Vertical jump performance is a commonly used test to measure lower-limb muscle power that is carried out with several types of equipment. The aim of this study was to validate an open-source jump mat (Chronojump Boscosystems) against a proprietary jump mat (Globus Ergo Tester). Sixty-three active...

In sport performance, motion capture aims at tracking and recording athletes’ human motion in real time to analyze physical condition, athletic performance, technical expertise and injury mechanism, prevention and rehabilitation. The aim of this paper is to systematically review the latest developments of motion capture systems for the analysis of sport performance. To that end, selected keywords were searched on studies published in the last four years in the electronic databases ISI Web of Knowledge, Scopus, PubMed and SPORTDiscus, which resulted in 892 potential records. After duplicate removal and screening of the remaining records, 81 journal papers were retained for inclusion in this review, distributed as 53 records for optical systems, 15 records for non-optical systems and 13 records for markerless systems. Resultant records were screened to distribute them according to the following analysis categories: biomechanical motion analysis, validation of new systems and performance enhancement. Although optical systems are regarded as golden standard with accurate results, the cost of equipment and time needed to capture and postprocess data have led researchers to test other technologies. First, non-optical systems rely on attaching sensors to body parts to send their spatial information to computer wirelessly by means of different technologies, such as electromagnetic and inertial (accelerometry). Finally, markerless systems are adequate for free, unobstructive motion analysis since no attachment is carried by athletes. However, more sensors and sophisticated signal processing must be used to increase the expected level of accuracy.Resumen: En el ámbito del rendimiento deportivo, el objetivo de la captura de movimiento es seguir y registrar el movimiento humano de deportistas para analizar su condición física, rendimiento, técnica y el origen, prevención y rehabilitación de lesiones. En este artículo, se realiza una revisión sistemática de los últimos avances en sistemas de captura de movimiento para el análisis del rendimiento deportivo. Para ello, se buscaron palabras clave en estudios publicados en los últimos cuatro años en las bases de datos electrónicas ISI Web of Knowledge, Scopus, PubMed y SPORTDiscus, dando lugar a 892 registros. Tras borrar duplicados y análisis del resto, se seleccionaron 81 artículos de revista, distribuidos en 53 registros para sistemas ópticos, 15 para sistemas no ópticos y 13 para sistemas sin marcadores. Los registros se clasificaron según las categorías: análisis biomecánico, validación de nuevos sistemas y mejora del rendimiento. Aunque los sistemas ópticos son los sistemas de referencia por su precisión, el coste del equipamiento y el tiempo invertido en la captura y postprocesado ha llevado a los investigadores a probar otras tecnologías. En primer lugar, los sistemas no ópticos se basan en adherir sensores a zonas corporales para mandar su información espacial a un ordenador mediante distintas tecnologías, tales como electromagnética y inercial (acelerometría). Finalmente, los sistemas sin marcadores permiten un análisis del movimiento sin restricciones ya que los deportistas no llevan adherido ningún elemento. Sin embargo, se necesitan más sensores y un procesado de señal avanzado para aumentar el nivel de precisión necesario.

Vertical-jump tests are commonly used to evaluate lower-limb power of athletes and nonathletes. Several types of equipment are available for this purpose.Purpose: To compare the error of measurement of 2 jump-mat systems (Chronojump-Boscosystem and Globus Ergo Tester) with that of a motion-capture system as a criterion and to determine the modifying effect of foot length on jump height.Methods: Thirty-one young adult men alternated 4 countermovement jumps with 4 squat jumps. Mean jump height and standard deviations representing technical error of measurement arising from each device and variability arising from the subjects themselves were estimated with a novel mixed model and evaluated via standardization and magnitude-based inference.Results: The jump-mat systems produced nearly identical measures of jump height (differences in means and in technical errors of measurement ≤1 mm). Countermovement and squat-jump height were both 13.6 cm higher with motion capture (90% confidence limits ±0.3 cm), but this very large difference was reduced to small unclear differences when adjusted to a foot length of zero. Variability in countermovement and squat-jump height arising from the subjects was small (1.1 and 1.5 cm, respectively, 90% confidence limits ±0.3 cm); technical error of motion capture was similar in magnitude (1.7 and 1.6 cm, ±0.3 and ±0.4 cm), and that of the jump mats was similar or smaller (1.2 and 0.3 cm, ±0.5 and ±0.9 cm).Conclusions: The jump-mat systems provide trustworthy measurements for monitoring changes in jump height. Foot length can explain the substantially higher jump height observed with motion capture.

Uniform circular array processing has been shown to be a very useful tool for broadband acoustic source localization over 360°. Specifically, beamforming methods based on circular harmonics have attracted a lot of research attention in the last several years, as modal array signal processing is a very active research topic. On the other hand, due to the sparsity properties of speech, source localization methods in the time–frequency (T–F) domain have also demonstrated their capability to locate several simultaneous sources with high accuracy. In this paper, a localization framework based on circular harmonics beamforming and T–F processing that provides accurate localization performance under very adverse acoustic conditions is presented. Modal processing and sparsity-based localization are jointly addressed to estimate the direction-of-arrival of multiple concurrent speech sources. Experiments in real and simulated environments with different microphone setups are discussed, showing the validity of the proposed approach and comparing its performance with other state-of-the-art methods.