, with a smaller effect size than Fuzzy Entropy.
DFA effect size for the force platform was η²p = 0.182
DFA did not show a significant effect in the IMU data
This contrasts with Fuzzy Entropy, which showed significant effects in both measurement systems with much larger effect sizes (η²p = 0.738 and 0.712)
DFA and Fuzzy Entropy captured different aspects of movement complexity and responded differently to velocity conditions
Results
Both the inertial measurement unit and force platform yielded consistent findings regarding the effects of execution velocity on motor variability magnitude and movement complexity.
Acceleration signals were recorded using an IMU placed at the lumbar region; ground reaction force was obtained from a force platform
Significant effects of execution velocity were found on standard deviation in both systems (η²p = 0.937 for IMU; η²p = 0.882 for force platform)
Significant effects on Fuzzy Entropy were found in both systems (η²p = 0.738 for IMU; η²p = 0.712 for force platform)
DFA was the only measure that diverged between instruments, being significant only for the force platform
Discussion
Execution velocity functions as a task constraint that shapes the organization of motor behavior during resistance exercise, beyond its role as a mechanical or physiological training variable.
Three distinct velocity conditions (preferred, slow, and maximal intended) produced qualitatively different patterns of motor variability
The study applied a dynamical systems/ecological framework, conceptualizing velocity as a 'task constraint'
Authors conclude that 'velocity should be considered not only as a mechanical or physiological training variable, but also as a task constraint capable of shaping the organization of motor behavior during resistance exercise'
What This Means
This research suggests that how fast or slow a person performs a resistance exercise — in this case, a parallel back squat — meaningfully changes the nature of their movement variability. The study had 72 trained participants perform squats at three different speeds (their natural preferred speed, a deliberate slow speed, and as fast as possible) using 50% of their maximum lifting capacity. Sensors attached to the lower back and a force-measuring platform recorded movement data, which was then analyzed for both the size of movement fluctuations (variability magnitude) and the complexity or patterning of those fluctuations over time (movement complexity).
The results showed two distinct effects depending on speed. When participants moved as fast as possible, the physical fluctuations in their movement became larger — essentially, fast movement produced more mechanical 'noise.' In contrast, when participants moved slowly and deliberately, the temporal structure of their movement became more complex, meaning the patterns of variability were richer and less predictable over time. These two phenomena — more variability vs. more complexity — represent different aspects of how the motor system organizes itself under different demands.
This research suggests that coaches, trainers, and rehabilitation professionals should think about movement speed not just in terms of how it affects muscle force or power output, but also in terms of how it fundamentally changes the way the nervous system controls movement. Different training speeds may place qualitatively different demands on motor control, which could have implications for skill development, injury prevention, and rehabilitation programming.
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López-Fernández M, García-Aguilar F, Caballero C, Moreno F, Sabido R. (2026). Execution Velocity as a Task Constraint Modulates Motor Variability and Movement Complexity in Dynamic Resistance Exercise.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26196286