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      Assessment of Biomechanical Response to Fatigue through Wearable Sensors in Semi-Professional Football Referees

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          Abstract

          Quantifying muscle fatigue is a key aspect of everyday sport practice. A reliable and objective solution that can fulfil this task would be deeply important for two main reasons: (i) it would grant an objective indicator to adjust the daily training load for each player and (ii) it would provide an innovative tool to reduce the risk of fatigue-related injuries. Available solutions for objectively quantifying the fatigue level of fatigue can be invasive for the athlete; they could alter the performance or they are not compatible with daily practice on the playground. Building on previous findings that identified fatigue-related parameters in the kinematic of the counter-movement jump (CMJ), this study evaluates the physical response to a fatigue protocol (i.e., Yo-Yo Intermittent Recovery Test Level 1) in 16 football referees, by monitoring CMJ performance with wearable magneto-inertial measurement units (MIMU). Nineteen kinematic parameters were selected as suitable indicators for fatigue detection. The analysis of their variations allowed us to distinguish two opposites but coherent responses to the fatigue protocol. Indeed, eight out of sixteen athletes showed reduced performance (e.g., an effective fatigue condition), while the other eight athletes experienced an improvement of the execution likely due to the so-called Post-Activation Potentiation. In both cases, the above parameters were significantly influenced by the fatigue protocol ( p < 0.05), confirming their validity for fatigue monitoring. Interesting correlations between several kinematic parameters and muscular mass were highlighted in the fatigued group. Finally, a “fatigue approximation index” was proposed and validated as fatigue quantifier.

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          Monitoring Training Load to Understand Fatigue in Athletes

          Many athletes, coaches, and support staff are taking an increasingly scientific approach to both designing and monitoring training programs. Appropriate load monitoring can aid in determining whether an athlete is adapting to a training program and in minimizing the risk of developing non-functional overreaching, illness, and/or injury. In order to gain an understanding of the training load and its effect on the athlete, a number of potential markers are available for use. However, very few of these markers have strong scientific evidence supporting their use, and there is yet to be a single, definitive marker described in the literature. Research has investigated a number of external load quantifying and monitoring tools, such as power output measuring devices, time-motion analysis, as well as internal load unit measures, including perception of effort, heart rate, blood lactate, and training impulse. Dissociation between external and internal load units may reveal the state of fatigue of an athlete. Other monitoring tools used by high-performance programs include heart rate recovery, neuromuscular function, biochemical/hormonal/immunological assessments, questionnaires and diaries, psychomotor speed, and sleep quality and quantity. The monitoring approach taken with athletes may depend on whether the athlete is engaging in individual or team sport activity; however, the importance of individualization of load monitoring cannot be over emphasized. Detecting meaningful changes with scientific and statistical approaches can provide confidence and certainty when implementing change. Appropriate monitoring of training load can provide important information to athletes and coaches; however, monitoring systems should be intuitive, provide efficient data analysis and interpretation, and enable efficient reporting of simple, yet scientifically valid, feedback.
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            The Yo-Yo Intermittent Recovery Test

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              Epidemiology of muscle injuries in professional football (soccer).

              Muscle injuries constitute a large percentage of all injuries in football. To investigate the incidence and nature of muscle injuries in male professional footballers. Cohort study; Level of evidence, 2. Fifty-one football teams, comprising 2299 players, were followed prospectively during the years 2001 to 2009. Team medical staff recorded individual player exposure and time-loss injuries. The first-team squads of 24 clubs selected by the Union of European Football Associations as belonging to the best European teams, 15 teams of the Swedish First League, and another 15 European teams playing their home matches on artificial turf pitches were included. A muscle injury was defined as "a traumatic distraction or overuse injury to the muscle leading to a player being unable to fully participate in training or match play." In total, 2908 muscle injuries were registered. On average, a player sustained 0.6 muscle injuries per season. A squad of 25 players can thus expect about 15 muscle injuries per season. Muscle injuries constituted 31% of all injuries and caused 27% of the total injury absence. Ninety-two percent of all muscle injuries affected the 4 major muscle groups of the lower limbs: hamstrings (37%), adductors (23%), quadriceps (19%), and calf muscles (13%). Sixteen percent of the muscle injuries were reinjuries. These reinjuries caused significantly longer absences than did index injuries. The incidence of muscle injury increased with age. When separated into different muscle groups, however, an increased incidence with age was found only for calf muscle injuries and not for hamstring, quadriceps, or hip/groin strains. Muscle injuries are a substantial problem for players and their clubs. They constitute almost one third of all time-loss injuries in men's professional football, and 92% of all injuries affect the 4 big muscle groups in the lower limbs.
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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                24 December 2020
                January 2021
                : 21
                : 1
                : 66
                Affiliations
                [1 ]The BioRobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy; michelangelo.guaitolini@ 123456santannapisa.it (M.G.); a.mannini@ 123456santannapisa.it (A.M.)
                [2 ]Department of Excellence in Robotics & AI, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
                [3 ]TuringSense EU Lab s.r.l., 47121 Forlì, Italy; pietro.garofalo@ 123456turingsense.com
                [4 ]School of Sport and Exercise Sciences, Università di Tor Vergata, 00118 Rome, Italy; castagnac@ 123456libero.it
                [5 ]Italian Football Federation (FIGC) Technical Department, Football Training and Biomechanics Laboratory, 50135 Firenze, Italy
                [6 ]IRCCS Fondazione don Carlo Gnocchi, 50143 Firenze, Italy
                Author notes
                Author information
                https://orcid.org/0000-0003-0760-052X
                Article
                sensors-21-00066
                10.3390/s21010066
                7795543
                33374324
                19b3f0da-302b-4774-9381-638152105d52
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 16 November 2020
                : 21 December 2020
                Categories
                Article

                Biomedical engineering
                fatigue detection,counter-movement jump,wearable inertial sensors,football,biomechanics

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