![Range [min to max] percent mean difference values for GNSS radar or laser agreement reported with a priori
percent agreement thresholds with interpretations. GNSS 5 global navigation satellite system; sp 5 sliding platform; tg 5
timing gates.](https://www.researchgate.net/profile/Patrick-Cormier/publication/374868244/figure/fig12/AS:11431281216101568@1704561057843/Range-min-to-max-percent-mean-difference-values-for-GNSS-radar-or-laser-agreement_Q320.jpg)
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A Systematic Review and Meta-Analysis of Wearable Satellite System Technology for Linear Sprint Profiling: Technological Innovations and Practical Applications
Abstract and Figures
Cormier, P, Meylan, C, Agar-Newman, D, Geneau, D, Epp-Stobbe, A, Lenetsky, S, and Klimstra, M. A systematic review and meta-analysis of wearable satellite system technology for linear sprint profiling: technological innovations and practical applications. J Strength Cond Res XX(X): 000-000, 2023-An emerging and promising practice is the use of global navigation satellite system (GNSS) technology to profile team-sports athletes in training and competition. Therefore, the purpose of this narrative systematic review with meta-analysis was to evaluate the literature regarding satellite system sensor usage for sprint modeling and to consolidate the findings to evaluate its validity and reliability. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, an electronic search of the databases, PubMed and SPORTDiscus (EBSCO), was conducted. Concurrent validity and reliability studies were considered, and 16 studies were retained for the review from the initial 1,485 studies identified. The effects on outcomes were expressed as standardized mean differences (SMDs, Cohen's d) for each outcome (i.e., maximal sprint speed [MSS], the acceleration constant [t], maximal theoretical velocity [V 0 ], relative force [F 0 ], and relative power [P max ]). Effect magnitudes represented the SMD between GNSS-derived and criterion-derived (i.e., radar and laser) and resulted in the following estimates: small for MSS (d = 0.22, 95% CI 0.01 to 0.42), t (d = 0.18, 95% CI 0.60 to 0.23), V 0 (d = 0.14, 95% CI 0.08 to 0.36), relative F 0 (d = 0.15, 95% CI 0.25 to 0.55), and relative P max (d = 0.21, 95% CI 0.16 to 0.58). No publication bias was identified in meta-analyzed studies and moderator analysis revealed that several factors (sampling rate and sensor manufacturer) influenced the results. Heterogeneity between studies was considered moderate to high. This highlighted the differences between studies in sensor technology differences (i.e., sampling rate, sensor fusion, and satellite network acquisition), processing techniques, criterion technology used, sprint protocols, outcome reporting, and athlete characteristics. These findings may be useful in guiding improvements in sprint modeling using GNSS technology and enable more direct comparisons in future research. Implementation of all-out linear sprint efforts with GNSS technology can be integrated into sport-specific sessions for sprint modeling when robust and consistent data processing protocols are performed, which has important implications for fatigue monitoring, program design, systematic testing, and rehabilitation in individual and team sports.
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... When the studies are examined, it is seen that they are mostly done on team sports [45][46][47][48][49] and runners [50][51][52][53][54]. When we look at the use of wearable technology in sports sciences, it is seen that performance tracking and analysis [45,49,51,[53][54][55][56][57][58] are the primary reasons for preference. ...
Wearable technology Sports Today, wearable monitoring systems created thanks to technological advances are integrated into the human body and are widely used in many fields from sports to health. These systems, in which multiple disciplines work together simultaneously, provide physiological and biochemical data, enabling the determination of the current situation and the creation of appropriate performance and improvement programs for individuals. In this review study, 23 articles, 4 of which were review articles, published in the Sports Sciences category on the Web of Science database in 2024 were examined using the keywords "wearable technology" and "sports". As a result of the review of these articles, it was determined that 8 articles were not related to the subject of wearable technologies in sports and were removed from the review (19 articles were included in the study). When studies on wearable technology in the field of sports sciences are examined, most studies are conducted on runners, and performance monitoring and injury prevention are among the main reasons for using this innovative technology. Considering the increasing technological developments, it is evaluated that the studies in this field will increase in parallel with this development and will make great contributions to the field of sports sciences.
... A filter was applied to the raw GNSS velocity data to enhance interpretability by smoothing the variations in velocity-time profiles caused by observed withinstep velocity fluctuations and inherent noise (6). Although filtering has been shown to improve the validity of velocity measurements, there is currently no consensus on the optimal filtering/smoothing process, especially considering differing GNSS unit parameters (i.e., sample rate) (12). Therefore, the "smooth.spline" ...
Dennison, L, Duthie, GM, Ehrmann, F, and Psarakis, MA. Concurrent validity and interunit reliability of 25-Hz GNSS units for profiling sprinting performance. J Strength Cond Res XX(X): 000-000, 2024-Profiling sprint performance by assessing within-race velocity or time is crucial for understanding an athlete's capabilities and identifying areas for improvement. While traditional gold standard systems provide valid and reliable measurements, they are often costly, laboratory-based, or impractical for field-based settings. New Global Navigation Satellite System (GNSS) units (25 Hz) with higher sampling rates may address some of these limitations. The purpose of the project was to evaluate the concurrent validity and interunit reliability of 25-Hz GNSS units by examining their agreement with laser devices and timing gates for velocity measurements and sprint/interval times. Concurrent validity was assessed during a real track and field training session. Thirty subjects each completed 3 to 6 maximal 40-meter sprints, for a total of 106 sprints, while being assessed simultaneously through all systems. Interunit reliability was assessed by placing 3 GNSS units on a motor vehicle and completing 60 accelerations from 0 to 60 m. Low mean bias (<1%) and typical error less than <2% for all measurements demonstrate excellent agreement between GNSS and criterion devices. The units demonstrated good reliability for the 0-10 m interval time (intraclass correlation coefficient [ICC] = 0.86), excellent reliability for all remaining 10 m to 60 m intervals (ICC = 0.91-0.99), sprint times 0-60 m (ICC = 0.97), and maximal sprint velocity (ICC = 1.0). These GNSS units provide an efficient and feasible alternative to traditional measurement devices. For coaches, this technology offers a scalable method to concurrently assess the sprint performances of multiple athletes during training and competitions, enabling evidence-based decisions to guide athletic development.
... Further, a tactically proficient Table 7 Conditioning format types based on HIIT recommendations compared with the ball-in-play demands of women's rugby sevens measures of training load, such as ratings of perceived exertion (RPE) and training duration to capture the internal load (session RPE) (42) and subjective measures that include subscales to monitor nontraining stress, fatigue, physical recovery, health, and well-being as the athletes' response to training (84). Monitoring external load is desirable; however, monitoring external load accurately may be challenging depending on the university's budget and staffing, limiting access to technologies like GNSS units, which are ideal for quantifying external load during training and competition (8,29,30,32). Concerning the subjective questionnaire results, reporting standardized scores such as z-scores may be useful to ascertain whether the athlete is feeling better or worse than normal. To minimize time lost because of injury periods, it is important to track injury occurrence and severity (injury burden) to introduce preventative measures and continuously assess training intervention effectiveness (98). ...
With increasing investments and resources, rugby sevens is growing internationally and domestically in many countries. Within Canada, women's rugby sevens is a popular sport at the regional and national levels in university settings and centralized training programs. Given the importance of strength and conditioning for success in sevens, the purpose of this article is to highlight some of the frameworks used to develop sevens athletes from the university to the international level within the Canadian context. As such, the match demands and physical characteristics relevant to rugby sevens are discussed based on a comprehensive needs analysis. This is further contextualized by a training philosophy and framework tailored for university-aged female athletes, which play a key role in the Canadian talent development pathway.
... Several methods assess sensor physical characteristics, including dose-response curves, Modulation Transfer Function (MTF), and Detective Quantum Efficiency (DQE). The dose-response curve evaluates sensitivity and contrast, while MTF measures resolution as a function of spatial frequency [21,28]. A study in this review found that the CDR wireless sensor's sensitivity and contrast matched the wired CDR sensor's [21], confirming previous research [29]. ...
Radiography facilities face challenges with the positioning of digital radiography detectors. This study evaluates the image quality, radiation dose, and patient comfort associated with wireless sensors in digital radiography. A systematic exploration was performed across PubMed/MEDLINE, EMBASE, SCOPUS, Web of Science, and SCIELO. Nine papers met the eligibility criteria, including three observational studies with 111 patients, four in vitro experiments with 258 extracted human teeth, and two ex vivo investigations with 16 cadaver mandibles. All studies consistently reported high-quality images produced by wireless sensors. Two studies demonstrated the superiority of wireless sensors, one found comparable accuracy with conventional radiography, and another indicated similar image quality among the sensors. Both wireless and wired sensors significantly reduced radiation doses compared to conventional X-rays. The Visual Analog Scale (VAS) did not reveal a clear superiority of wireless over wired sensors, though both were generally less comfortable than traditional film. The wireless sensors consistently produce high-quality images, comparable to or superior to other digital devices. Both wireless and wired sensors significantly reduce radiation doses compared to conventional X-rays, emphasizing their safety and efficacy. Patient comfort levels vary, with neither sensor type showing clear superiority over the other, and both being less comfortable than traditional film.
... This shift is supported by methodological advancements that have improved the detection and quantification of heterogeneity, enabling a more nuanced interpretation and understanding of its implications. There are several good examples of assessing the heterogeneity, e.g., (Alhasan et al., 2023;Bhattacharjee & Khan, 2023;Chen et al., 2023;Cormier et al., 2023;Dong et al., 2023;Huang et al., 2023;Mokhtari-Ardekani, 2023;Pereira et al., 2023;Rahmani, Fayyazishishavan, et al., 2023;Salazar de Pablo et al., 2023;Varhlunchungi et al., 2023;Zhang et al., 2023). ...
The aim of this study was to determine the minimum playing time in matches required to produce reliable acceleration – speed (AS) profiles from global navigation satellite system (GNSS) data. The playing time of 25 professional rugby union players was recorded using GNSS technology and segmented into four sections from 40, 80, 120 and 160 minutes of play. For each interval, the impact of integrating new match data on the AS profile was assessed, aiming to identify the saturation point where additional data did not induce significant changes in the profile outputs. A repeated measures ANOVA and Bonferroni post-hoc tests were applied to examine the variations of AS profile between time intervals. This led to identify the saturation point for assessing “robust” values of theoretical maximum acceleration (A0) and maximum speed (S0). A substantial lack of significant effect was observed for A0 (p = 1.00) and S0 (p = 0.99) in the section of 160 minutes, with an intra-subject variability of 1.50 and 1.20% for A0 and S0, respectively. Determining AS profiles for rugby players is essential for monitoring performance in training and match contexts. Our findings indicate that an equivalent of two full rugby union matches is required to generate a reliable AS profile.
The purpose of this article is to provide practitioners with a system to categorize
and individualize training prescription from sprint force-velocity (F-v) profiles to enhance performance in team and individual sport athletes. Despite F-v variables presenting key information about the underpinning mechanisms contributing to sprint performance, the overall data interpretation may be limited for the practitioner
to implement applied training interventions compared with the researcher. Therefore, this article provides a conceptual framework for appropriate training prescriptions based on individual biomechanical and technical characteristics contributing to sprint performance.
Attempting to build a house without a blueprint could result in a fundamentally unsound structure. A thorough investigation of a building's foundation is essential to assess its quality and fitness for purpose. This is also true of literature reviews which should be constructed on the foundation of a well-developed methodology that clearly outlines the search strategy, inclusion/exclusion criteria, sources of literature, and information synthesis techniques employed to develop the arguments and conclusions presented to the reader. This research note outlines a systematic-narrative hybrid strategy that can be incorporated into a literature review manuscript without overburdening the reader with unnecessary detail.
To directly compare five commonly used on-field systems (motorized linear encoder, laser, radar, global positioning system, and timing gates) during sprint acceleration to (i) measure velocity–time data, (ii) compute the main associated force–velocity variables, and (iii) assess their respective inter-trial reliability. Eighteen participants performed three 40 m sprints, during which five systems were used to simultaneously and separately record the body center of the mass horizontal position or velocity over time. Horizontal force–velocity mechanical outputs for the two best trials were computed following an inverse dynamic model and based on an exponential fitting of the position- or velocity-time data. Between the five systems, the maximal running velocity was close (7.99 to 8.04 m.s−1), while the time constant showed larger differences (1.18 to 1.29 s). Concurrent validity results overall showed a relative systematic error of 0.86 to 2.28% for maximum and theoretically maximal velocity variables and 4.78 to 12.9% for early acceleration variables. The inter-trial reliability showed low coefficients of variation (all < 5.74%), and was very close between all of the systems. All of the systems tested here can be considered relevant to measure the maximal velocity and compute the force–velocity mechanical outputs. Practitioners are advised to interpret the data obtained with either of these systems in light of these results.
This study evaluated the validity and reliability of common systems to assess sprint-derived horizontal force-velocity-power (FVPH) profile metrics. Two double constellation (GPS/GNSS) athlete monitoring systems (STATSports Apex, Catapult Vector S7) and one timing gate system were compared to a criterion (radar gun) for the computation of FVPH profiling metrics. Inter-system validity was assessed using Intraclass, Pearson Correlation Coefficients (ICC, and R2), and Bland-Altman plots with absolute and percent agreement bias. Intra-system reliability was assessed with agreement bias and ICC. STATSports demonstrated moderate agreement for F0, Pmax, τ and Drf (8.62, 6.46, -9.81 and 9.96%), and good agreement for V0 and MSS (-2.18 and -1.62%). Catapult displayed good agreement across all metrics (F0, V0, Pmax, MSS, τ, and Drf: -0.96, -0.89, -1.85, -0.84, 0.38, and -0.27% respectively). Timing gates demonstrated good agreement with V0 and MSS (-2.62 and -1.71%) and poor agreement with F0, Pmax, τ, and Drf (19.17, 16.64, -20.49, and 20.18%). Intra-system reliability demonstrated good agreement (<2% bias) with very large to near perfect ICC (0.85-0.97) for Catapult and STATSports systems. Overall, GPS/GNSS 10Hz technology are reliable across devices and can provide moderate to good accuracy of FVPH profile metrics in single maximal effort sprints. However, Catapult provided better agreement for more FVPH profile metrics than STATSports which may be related to differences in proprietary algorithms. Also, modeling timing gate data using current FVPH profiling techniques result in poor bias that requires greater investigation. GPS/GNSS data can be used for FVPH profiling which could inform performance and rehabilitation processes.
Purpose:
The aims of this study were to (1) assess the concurrent validity of global positioning systems (GPSs) against a radar device to measure sprinting force-velocity (F-v) profiles and (2) evaluate the interunit reliability of 10-Hz GPS devices (Vector S7, Catapult Innovations).
Methods:
Sixteen male elite U18 rugby union players (178.3 [7.6] cm; 78.3 [13.2] kg) participated. Two 50-m sprints interspersed with at least 5 minutes of recovery were completed to obtain input (maximal sprint speed and acceleration time constant τ) and output (theoretical maximal horizontal force, sprinting speed, and horizontal power) F-v profile variables. Sprint running speed was concurrently measured with a radar and 2 GPS units placed on the upper back of each player. Concurrent validity and interunit reliability analyses were performed.
Results:
Moderate to nearly perfect correlations were observed between radar and GPS-derived F-v variables, with small to large typical errors. Trivial to small coefficients of variation were found regarding the GPS interunit reliability.
Conclusion:
The GPS devices tested in this study represent a valid and reliable alternative to a radar device when assessing sprint acceleration F-v profiles in team-sport players.
Seeking to obtain a competitive advantage and manage the risk of injury, team sport organisations are investing in tracking systems that can quantify training and competition characteristics. It is expected that such information can support objective decision-making for the prescription and manipulation of training load. This narrative review aims to summarise, and critically evaluate, different tracking systems and their use within team sports. The selection of systems should be dependent upon the context of the sport and needs careful consideration by practitioners. The selection of metrics requires a critical process to be able to describe, plan, monitor and evaluate training and competition characteristics of each sport. An emerging consideration for tracking systems data is the selection of suitable time analysis, such as temporal durations, peak demands or time series segmentation, whose best use depends on the temporal characteristics of the sport. Finally, examples of characteristics and the application of tracking data across seven popular team sports are presented. Practitioners working in specific team sports are advised to follow a critical thinking process, with a healthy dose of scepticism and awareness of appropriate theoretical frameworks, where possible, when creating new or selecting an existing metric to profile team sport athletes.
This study aimed to (1) compare "in-situ" monitored acceleration-speed (ASin-situ) profile metrics from training/competition data in elite female soccer players to similar metrics from profiles developed from isolated maximal sprint efforts (ASsprint) and; (2) compare the confidence interval (CI) and a Tukey boxplot (BP) outlier removal technique on the training/competition data to derive ASin-situ profiles. Fifteen national team soccer players participated in a 4-week camp while wearing 10 Hz GNSS units. Towards the middle of the camp, 2 × 40 m isolated maximal sprints were performed. ASin-situ profiles (theoretical maximum acceleration A0 in m∙s-2 and speed S0 in m∙s-1) were computed using the CI and BP techniques with training/competition data. The sprint data were modelled separately to construct horizontal force-velocity (FV) profiles, from which ASsprint profiles were derived. Bland-Altman analysis was used to assess agreement between the CI- and BP-derived ASin-situ profiles to the ASsprint profiles, as well as regression analysis for systematic and proportional bias. Additionally, 1-way ANOVAs with Tukey posthoc compared the metrics between each method of analysis. Using the BP method, good agreement of the ASin-situ with ASsprint profile metrics A0/S0 was displayed, whereas good to moderate agreement was shown for the CI. The CI technique showed a proportional bias for A0/S0. Good to excellent intertrial reliability was demonstrated for isolated sprint metrics. Both BP and CI techniques provided comparable ASin-situ profiles to ASsprint profiles. This current research demonstrated that ASin-situ profiling is applicable in elite women's soccer and will have further application in many team sports.
The aims of this study were to describe differences in the acceleration-speed (A-S) profile in-situ and to assess the week-to-week reliability of the A-S profile in-situ over a given training cycle of elite youth soccer players, in relation to the number of sessions included and analyse the effect of the inclusion or not of a specific sprint session. In this retrospective study, 18 male elite U19 football players (179.4 ± 7.1 cm; 69.0 ± 9.5 kg) participated. GPS data collected from three consecutive typical training weeks were used to calculate different combinations of A-S profile in-situ variables (theoretical maximal acceleration [A0], theoretical maximal speed [S0] and the slope of the acceleration-speed [ASslope]). The number (and content) of sessions affected mainly S0 while A0 remained similar with or without a sprint session. The reliability of the A-S profile in-situ is more related to the spread of points rather than a specific number of sessions (and thus points) and was improved when a high percentage of maximum speed (i.e. ≥ 95%) was reached. The present study showed low week-to-week variability for A0, S0 and ASslope. However, practitioners need to make sure that the values cover a sufficient range of raw data [20-95% of maximum speed] to build a clear and consistent linear regression, and in turn extrapolate meaningful A-S profile values.
This short communication considers the calculation of player speed from tracking data. Whereas there are many player tracking systems, all rely on the collection of Cartesian coordinates corresponding to the players on the pitch. From these Cartesian coordinates, there are many ways that one could approximate player speed and acceleration. We introduce some simple principles from exploratory data analysis, which help yield more reliable speed calculations. The general principles are illustrated on various player tracking systems.
The application of acceleration and deceleration data as a measure of an athlete's physical performance is common practice in team sports. Acceleration and deceleration are monitored with athlete tracking technologies during training and games to quantify training load, prevent injury and enhance performance. However, inconsistencies exist throughout the literature in the reported methodological procedures used to quantify acceleration and deceleration. The object of this review was to systematically map and provide a summary of the methodological procedures being used on acceleration and deceleration data obtained from athlete tracking technologies in team sports and describe the applications of the data. Systematic searches of multiple databases were undertaken. To be included, studies must have investigated full body acceleration and/or deceleration data of athlete tracking technologies. The search identified 276 eligible studies. Most studies (60%) did not provide information on how the data was derived and what sequence of steps were taken to clean the data. Acceleration and deceleration data were commonly applied to quantify and describe movement demands using effort metrics. This scoping review identified research gaps in the methodological procedures and deriving and cleaning techniques that warrant future research focussing on their effect on acceleration and deceleration data.