The Effect of Fatigue on Leg Muscle Activation and Tibial Acceleration During a Jumping Task

Impact Magnitude and Symmetry in Females During Return to Sport Tasks Measured With Inertial Sensors

CONTEXT

Impact magnitude, such as peak tibial acceleration, may be associated with lower extremity injury risk and can be measured with an inertial sensor. An understanding of impact magnitude across functional tasks could guide clinicians in exercise prescription during rehabilitation of lower extremity injuries.

OBJECTIVES

To determine (1) differences in impact magnitude based on task and (2) which tasks have asymmetrical impact magnitude based on limb dominance.

DESIGN

Observational cohort design. Thirty-three healthy, recreationally active adult females participated in 1 testing session on a basketball court.

METHODS

Participants wore inertial sensors with embedded accelerometers on bilateral distal shanks. Participants completed 9 plyometric, speed, and agility tasks commonly utilized during the return to sport phase of lower extremity rehabilitation.

MAIN OUTCOME MEASURES

Average impact magnitude (peak tibial acceleration in multiples of gravity, g) for each limb for each task.

ANALYSES

We used a repeated-measures analysis of variance (factor: task) to determine the differences in impact magnitude based on task. We categorized tasks by magnitude of impact into low, medium, high, and very high impact. We utilized paired t tests for each task to compare limbs (dominant vs nondominant).

RESULTS

Impact magnitude differed based on task (P < .001). We classified tasks as low impact (≤10g; single-leg [SL] lateral jump, double-leg [DL] lateral jump); medium impact (11-20g; SL vertical jump, box drill); high impact (21-30g; modified T test, DL forward jump, SL forward jump); and very high impact (≥31g; sprint, DL tuck jump). Impact magnitude differed by limb in 3 tasks (DL forward jump, DL lateral jump, and box drill), with a higher impact on the dominant limb in each task.

CONCLUSIONS

Impact magnitude differed based on task. While most tasks had symmetric impact magnitude between limbs, 3 tasks had a higher impact magnitude on the dominant limb.

Accelerometer-Based Identification of Fatigue in the Lower Limbs during Cyclical Physical Exercise: A Systematic Review

Physical exercise (PE) is beneficial for both physical and psychological health aspects. However, excessive training can lead to physical fatigue and an increased risk of lower limb injuries. In order to tailor training loads and durations to the needs and capacities of an individual, physical fatigue must be estimated. Different measurement devices and techniques (i.e., ergospirometers, electromyography, and motion capture systems) can be used to identify physical fatigue. The field of biomechanics has succeeded in capturing changes in human movement with optical systems, as well as with accelerometers or inertial measurement units (IMUs), the latter being more user-friendly and adaptable to real-world scenarios due to its wearable nature. There is, however, still a lack of consensus regarding the possibility of using biomechanical parameters measured with accelerometers to identify physical fatigue states in PE. Nowadays, the field of biomechanics is beginning to open towards the possibility of identifying fatigue state using machine learning algorithms. Here, we selected and summarized accelerometer-based articles that either (a) performed analyses of biomechanical parameters that change due to fatigue in the lower limbs or (b) performed fatigue identification based on features including biomechanical parameters. We performed a systematic literature search and analysed 39 articles on running, jumping, walking, stair climbing, and other gym exercises. Peak tibial and sacral acceleration were the most common measured variables and were found to significantly increase with fatigue (respectively, in 6/13 running articles and 2/4 jumping articles). Fatigue classification was performed with an accuracy between 78% and 96% and Pearson's correlation with an RPE (rate of perceived exertion) between r = 0.79 and r = 0.95. We recommend future effort toward the standardization of fatigue protocols and methods across articles in order to generalize fatigue identification results and increase the use of accelerometers to quantify physical fatigue in PE.