Athlete Monitoring Research Articles

Training Model for Extended Career Athletes: A Narrative Review.

Today's elite and professional sports tend to feature older, more seasoned athletes, who have longer sporting careers. As advancing age can potentially limit peak performance, balancing training load is necessary to maintain an optimal state of performance and extend their sports career. To describe an appropriate training model for extended career athletes. Medline (PubMed), SPORTDiscus, ScienceDirect, Web of Science, and Google Scholar. A search of the literature between January 1, 2015 and November 22, 2023 was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Narrative review. Level 4. Data were extracted from studies related to the management of training and performance of athletes with extended and long careers. A total of 21 articles related to extended careers were found. Key themes from these papers included: expertise, biological maturation, and specificity; epidemiology and health; athlete monitoring; strength training; load management and detraining; success management. A training model for extended career athletes should balance the deleterious effects of age with the athletes' knowledge of, and expertise within, the sport. Designing specific training that accommodates previous injuries, training load intolerances, and caters for quality of life after retirement should be key considerations. Load management strategies for athletes with extended careers should include strength training adaptations to minimize pain, load-response monitoring, a broad range of movement, recovery and intensity activities, and the avoidance of large training load peaks and periods of inactivity.

Information Technology Support for Athlete Health Monitoring and Medical Diagnosis

The paper uses WSN to monitor athletes’ medical diagnosis information remotely. The aim is to strengthen the monitoring and management of athletes’ medical diagnosis data. The method of wireless sensor node and IPv6 routing based on IPv6 is proposed. The terminal-to-terminal network structure based on IP can carry long-distance transmission and share athlete medical diagnosis information. The monitoring system’s bottom structure design is realized using Contiki technology. At the same time, it also realizes the data acquisition and management in the monitoring system. The component interface is designed based on TinyOS. The design of the wireless client based on GPSR is completed based on GPSR. This paper uses the VanetMobiSim platform to complete a remote monitoring system’s software development and simulation test based on wireless medical diagnosis information. The results show that this system’s medical diagnosis information covers a wide range, and the information search efficiency is high.

A dual wave structure triboelectric sensor for heart rate and exercise monitoring

Recently, research on wearable devices for physiological exercise monitoring has garnered significant attention. Here, we propose a dual wave-structured triboelectric nanogenerator (DW-TENG) integrated with a cotton cloth, developed for smart running applications. The DW-TENG sensor leverages a flexible wave triboelectric layer composed of polydimethylsiloxane and silicone, with a copper electrode layer between them for sensing. This structure allows for customizable pressure sensitivity by adjusting the silicone hardness. Experimental results show that the DW-TENG achieves a sensitivity of 0.4 V kPa−1, with response and recovery times of 75 and 90 ms, respectively. The sensor effectively measures heart rate changes during various physical activities, including walking, running, and jumping. Electrical performance tests reveal that the DW-TENG’s output is significantly influenced by the silicone hardness, operational frequency, and microstructure height. The DW-TENG sensor demonstrates high durability and stability, maintaining consistent voltage output over 40 000 cycles. This research highlights the potential of the DW-TENG in multifunctional physiological and physical activity monitoring, providing real-time data on respiratory patterns, heart rate, and movement dynamics, thus enhancing athletic training, performance assessment, and health monitoring.

Thermal radiation imaging technology and sensor assisted calculation of sports training technology simulation

With the development of sports training science and technology, the real-time monitoring of athletes’ physical condition and training effect is becoming more and more important. As a non-contact measurement method, thermal radiation imaging technology can capture the changes of athletes’ body surface temperature efficiently and in real time, and provide relevant information about physiological state and performance indicators. This paper discusses the application of thermal radiation imaging technology in sports training to help measure athletes’ physical state and training effect, so as to provide scientific basis for improving training efficiency and reducing sports injuries. In this paper, the high resolution thermal imaging equipment is used to systematically analyze the thermal radiation imaging of athletes, and the physiological index monitoring and data processing technology are combined to dynamically observe the temperature distribution and change characteristics of athletes under different training states. Through comparative analysis, the correlation between the data provided by thermal radiation imaging technology in the training process and the traditional physiological indicators was evaluated. The results show that thermal radiation imaging technology can effectively reflect the heat distribution and local body temperature changes of athletes during training. Compared to traditional physiological feedback data, the technology has significant advantages in quickly identifying excessive fatigue and potential injuries in athletes, especially during high-intensity training, and can provide early warning of associated risks. The application of sensor-assisted measurement system will further enhance the accuracy and effectiveness of sports scientific research and provide important support for athletes’ scientific training and health management.

Design, Calibration and Morphological Characterization of a Flexible Sensor with Adjustable Chemical Sensitivity and Possible Applications to Sports Medicine.

Active life monitoring via chemosensitive sensors could hold promise for enhancing athlete monitoring, training optimization, and performance in athletes. The present work investigates a resistive flex sensor (RFS) in the guise of a chemical sensor. Its carbon 'texture' has shown to be sensitive to CO2, O2, and RH changes; moreover, different bending conditions can modulate its sensitivity and selectivity for these gases and vapors. A three-step feasibility study is presented including: design and fabrication of the electronic read-out and control; calibration of the sensors to CO2, O2 and RH; and a morphological study of the material when interacting with the gas and vapor molecules. The 0.1 mm-1 curvature performs best among the tested configurations. It shows a linear response curve for each gas, the ranges of concentrations are adequate, and the sensitivity is good for all gases. The curvature can be modulated during data acquisition to tailor the sensitivity and selectivity for a specific gas. In particular, good results have been obtained with a curvature of 0.1 mm-1. For O2 in the range of 20-70%, the sensor has a sensitivity of 0.7 mV/%. For CO2 in the range of 4-80%, the sensitivity is 3.7 mV/%, and for RH the sensitivity is 33 mV/%. Additionally, a working principle, based on observation via scanning electron microscopy, has been proposed to explain the chemical sensing potential of this sensor. Bending seems to enlarge the cracks present in the RFS coverage; this change accounts for the altered selectivity depending on the sensor's curvature. Further studies are needed to confirm result's reliability and the correctness of the interpretation.

Metabolic Phenotyping from Whole-Blood Responses to a Standardized Exercise Test May Discriminate for Physiological, Performance, and Illness Outcomes: A Pilot Study in Highly-Trained Cross-Country Skiers

BackgroundThis study used metabolic phenotyping to explore the responses of highly-trained cross-country skiers to a standardized exercise test, which was part of the athletes’ routine testing, and determine whether metabolic phenotyping could discriminate specific physiological, performance, and illness characteristics.MethodsTwenty-three highly-trained cross-country skiers (10 women and 13 men) participated in this study. Capillary whole-blood samples were collected before (at rest) and 2.5 min after (post-exercise) a roller-ski treadmill test consisting of 5–6 × 4-min submaximal stages followed by a self-paced time trial (~ 3 min) and analyzed using mass spectrometry. Performance level was defined by International Ski Federation distance and sprint rankings. Illness data were collected prospectively for 33 weeks using the Oslo Sports Trauma Research Center Questionnaire on Health Problems. Orthogonal partial least squares-discriminant analyses (OPLS-DA) followed by enrichment analyses were used to identify metabolic phenotypes of athlete groups with specific physiological, performance, and illness characteristics.ResultsBlood metabolite phenotypes were significantly different after the standardized exercise test compared to rest for metabolites involved in energy, purine, and nucleotide metabolism (all OPLS-DA p < 0.001). Acute changes in the metabolic phenotype from rest to post-exercise could discriminate athletes with: (1) higher vs. lower peak blood lactate concentrations; (2) superior vs. inferior performance levels in sprint skiing, and (3) ≥ 2 vs. ≤ 1 self-reported illness episodes in the 33-week study period (all p < 0.05). The most important metabolites contributing to the distinction of groups according to (1) post-exercise blood lactate concentrations, (2) sprint performance, and (3) illness frequency were: (1) inosine, hypoxanthine, and deoxycholic acid, (2) sorbitol, adenosine monophosphate, and 2-hydroxyleuroylcarnitine, and (3) glucose-6-phosphate, squalene, and deoxycholic acid, respectively.ConclusionMetabolic phenotyping discriminated between athlete groups with higher vs. lower post-exercise blood lactate concentrations, superior vs. inferior sprint skiing performance, and more vs. less self-reported illnesses. While the biological relevance of the identified biomarkers requires validation in future research, metabolic phenotyping shows promise as a tool for routine monitoring of highly-trained endurance athletes.

Evaluation of high altitude training camps with heart rate recovery and heart rate variability analysis: beneficial effect in elite swimmers.

The available evidence on the impact of altitude training on sports performance is inconclusive. Heart rate variability (HRV) and heart rate recovery (HRR) are among the most frequently used parameters in athletic performance analysis and monitoring. Our study aims to investigate the effect of high altitude training on HRR and HRV, which are reliable predictors of athletic performance. Elite national swimmers were included in the study. Time domain and frequency domain analyzes were performed with the Polar Verity Sense device and Kubios HRV software. HRR were measured at one-minute intervals for the first 15 minutes after peak heart rate, and then recorded at the 20th, 25th and 30th minutes. A significant difference is observed from the beginning to the 11th minute. The P value at 1, 3, 5, 7 and 11 minutes is 0.001, 0.023, 0.032, 0.019 and 0.020, respectively. Similarly, a significant change was observed in delta HRR. Among the HRV parameters, RMSSD, SDNN, Poincaré SD1 and PNS are statistically significant. P values are 0.004, 0.018, 0.024 and 0.013 respectively. High altitude training program has a positive effect on HRV and CRV in elite swimmers. This condition is associated with increased cardiac parasympathetic activity. Time domain analyses have proven to be more beneficial for HRV. HRR and HRV are effective, reliable and inexpensive methods of performance monitoring of elite athletes.

Advances in Intelligent Sports Based on Triboelectric Nanogenerators

In the realm of intelligent sports, the integration of triboelectric nanogenerators (TENGs) marks a transformative approach toward energy sustainability and more advanced athletic monitoring. By leveraging the principle of triboelectricity, TENGs ingeniously convert mechanical energy from athletes’ movements into electrical energy, which offers a green and efficient power solution for wearable technology. This paper presents an innovative study on the application of TENG technology in sports science, with the results illustrating the potential utility of TENGs in revolutionizing the way we monitor, analyze, and enhance athletic performance. Through the development of self-powered wearables and equipment, TENGs facilitate real-time data collection on physiological and biomechanical parameters, ultimately enabling personalized training adjustments and injury prevention strategies. Our findings underscore the dual benefit of TENGs in promoting environmental sustainability by reducing the overall reliance on traditional energy sources and growing the capabilities of intelligent sports systems. This research contributes to the burgeoning field of nano-energy sports applications while setting the stage for future explorations into the optimization of TENG integration in athletic performance enhancement. Finally, the paper concludes by discussing remaining challenges in this area and opportunities for further research.

The Cumulative Impacts of Fatigue during Overload Training Can Be Tracked Using Field-Based Monitoring of Running Stride Interval Correlations.

Integrating running gait coordination assessment into athlete monitoring systems could provide unique insight into training tolerance and fatigue-related gait alterations. This study investigated the impact of an overload training intervention and recovery on running gait coordination assessed by field-based self-testing. Fifteen trained distance runners were recruited to perform 1-week of light training (baseline), 2 weeks of heavy training (high intensity, duration, and frequency) designed to overload participants, and a 10-day light taper to allow recovery and adaptation. Field-based running assessments using ankle accelerometry and online short recovery and stress scale (SRSS) surveys were completed daily. Running performance was assessed after each training phase using a maximal effort multi-stage running test-to-exhaustion (RTE). Gait coordination was assessed using detrended fluctuation analysis (DFA) of a stride interval time series. Two participants withdrew during baseline training due to changed personal circumstances. Four participants withdrew during heavy training due to injury. The remaining nine participants completed heavy training and were included in the final analysis. Heavy training reduced DFA values (standardised mean difference (SMD) = -1.44 ± 0.90; p = 0.004), recovery (SMD = -1.83 ± 0.82; p less than 0.001), performance (SMD = -0.36 ± 0.32; p = 0.03), and increased stress (SMD = 1.78 ± 0.94; p = 0.001) compared to baseline. DFA values (p = 0.73), recovery (p = 0.77), and stress (p = 0.73) returned to baseline levels after tapering while performance trended towards improvement from baseline (SMD = 0.28 ± 0.37; p = 0.13). Reduced DFA values were associated with reduced performance (r2 = 0.55) and recovery (r2 = 0.55) and increased stress (r2 = 0.62). Field-based testing of running gait coordination is a promising method of monitoring training tolerance in running athletes during overload training.

A flexible silicone tube arrangement structure triboelectric nanogenerator for tennis training monitoring

As the Internet of Things (IoTs) rapidly gain popularity, the demand for self-powered flexible electronic devices is continuously rising, particularly in the intelligent sports field. Hence, we introduced a silicone tube-based triboelectric nanogenerator (ST-TENG) designed for mechanical energy harvesting and tennis training monitoring. The ST-TENG, with its innovative tubular structure, effectively harvests low-frequency mechanical energy and converts it into electrical energy. At a working frequency of 6 Hz, the ST-TENG achieved an open-circuit voltage (Voc) of 122.51 V, a short-circuit current (Isc) of 15.05 µA, and a transfer charge (Qsc) of 33.74 nC. The ST-TENG demonstrates high sensitivity and accuracy in capturing subtle motion details, providing comprehensive data on various aspects of an athlete’s performance. The ST-TENG demonstrated excellent responsiveness to pressure and bending, making it suitable for real-time motion monitoring in tennis. Integrating the ST-TENG into the clothing and equipment of tennis players effectively monitored wrist, waist, and foot movements, providing detailed motion data. This research paves the way for developing highly efficient, self-powered wearable sensors that can significantly enhance the accuracy and sustainability of real-time athletic training monitoring.

The Impact of Wearable Technologies on Marginal Gains in Sports Performance: An Integrative Overview on Advances in Sports, Exercise, and Health

Wearable technologies have become increasingly popular in recent years, as athletes and coaches look for ways to gain a competitive edge. These devices can track a variety of metrics, including heart rate, sleep quality, and movement patterns. This information can be used to identify areas for improvement and make small, incremental changes that can lead to significant gains in performance. The purpose of this narrative review is to provide an integrative overview of the literature on the impact of wearable technologies on marginal gains in sports performance. The literature review was conducted using the Scopus, PubMed, and Web of Science databases, and a total of 55 papers were considered eligible. The results of the literature overview suggest that wearable devices can be classified into three main categories. (1) Location-based wearables (LBW) track an athlete’s location and movement, which can be used to analyze training patterns and identify potential injury risks. (2) Biometric wearables (BMW) track physiological data such as heart rate, sleep quality, and body temperature; these data can be used to monitor an athlete’s fitness levels and identify signs of overtraining. (3) Performance wearables (PMW) track performance metrics such as power output, speed, and distance; this information can be used to optimize training programs and track progress over time. For each category, this paper provides the five most important data points measured by each suggested device. Additionally, sport-specific examples are provided for each category based on the literature data. The limitations of wearable devices, such as accuracy, validity, reliability, interpretability, and cost, are also discussed. However, despite these limitations, the results of the literature review suggest that wearable technologies can be a valuable tool for athletes and coaches who are looking to improve performance. Ultimately, this technological evolution in sports science is likely to dramatically change the state of the art in athletic monitoring and sports analytics.

Fabrication and application of wearable ionic polymer metal composite sensors for sports science

Ionic polymer-metal composite (IPMC) sensors were fabricated and investigated for quantifying impact energy in sports applications. Nafion membranes were roughened and electroless plated with gold-platinum electrodes to form IPMCs. When subjected to impacts of varying energies, the IPMCs generated transient voltage spikes whose peak amplitudes and slopes showed exponential relationships with the impact energies. Empirical models were developed correlating the IPMC voltage response features to the impact energies, achieving measurement accuracy within ±10 % RMS error over the tested dynamic range from 0.005 J to 1 J. The IPMC voltage profile was found to depend primarily on the impact energy and resultant strain rate, rather than impactor properties or contact geometry. Proper calibration procedures for each IPMC sensor before deployment were required to account for device-to-device variations. The results demonstrate the potential of IPMC sensors for continuous monitoring of athletes' impacts during sports activities. Further optimization is needed to improve the robustness, repeatability, and stability of the IPMC sensors under realistic sports conditions for reliable field performance.

Optimized design of flexible sensors for snow and ice sports characterization and intelligent recognition of training technique movements

Skiing performance is affected by a variety of external factors, and real-time monitoring of skiers' skiing status is very important for improving athletes' skiing technique. There are problems in the training monitoring of snow sports athletes in a wide range of venues, such as difficulty in accurately obtaining the parameters of sports status, lack of quantitative assessment of the training effect, and inability to provide timely feedback. And traditional sensors cannot adapt to cold, humid and other weather conditions, which affects their stability. Traditional sensors can only provide limited motion data and cannot comprehensively evaluate the technical level of skiers. At the same time, it is difficult to provide sufficiently accurate data in complex snowy environments. To address this problem, this study proposes a flexible sensor that can contact with the human body and sense athletes' body postures and movements in real time. By combining the flexible sensor with ice and snow sports equipment, intelligent recognition of athletes' movements can be realized. By monitoring and analyzing athletes' movements in real time, problems can be detected in time and targeted adjustments and training can be carried out. The findings of the experiment demonstrate that the accuracy of the time synchronization model, the time-domain high-pass filtering model, the zero-speed correction model, and the improved zero-speed correction model are, respectively, 97, 94, 92, and 90 when the size of the training set is 800. At the distance of 2000 m, The CF-TENG, H-TENG and CS-TENG response times are 18 ms, 20 ms and 28 ms. The results show that the designed flexible sensors have good performance and can be used in the daily training of cross-country skiing and alpine skiing professional sports teams.

A Review of the Validity and Reliability of Accelerometer-Based Metrics From Upper Back-Mounted GNSS Player Tracking Systems for Athlete Training Load Monitoring.

Dawson, L, Beato, M, Devereux, G, and McErlain-Naylor, SA. A review of the validity and reliability of accelerometer-based metrics from upper back-mounted GNSS player tracking systems for athlete training load monitoring. J Strength Cond Res 38(8): e459-e474, 2024-Athlete load monitoring using upper back-mounted global navigation satellite system (GNSS) player tracking is common within many team sports. However, accelerometer-based load monitoring may provide information that cannot be achieved with GNSS alone. This review focuses on the accelerometer-based metrics quantifying the accumulation of accelerations as an estimation of athlete training load, appraising the validity and reliability of accelerometer use in upper back-mounted GNSS player tracking systems, the accelerometer-based metrics, and their potential for application within athlete monitoring. Reliability of GNSS-housed accelerometers and accelerometer-based metrics are dependent on the equipment model, signal processing methods, and the activity being monitored. Furthermore, GNSS unit placement on the upper back may be suboptimal for accelerometer-based estimation of mechanical load. Because there are currently no feasible gold standard comparisons for field-based whole-body biomechanical load, the validity of accelerometer-based load metrics has largely been considered in relation to other measures of training load and exercise intensity. In terms of convergent validity, accelerometer-based metrics (e.g., PlayerLoad, Dynamic Stress Load, Body Load) have correlated, albeit with varying magnitudes and certainty, with measures of internal physiological load, exercise intensity, total distance, collisions and impacts, fatigue, and injury risk and incidence. Currently, comparisons of these metrics should not be made between athletes because of mass or technique differences or between manufacturers because of processing variations. Notable areas for further study include the associations between accelerometer-based metrics and other parts of biomechanical load-adaptation pathways of interest, such as internal biomechanical loads or methods of manipulating these metrics through effective training design.

Match-related activity profiles of youth female and male football players during World Cup classification tournaments and their relationship to body composition.

The activity profiles of football players during competition can be affected by the athletes' competitive level and sex. However, evidence of this in youth South American athletes is scarce as is the effects of body composition on match activity profiles. Therefore, the present study compared the activity profiles of Chilean under-20 (U20) and under-17 (U17) male and female teams during the World Cup qualification tournaments (WC) using a multicomponent athlete monitoring system and explored the relationships between these profiles and the players' body composition. Athlete's body composition was measured as there were total distance, distance covered at different velocities, explosive efforts, sprints, and estimated player load (PL) during the 2018-2019 World Cup Qualifiers. Males had greater muscle and lower fat mass than females and covered 10.8% more total distance with maximal speed being 15.3% faster in match play (P<0.05). However, females covered more distance at higher running speeds and had a greater number of sprints (P<0.05). For males, the U20 club was 3.7% faster and performed 26.3% more explosive efforts than the U17 club (P<0.05). Contrastingly, the female U17 club covered more total distance, more distance at different speeds had more total sprints, greater PL, and muscle mass than the U20 club (P<0.05). Across all athletes, fat mass correlated negatively to total distance (R=-0.39; P=0.001), while muscle mass correlated positively with maximal speed (R=0.72; P=0.001). Gender, competitive level, and body composition seem to affect match-activity profiles in football players during WC qualifiers.

The effect of football heading on sidestep cutting biomechanics

Heading is an integral part of football, with ~20 headers or aerial duels executed per game to intercept, pass or score. However, concerns have recently been raised about the potential short and long-term health impacts of repeated heading. There is evidence suggesting increased risks of sub-concussive trauma – head impacts that do not result in obvious symptoms of concussion but affect cognition and motor function (Montenigro et al., 2017, J Neurotra, 34, 328-340). Repeated heading has been demonstrated to alter brain-muscle communication and affect movement control (Parr et al., 2023, Front Hu Neuro, 17, 1145700) and mechanics of simple tasks such as jumping (Lapointe et al., 2018, Int J Psychophys, 132, 93-98). However, whether these observed cognition and motor impairments translate to the biomechanics of complex multidirectional sport-specific movements such as sidestep cutting is not known. This is an important area to understand because sidestep cutting, an acute change of direction which is ubiquitous in football, is an important performance-determining factor and also a common inciting event for lower-limb injuries (Alentorn-Geli et al., 2009, Knee Sur Sports Trauma, Arth, 17, 705-729) such as the anterior cruciate ligament (ACL) rupture. Due to its propensity to generate high multiplanar knee joint loading during the stance phase of the manoeuvre (Dempsey et al., 2009, Am J Sports Med, 37, 2194-2200), there are often high stresses on the lower limbs which can result in musculoskeletal injury. To date, a copious number of studies have analysed the biomechanics of the sidestep cutting manoeuvre, showing that knee loading is sensitive to the constraints and strategies used to manoeuvre (Dos’Santos et al., 2019, Strength Cond J, 41, 40-54). Accordingly, this present study aims to determine whether there is an effect of repeated heading on sidestep-cutting biomechanics and, if so, the nature of this effect. Participants (n=40) will perform reactive and pre-planned sidestep cutting manoeuvres before completing 15 virtual (n=20) or physical (n=20) ball-heading. They will then repeat the cutting tasks immediately after the bout of heading. Whole-body optical motion capture, ground reaction forces, tri-planar lower-limb joint angles and moments during the stance phase will be analysed to test the effects of football heading on sidestep cutting biomechanics. Results may indicate whether exposure to football heading is a potential risk factor for lower-limb/ACL injury and thus inform the development of training sessions, athlete monitoring, and organisational/national heading guidance and policy for matches and training.

Training load monitoring and wellness tracking of student athletes

The evolution of Strength and Conditioning (S&amp;C) has been significant in enhancing athletic performance, especially with a more recent shift in considering holistic athlete wellness which encompasses physical, emotional, and psychological aspects. Understanding the multifaced nature of athlete wellness allows an insight into the holistic wellbeing of athletes. Despite this, student-athletes are an understudied population who face unique challenges due to academic pressures, financial challenges, and intense training schedules in contrast to the established professional athlete. This study aims to investigate the correlation between S&amp;C training loads and various wellness metrics (sleep quality, muscle soreness, mood and educational stress) in student athletes. Understanding how student athlete wellness varies over the academic year allows S&amp;C coaches to tailor training loads to better compliment wellness and improve psychological, physical wellbeing and ultimately athletic performance. With institutional ethics approval from University of Derby, a mixed methods approach was adopted using an online questionnaire which 50 student athletes filled out multiple times a day over the academic year. Sports included were men’s &amp; women’s volleyball, badminton and men’s futsal. Data collected by the survey included sleep duration and quality, muscle soreness ratings, mood surveys, illness reports, training load measurements, stress and anxiety evaluations. This comprehensive data set enables a detailed analysis of trends over time. It is anticipated that the study will reveal significant relationships between training loads and various wellness indicators. Specific trends, such as the impact of academic stress on training effectiveness or the role of sleep quality in recovery and performance, are expected to emerge. These insights will provide valuable information for tailoring S&amp;C programs to better support student athletes. Understanding the complex relationship of training loads and wellness in student athletes is crucial for optimising their performance and overall well-being. This study aims to contribute to a more intricate understanding of these relationships, informing the development of more effective, individualised training and wellness strategies. Ultimately, the research will provide an understanding for the importance of a holistic approach in athlete development, considering both physical and psychological aspects for optimal performance enhancement.

Position-Specific Movement Characteristics and Heart Rate Profile of Hearing-Impaired Futsal Players: A Simulated Game Analysis

The aim of this study is to compare the movement characteristics and heart rate (HR) response of hearing-impaired futsal players based on their playing positions during a simulated game. The study involved twelve players from the Turkish Deaf Men's Futsal National Team, and PlayerLoad (PL) metrics such as total PL (PLTOTAL), PL per minute (PL·min⁻¹), peak PL (PLPEAK), low to very high PL bands (PLLOW-PLVHIGH), and external load variables such as acceleration (ACC), deceleration (DEC), explosive efforts (EXPEFF), and right/left change of direction (COD-R, COD-L), were analyzed using inertial movement analysis (IMA). Additionally, the internal load metrics, including minimum, average, and maximum HR (HRMIN, HRAVE, HRMAX), percentage of HRMAX (%HRMAX) and percentage of time spent in different HR zones (HRZONE1 to HRZONE4) were continuously monitored. IMA variables and HR metrics, based on playing position, were analysed with the Kruskal-Wallis H test. Group comparisons were conducted using the Mann-Whitney U test, and Bonferroni correction was applied. As a result, PL variables change with notable distinctions between defenders and wingers. Additionally, the PLVHIGH stands out as the only significant difference when comparing wingers and pivots. Wingers generally exhibit different external load, including ACC and COD-L, compared to defenders. Additionally, differences were observed in COD-L between pivots and defenders, as well as in COD-R between pivots and wingers. In conclusion, external and internal load metrics during the simulated game vary depending on the players’ positions in hearing-impaired futsal players, highlighting the importance for coaches to consider this diversity in their athlete monitoring approaches.

Validation of Step Detection and Distance Calculation Algorithms for Soccer Performance Monitoring.

This study focused on developing and evaluating a gyroscope-based step counter algorithm using inertial measurement unit (IMU) readings for precise athletic performance monitoring in soccer. The research aimed to provide reliable step detection and distance estimation tailored to soccer-specific movements, including various running speeds and directional changes. Real-time algorithms utilizing shank angular data from gyroscopes were created. Experiments were conducted on a specially designed soccer-specific testing circuit performed by 15 athletes, simulating a range of locomotion activities such as walking, jogging, and high-intensity actions. The algorithm outcome was compared with manually tagged data from a high-quality video camera-based system for validation, by assessing the agreement between the paired values using limits of agreement, concordance correlation coefficient, and further metrics. Results returned a step detection accuracy of 95.8% and a distance estimation Root Mean Square Error (RMSE) of 17.6 m over about 202 m of track. A sub-sample (N = 6) also wore two pairs of devices concurrently to evaluate inter-unit reliability. The performance analysis suggested that the algorithm was effective and reliable in tracking diverse soccer-specific movements. The proposed algorithm offered a robust and efficient solution for tracking step count and distance covered in soccer, particularly beneficial in indoor environments where global navigation satellite systems are not feasible. This advancement in sports technology widens the spectrum of tools for coaches and athletes in monitoring soccer performance.

Athlete monitoring perspectives of sports coaches and support staff: A scoping review

Objectives To map and summarise the sports coaches’ and support staff's perspectives on athlete monitoring to explore the breadth of literature, identify knowledge gaps and inform future research. Design Scoping review based on the Joanna Briggs Institute (JBI) methodology. Methods SPORTDiscus, MEDLINE, APA PsycInfo, and Embase databases were searched in English until 6 September 2022. The inclusion criteria were (1) coach(es) and/or support staff were explicitly questioned about their knowledge, perceptions, understanding, opinions, and/or applied practice of athlete monitoring; (2) results could be directly attributed to coach(es) and/or support staff; (3) primary research projects that are available as full-text. Exclusion criteria were applied for grey literature. The data were extracted into a custom-made data charting spreadsheet. Results From the 4381 identified records, 42 met the eligibility criteria. Almost all the studies were conducted within the Anglosphere and at the national or international level. The main reasons for coaches and support staff to implement athlete monitoring were to reduce injury and illness, inform the training program, and improve or maintain performance. While training load monitoring is generally seen as valuable the coaches and support staff acknowledged that there was no perfect scientific approach to monitoring athletes and believed it should be part of the bigger picture, emphasising communication. Conclusions There has been a recent surge in research demonstrating that athlete monitoring extends beyond quantitative information and encompasses non-quantified subjective information. This further substantiates that coaches and support staff will remain central to athlete monitoring, even amidst the anticipated technological progress.