Revista Tecnología y Ciencia - Universidad Tecnológica Nacional
Año 20 - Número 44 / Mayo - Agosto
DOI:https://doi.org/10.33414/rtyc.44.42-51.2022
Reconocimiento-NoComercial 4.0 Internacional
Presentación: 05/04/2022
Aprobación: 06/06/2022
Markel Rico-González
Department of Didactics of Musical, Plastic and Corporal Expression, University of the Basque Country, UPV-EHU. Leioa - Spain
markeluniv@gmail.com
https://orcid.org/0000-0002-9849-0444
Asier Los Arcos
Society, Sports and Physical Exercise Research Group (GIKAFIT). Department of Physical Education and Sport. Faculty of Education and Sport. University of the Basque Country (UPV/EHU), Vitoria-Gasteiz - Spain
asierlosarcos@gmail.com
https://orcid.org/0000-0003-1001-7706
Alejandro Bastida-Castillo
Faculty of Sports Sciences. University of Murcia, San Javier - Spain
alejandrobastidacastillo@gmail.com
https://orcid.org/0000-0002-8293-4549
José Pino-Ortega
Faculty of Sports Sciences. University of Murcia, San Javier - Spain
pepepinoortega@gmail.com
https://orcid.org/0000-0002-9091-0897
The use of valid, accurate and reliable systems is decisive for ensuring optimal data collection and correct interpretation of values. Among other factors, it seems that sampling rate and the number of nodes determine data accuracy using LPS. Thus, the aim of this study was to assess and compare the accuracy of two UWB configurations (i.e. UWB6_18HZ: 6 antennae and 18 Hz capacity vs. UWB8_33HZ: 8 antennae and 33 Hz capacity) to measure locomotion on court. A healthy and well-trained former soccer player (age: 38 years, mass: 76.34 kg, height 1.85 m) ran 9 m along the middle line of a volleyball court (n=10, samples= 424). UWB6_18HZ and UWB8_33HZ configurations have shown high accuracy in sport movement patterns monitoring (mean difference between actual measurements and UWB = 0.014±0.03m for UWB6_18HZ and 0.013±0.03m for UWB8_33HZ), although UWB8_33HZ presented higher accuracy (8.99±0.03 m) than UWB6_18HZ (8.94±0.03). Therefore, manufacturers should consider future developments based on sampling rates and number of antennae installed around the court.
Keywords: Local Positioning System; Electronic Performance and Tracking System; Technology; sampling frequency; ultra-wide band
El uso de sistemas válidos, precisos y fiables es decisivo para garantizar una recogida de datos óptima y una interpretación correcta de los datos. Entre otros factores, parece que la frecuencia de muestreo y el número de antenas determinan la precisión de los datos utilizando sistemas de posicionamiento local (LPS). Por lo tanto, el objetivo de este estudio fue evaluar y comparar la precisión de dos configuraciones ultra banda ancha (UWB) (UWB6_18HZ: 6 antenas y 18 Hz de capacidad frente a UWB8_33HZ: 8 antenas y 33 Hz de capacidad) para medir los patrones de movimiento en los deportes. Un jugador de fútbol sano y bien entrenado (edad: 38 años, masa: 76,34 kg, altura 1,85 m) corrió 9 m a lo largo de la línea media de una cancha de voleibol (n = 10 recorridos, muestras = 424). Las configuraciones UWB6_18HZ y UWB8_33HZ han mostrado una alta precision (diferencia media entre las mediciones reales y UWB = 0.014 ± 0.03m frente a UWB6_18HZ y 0.013 ± 0.03m para UWB8_33HZ), aunque UWB8_33HZ presentó mayor precisión (8.99 ± 0.03 m_18HZ_18) que UWB6_18HZ (8,94 ± 0,03). Por lo tanto, los fabricantes deben considerar desarrollos futuros basados frecuencias de muestreo y número de antenas instaladas alrededor de la cancha.
Palabras clave: Sistema de posicionamiento local; EPTS; Tecnología; frecuencia de muestreo; ultra-banda ancha
Since the accuracy of Electronic Performance and Tracking Systems (EPTS) (Rico-González, Pino-Ortega, et al., 2020) has gained crucial importance (Rico-González, Arcos, et al., 2020), the validity and reliability of EPTS have been widely assessed (Cummins et al., 2013; Serpiello et al., 2018) and compared (Bastida Castillo et al., 2018a; Bastida-Castillo, Gómez-Carmona, De La Cruz Sánchez, et al., 2019; Dogramaci et al., 2011; Linke et al., 2018). The higher accuracy of Local Positioning Systems (LPS) than the rest of the available tools suggests that the use of these systems will increase in the future (Rico-González, Pino-Ortega, et al., 2020), specifically, the LPS based on ultra-wide band (UWB) (Alarifi et al., 2016; Leser et al., 2011). Ultra-wide band (UWB) uses a set of antennae placed around the court in order to alleviate any satellite reference problems by using time-based positioning techniques (Alarifi et al., 2016).
Technology is continually improving through developments related to microprocessors, data processing, and software. In fact, new models/brands sometimes differ in terms of sampling rates, chip sets, filtering methods, and data processing algorithms (Malone et al., 2017). For these reasons, sports scientists are continuously investigating whether these improvements influence high quality measurements (Malone et al., 2017). Among others, it has been found that the sampling rate capacity influences the accuracy of the reported position of individual players on the pitch (Pons et al., 2019; Rico-González, Arcos, et al., 2020; Rico-González, Los Arcos, et al., 2020; Stevens et al., 2014), but the number of nodes has not yet been assessed in sport. Since GPS are based on quite similar principles to UWB and Jackson et al., (2018) showed significant differences (P <0.05) between different amounts of reference nodes to track positioning, the authors of this study hypothesised that two different numbers of antennae and sampling rate configurations could influence the quality of the data recorded. Therefore, the aim of this study was to assess and compare the accuracy of two UWB configurations: a UWB-based system with 6 antennae and 18 Hz capacity (UWB6_18HZ), and a UWB-based system with 8 antennae and 33 Hz capacity (UWB8_33HZ).
Participants
A healthy and well-trained athlete (age: 38 years, mass: 76.34 kg, height 1.85 m) volunteered to participate in the current investigation. The participant did not present any physical limitations or musculoskeletal injuries that could affect testing. Subject height was measured using a stadiometer (SECA, Hamburg, Germany). Body mass was obtained using a scale (TANITA BC-601, Tokyo, Japan). The study was conducted according to the Declaration of Helsinki and was approved by the Bioethics Commission of the University of Murcia (ID: 2061/2018). The participant was informed of the risks and provided informed written consent.
Procedure
Data acquisition in the present study was carried out on an indoor volleyball court, measuring 18 x 9 m. The participant was equipped with two light-weight (70 g) inertial devices, each measuring 81×45×16 mm, in a custom vest located on the back of the upper torso, fitted tightly to the body, as is typically used in games. The devices were placed in parallel in the custom vest, 2 cm apart and at the same height Although two devices were used simultaneously in the experimental protocol a previous study did not report any problems in UWB-based tracking system accuracy with 28 devices turned on (Bastida Castillo et al., 2018b). The participant ran along the middle line of the court ten times in each direction; with an interval of at least 5 s rest between repetitions (n = 20 trials performed and 424 samples of positioning data). All the tasks started from a standing position. The participant moved according to two criteria: (i) To run only on the lines marked on the volleyball court, and (ii) to reach a speed of >15 km/h where possible. The tests were monitored in real time by S PROTM software to verify that the devices were performing correctly and that the participant achieved the necessary speed in each trial.
Data collection
Study methodology was written following the protocol by Rico-González, Los Arcos et al., (2020) in order to guarantee a precise description of the use of the technology, scoring 21 points out of 23 (91%). The rest of the items cannot be explained as the authors did have not this information.
Positional data on the court were recorded with a time motion tracking system using two inertial measurement units (IMU; WIMU PROTM, RealTrack Systems, Almeria, Spain). Each device had its own internal microprocessor, 2 GB flash memory and a high-speed USB interface, to record, store and upload data. The devices were powered by an internal battery with 4 h of life, had a total weight of 70 g and measured 81x45x16 mm. Each device contains, among others sensors, a 10 Hz GPS and an 18 Hz Ultra-Wide Band (UWB). This model is valid and reliable (Bastida Castillo et al., 2018b), and has International Match Standard (IMS) certification from FIFA. S PROTM software (RealTrack Systems, Almeria, Spain) was used to analyse and export the data of the x- and y- position coordinates (Bastida-Castillo, Gómez-Carmona, De la Cruz-Sánchez, et al., 2019).
Two different systems were compared:
1) A reference system composed of 6 antennae and 18 Hz UWB chipsets (UWB6_18HZ) (Figure 1). In this case, the antennae with UWB technology were fixed 1.5 m from the perimeter line in the corners and 3 m from the middle line of the court, forming a hexagon for better signal emission and reception (Bastida-Castillo, Gómez-Carmona, De la Cruz-Sánchez, et al., 2019).
2) The reference system was composed of 8 antennae and 33 Hz UWB chipsets (UWB8_33HZ) (Figure 2). The position of the antennae was equal, but an antenna was fixed 3 m behind each goal, forming an octagon with the same aim.
UWB6_18HZ |
UWB8_33HZ |
|
Device´s characteristics (same for both configurations) |
||
Technology |
UWB |
|
Weight |
70 g |
|
Size |
81×45×16 mm |
|
Memory |
2 GB Flash memory |
|
Battery |
4 h |
|
Antenna´s height |
3 m |
|
Algorithm |
TOA |
|
Configuration´s differences |
||
Hertz |
18 Hz |
33 Hz |
Nº of antennae |
6 |
8 |
Installation shape |
Figure 1 |
Figure 2 |
Table 1. Configurations’ characteristics
All of the antennae were positioned at a height of 3 m and held by a tripod (Bastida-Castillo, Gómez-Carmona, De la Cruz-Sánchez, et al., 2019). The auto-start process followed the protocol suggested by Reche-Soto et al. (2019). The WIMIPROTM inertial devices were placed in a pocket in a specific custom vest placed between the scapulae at the T2-T4 level and prior to the in-field exercises following previous study protocols (Reche-Soto et al., 2019).
Figure 1. A system with 6 antennae and 18 Hz
Figure 2. A system with 8 antennae and 33 Hz
Unlike other systems, WIMIPROTM inertial devices compute the positioning data in receivers. All the antennae have a common clock and the receiving node calculates positioning data through time difference of arrival (TDOA) of the incoming signal and directly calculates its distance from the transmitter; thus, multiplying the estimated TOA by the speed of light makes it possible to draw a circle with the reference node at its centre and a radius equal to the estimated range. By collecting at least three measurements (triangulation) and intersecting the defined circles, it is possible to determine the position of the receivers with high accuracy. The UWB system was adjusted to the reference field before the start of the investigation by walking round the perimeter of the court carrying one of the devices in one hand so that it recognised this as the reference system (Bastida Castillo et al., 2018b). The number of points was 2 per second = 322 data points. The layout of the court was projected in the software S PROTM (RealTrack Systems, Almeria, Spain), and would later be the reference field in the system. This reference system was very similar to the real measurements of the court (100 x 64 m).
Data processing
To investigate the accuracy of the UWB system for monitoring the player’s positions on the court, the data were transformed into raw positioning data (x and y coordinated) using software (S PRO, RealTrack Sytems, Almeria, Spain). The data were downloaded after the session because data monitored in real time have been shown to be significantly inaccurate relative to the post-session data (Rico-González, Arcos, et al., 2020). Unlike other validity and reliability studies in which optic-based systems have been used as a gold standard (Linke et al., 2018; Ogris et al., 2012), in this study a geographic information system (GIS) was proposed as the reference system (Bastida-Castillo, Gómez-Carmona, De la Cruz-Sánchez, et al., 2019), and does not require any instrument other than a device with software included. The reference system to compare the results was projected in the software using a GIS mapping application. The GIS makes representations of geometrical shapes, such as polygons or circles, with millimetre accuracy. In this way, the routes selected with their real measurements (measured by trundle wheel) were introduced into the previously created template. And then, the x and y coordinate data of the UWB system were introduced and compared. The distance error of each axis was reported. Of all the data entered, only those that corresponded to the execution of the routes were selected, according to recordings obtained using ANT+ technology and photocells at the beginning and end of each test. The protocol to record the beginning and end of the tests was described in a previous study (see study for more information) (Bastida Castillo et al., 2017).
Statistical analysis
Descriptive statistics are presented as mean values ± SD. A Shapiro-Wilk test was performed for the evaluation of normality (assumption) for statistical distribution. Error of measurement was assessed as mean difference between device data and real measures (as criterion reference). The comparison between UWB configurations (UWB6_18HZ and UWB8_33HZ) was analysed using the paired samples Wilcoxon test. Besides, an agreement analysis between the two variables was performed with the Bland & Altman test (Bland & Altman, 1986), and the coefficient of variance (%CV) was calculated as the standard deviation of difference divided by mean and multiplied by 100 (Atkinson & Nevill, 1998). The strength of the CV (<10%) was quantified in accordance with (Atkinson & Nevill, 1998). The statistical analysis was performed using SPSS (Statistics 20.0) for Mac OS Mojave.
Results
When analysing the whole dataset (n=424 distance measures) the mean difference between the real measure and the UWB measure was 0.014±0.03m for UWB6_18HZ and 0.013±0.03m for UWB8_33HZ. Wilcoxon showed a significance difference between them (p<0.001).
Table 1 shows the difference between the raw data recorded by both UWB configurations. The paired samples Wilcoxon test revealed a systematic bias by which the values obtained with UWB6_18HZ tended to be slightly lower than those measured with UWB8_33HZ in comparison to the real values (9 meters).
UWB6_18HZ (M±SD) |
UWB8_33HZ (M±SD) |
Bias ±SD (95%LOA) |
Wilcoxon |
Cohen d |
|
One-way (n=106) |
8.94±0.03 |
8.99±0.03 |
-0.04±0.04 (-0.14 to 0.04) |
P<0.001 |
1.53 |
Return-way (n=106) |
9.02±0.03 |
9.03±0.03 |
-0.007±0.04 (-0.1 to 0.08) |
P<0.05 |
0.30 |
Total way (n=212) |
8.98±0.03 |
9.01±0.03 |
-0.02±0.05 (-0.13 to 0.07) |
P<0.001 |
0.62 |
Table 2. Bland-Altman and Wilcoxon test between raw data recorded by UWB6_18HZ and UWB8_33HZ to measure a 9-metre run. The mean ± SD of both configuration and Bland & Altman results are expressed in meters.
Cohen d revealed higher differences between UWB configuration in one-way situation (1.53). However, a high effect was found in total way (0.62). Finally, all data set reported < 1%CV.
Due to the lack of information that studies report in their method about the use of EPTS, which makes it difficult to compare them, a fundamental survey has been published to summarise what relevant information should be reported in the methodology of studies about the use of tracking systems (Rico-González, Arcos, et al., 2020). The number of antennae and the sampling rates are two of these criteria that researchers should report on the use of UWB in their articles. For this reason, this study was aimed at assessing accuracy comparing movement pattern measurement in sport between two UWB local positioning system configurations with improvements in the amount of reference nodes and sampling rate. The results showed that both UWB6_18HZ and UWB8_33HZ had acceptable accuracy for the measurement of positioning on the court. But, UWB8_33HZ slightly outperformed UWB6_18HZ. So, sampling rate and the number of antennae as a reference of UWB systems should be considered by sport technical staff and researchers when they measure players’ locomotion.
To date, low sampling frequencies have become a main reason for low quality measurement by video based semi-automatic systems and for Global Navigation Satellite Systems (Stevens et al., 2014). Duarte et al., (2010) analysed the impact of the sampling frequency on the outcomes of positional data with a camera-based system, comparing an original data set with different cut-off frequencies (3-Hz and 6-Hz) on the x coordinates of an attacker’s locomotion in a 1vs1 football sub-phase. They found less variation using a 6-Hz than 3-Hz cut-off frequency. Thus, they used the cut-off frequency of 6 Hz to analyse player movement patterns (Duarte et al., 2010). In the same vein, we found greater accuracy in measuring locomotion on the court using UWB8_33HZ than UWB6_18HZ. This suggests that the sampling rate may be the reason for the higher quality measure. However, further studies should evaluate independently the impact of the sampling rate and the number of nodes installed around the court on the accuracy of the measurement (Rico-González, Arcos, et al., 2020). Based on the same principles for positioning calculation between global positioning systems and LPS, it seems that a greater number of reference points for calculation may also provide higher quality measurements (Jackson et al., 2018). Higher accuracy was achieved using more reference points in total distance measurements (GNSS: 997 ± 533 and GPS: 925 ± 499) (Jackson et al., 2018).
Study limits
Since the greater accuracy of a UWB system with 8 antennae and 33 Hz in comparison to a UWB system with 6 antennae and 18 Hz has only been found for linear locomotion, further studies should compare the accuracy of both systems during match conditions in different sports.
Both the UWB6_18HZ and UWB8_33HZ were found to have acceptable accuracy for the measurement of positioning on the court, but UWB833HZ slightly outperformed UWB618HZ. Future studies should corroborate these outcomes in different sports.
Practical Applications
Manufacturers should consider future developments based on sampling rates and number of antennae installed around the court.
Conflict of interest statement
The authors declare that they have no competing financial interests.
Funding
The authors received no potential support for the research, authorship and/or publication of this article.
Alarifi, A.; Al-Salman, A.; Alsaleh, M.; Alnafessah, A.; Al-Hadhrami, S.; Al-Ammar, M., & Al-Khalifa, H. (2016). Ultra Wideband Indoor Positioning Technologies: Analysis and Recent Advances. Sensors, 16(5), 707. https://doi.org/10.3390/s16050707
Atkinson, G., & Nevill, A. M. (1998). Statistical Methods For Assessing Measurement Error (Reliability) in Variables Relevant to Sports Medicine. Sports Medicine, 26(4), 217–238. https://doi.org/10.2165/00007256-199826040-00002
Bastida-Castillo, A.; Gómez Carmona, C. D.; De la Cruz Sánche, E., & Pino Ortega, J. (2018). Accuracy, intra- and inter-unit reliability, and comparison between GPS and UWB-based position-tracking systems used for time-motion analyses in soccer. European Journal of Sport Science, 1–8. https://doi.org/10.1080/17461391.2018.1427796
Bastida-Castillo, A.; Gómez-Carmona, C. D.; Pino Ortega, J., & de la Cruz Sánchez, E. (2017). Validity of an inertial system to measure sprint time and sport task time: A proposal for the integration of photocells in an inertial system. International Journal of Performance Analysis in Sport, 17(4), 600–608. https://doi.org/10.1080/24748668.2017.1374633
Bastida-Castillo, A.; Gómez-Carmona, C. D.; De La Cruz Sánchez, E., & Pino-Ortega, J. (2019). Comparing accuracy between global positioning systems and ultra-wideband-based position tracking systems used for tactical analyses in soccer. European Journal of Sport Science, 19(9), 1157–1165. https://doi.org/10.1080/17461391.2019.1584248
Bastida-Castillo, A.; Gómez-Carmona, C.; De la Cruz-Sánchez, E.; Reche-Royo, X.; Ibáñez, S., & Pino Ortega, J. (2019). Accuracy and Inter-Unit Reliability of Ultra-Wide-Band Tracking System in Indoor Exercise. Applied Sciences, 9(5), 939. https://doi.org/10.3390/app9050939
Bland, J. M., & Altman, DouglasG. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. The Lancet, 327(8476), 307–310. https://doi.org/10.1016/S0140-6736(86)90837-8
Cummins, C.; Orr, R.; O’Connor, H., & West, C. (2013). Global Positioning Systems (GPS) and Microtechnology Sensors in Team Sports: A Systematic Review. Sports Medicine, 43(10), 1025–1042. https://doi.org/10.1007/s40279-013-0069-2
Dogramaci, S. N.; Watsford, M. L., & Murphy, A. J. (2011). The Reliability and Validity of Subjective Notational Analysis in Comparison to Global Positioning System Tracking to Assess Athlete Movement Patterns. Journal of Strength and Conditioning Research, 25(3), 852–859. https://doi.org/10.1519/JSC.0b013e3181c69edd
Duarte, R.; Araújo, D.; Fernandes, O.; Fonseca, C.; Correia, V.; Gazimba, V.; Travassos, B.; Esteves, P.; Vilar, L., & Lopes, J. (2010). Capturing complex human behaviors in representative sports contexts with a single camera. Medicina, 46(6), 408. https://doi.org/10.3390/medicina46060057
Jackson, B. M.; Polglaze, T.; Dawson, B.; King, T., & Peeling, P. (2018). Comparing Global Positioning System and Global Navigation Satellite System Measures of Team-Sport Movements. International Journal of Sports Physiology and Performance, 13(8), 1005–1010. https://doi.org/10.1123/ijspp.2017-0529
Leser, R.; Baca, A., & Ogris, G. (2011). Local Positioning Systems in (Game) Sports. Sensors, 11(10), 9778–9797. https://doi.org/10.3390/s111009778
Linke, D.; Link, D., & Lames, M. (2018). Validation of electronic performance and tracking systems EPTS under field conditions. PLOS ONE, 13(7), e0199519. https://doi.org/10.1371/journal.pone.0199519
Malone, J. J.; Lovell, R.; Varley, M. C., & Coutts, A. J. (2017). Unpacking the Black Box: Applications and Considerations for Using GPS Devices in Sport. International Journal of Sports Physiology and Performance, 12(Suppl 2), 18–26. https://doi.org/10.1123/ijspp.2016-0236
Ogris, G.; Leser, R.; Horsak, B.; Kornfeind, P.; Heller, M., & Baca, A. (2012). Accuracy of the LPM tracking system considering dynamic position changes. Journal of Sports Sciences, 30(14), 1503–1511. https://doi.org/10.1080/02640414.2012.712712
Pons, E.; García-Calvo, T.; Resta, R.; Blanco, H.; López del Campo, R.; Díaz García, J., & Pulido, J. J. (2019). A comparison of a GPS device and a multi-camera video technology during official soccer matches: Agreement between systems. PLOS ONE, 14(8), e0220729. https://doi.org/10.1371/journal.pone.0220729
Reche-Soto, P.; Cardona-Nieto, D.; Diaz-Suarez, A.; Bastida-Castillo, A.; Gomez-Carmona, C.; Garcia-Rubio, J., & Pino-Ortega, J. (2019). Player Load and Metabolic Power Dynamics as Load Quantifiers in Soccer. Journal of Human Kinetics, 13.
Rico-González, M.; Los Arcos, A.; Rojas-Valverde, D.; Clemente, F. M., & Pino-Ortega, J. (2020). A Survey to Assess the Quality of the Data Obtained by Radio-Frequency Technologies and Microelectromechanical Systems to Measure External Workload and Collective Behavior Variables in Team Sports. Sensors, 16.
Rico-González, M.; Los Arcos, A.; Nakamura, F. Y.; Moura, F. A., & Pino-Ortega, J. (2020). The use of technology and sampling frequency to measure variables of tactical positioning in team sports: A systematic review. Research in Sports Medicine, 28(2), 279–292. https://doi.org/10.1080/15438627.2019.1660879
Rico-González, M.; Pino-Ortega, J.; Nakamura, F. Y.; Moura, F. A.; Rojas-Valverde, D., & Los Arcos, A. (2020). Past, present, and future of the technological tracking methods to assess tactical variables in team sports: A systematic review. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, 175433712093202. https://doi.org/10.1177/1754337120932023
Serpiello, F. R.; Hopkins, W. G.; Barnes, S.; Tavrou, J.; Duthie, G. M.; Aughey, R. J., & Ball, K. (2018). Validity of an ultra-wideband local positioning system to measure locomotion in indoor sports. Journal of Sports Sciences, 36(15), 1727–1733. https://doi.org/10.1080/02640414.2017.1411867
Stevens, T. G. A.; de Ruiter, C. J.; van Niel, C.; van de Rhee, R.; Beek, P. J., & Savelsbergh, G. J. P. (2014). Measuring Acceleration and Deceleration in Soccer-Specific Movements Using a Local Position Measurement (LPM) System. International Journal of Sports Physiology and Performance, 9(3), 446–456. https://doi.org/10.1123/ijspp.2013-0340