Biomechanical Response of the Lower Extremity to Running-Induced Acute Fatigue: A Systematic Review

Abstract

Objective: To investigate (i) typical protocols used in research on biomechanical response to running-induced fatigue, (ii) the effect of sport-induced acute fatigue on the biomechanics of running and functional tests, and (iii) the consistency of analyzed parameter trends across different protocols.Methods: Scopus, Web of Science, Pubmed, and IEEE databases were searched using terms identified with the Population, Interest and Context (PiCo) framework. Studies were screened following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and appraised using the methodological index for non-randomized studies MINORS scale. Only experimental studies with at least 10 participants, which evaluated fatigue during and immediately after the fatiguing run were included. Each study was summarized to record information about the protocol and parameter trends. Summary trends were computed for each parameter based on the results found in individual studies.Results: Of the 68 included studies, most were based on in-lab (77.9%) protocols, endpoint measurements (75%), stationary measurement systems (76.5%), and treadmill environment (54.4%) for running. From the 42 parameters identified in response to acute fatigue, flight time, contact time, knee flexion angle at initial contact, trunk flexion angle, peak tibial acceleration, CoP velocity during balance test showed an increasing behavior and cadence, vertical stiffness, knee extension force during MVC, maximum vertical ground reaction forces, and CMJ height showed a decreasing trend across different fatigue protocols.Conclusion: This review presents evidence that running-induced acute fatigue influences almost all the included biomechanical parameters, with crucial influence from the exercise intensity and the testing environment. Results indicate an important gap in literature caused by the lack of field studies with continuous measurement during outdoor running activities. To address this gap, we propose recommendations for the use of wearable inertial sensors.

Concurrent Evolution of Biomechanical and Physiological Parameters With Running-Induced Acute Fatigue

“…The goal of this analysis was assessing the association between the running gait parameters and the heart rate dynamics throughout the race. Based on existing results on the influence of acute fatigue on biomechanics, we selected five gait parameterst c , FSA, k vert , v, and a AP (Apte et al, 2021). We decided to include three physiological parameters-BPM as a classical metric, SDNN as the HRV metric, and the commonly used DFAα 1 for HRC (Gronwald and Hoos, 2020;Gronwald et al, 2020b).…”

“…Based on the literature on the influence of acute fatigue (Apte et al, 2021), we selected five gait parameters-t c , FSA, k vert , v, and a AP , and three physiological parameters-BPM, SDNN, DFA-α 1 for association analysis. In addition, we decided to include SD2 a posteriori, because our current findings demonstrated strong trends for the long-range HRC variables (DFA-α 2 , and SD2).…”

“…Since running biomechanical parameters such as contact time, flight time, trunk flexion angle, vertical stiffness, ground reaction forces (GRF), etc. change in response to acute fatigue (Apte et al, 2021), continuous monitoring of these parameters can assist in understanding the effect of fatigue on neuromuscular function (Paquette et al, 2020). While gait spatiotemporal parameters, body segment kinematics, and GRF can be measured directly, vertical stiffness is typically estimated by modeling the running gait as a spring-mass model (Blickhan, 1989;Morin et al, 2005).…”

“…The number of studies on continuous and field monitoring of running-induced acute fatigue remains scarce, despite the recent proliferation of wearable measurement systems and movement analysis algorithms in sports science (Camomilla et al, 2018;Apte et al, 2021). Within these, some studies focused on the classification of fatigued and non-fatigued states using machine learning techniques based on statistical features or composite indices (Eskofier et al, 2012;Buckley et al, 2017;Op De Beéck et al, 2018;Clermont et al, 2019), which preclude the investigation of interpretable biomechanical or cardiovascular parameters.…”

The Role of Water-Based Exercise on Vertical Ground Reaction Forces in Overweight Children: A Pilot Study

“…A simple drawing randomly determined the cadences' order. Each participant performed fifteen stationary running repetitions in each cadence, with a 3 min rest between the repetitions to avoid acute fatigue that could influence the evaluated kinetic parameters [28]. The land protocol was carried out in a room with controlled room temperature between 22 and 26 • C and participants wearing personal sneakers.…”