Modifiable (biomechanical and neuromuscular) anterior cruciate ligament (ACL) injury risk factors have been identified in laboratory settings. These risk factors were subsequently used in ACL injury prevention measures. Due to the lack of ecological validity, the use of on-field data in the ACL injury risk screening is increasingly advocated. Though, the kinematic differences between laboratory and on-field settings have never been investigated. The aim of the present study was to investigate the lower-limb kinematics of female footballers during agility movements performed both in laboratory and football field environments. Twenty-eight healthy young female talented football (soccer) players (14.9 ± 0.9 years) participated. Lower-limb joint kinematics was collected through wearable inertial sensors (Xsens Link) in three conditions: (1) laboratory setting during unanticipated sidestep cutting at 40-50°; on the football pitch (2) football-specific exercises (F-EX) and (3) football games (F-GAME). A hierarchical two-level random effect model in Statistical Parametric Mapping was used to compare joint kinematics among the conditions. Waveform consistency was investigated through Pearson's correlation coefficient and standardized z-score vector. In-lab kinematics differed from the on-field ones, while the latter were similar in overall shape and peaks. Lower sagittal plane range of motion, greater ankle eversion, and pelvic rotation were found for on-field kinematics (p < 0.044). The largest differences were found during landing and weight acceptance. The biomechanical differences between lab and field settings suggest the application of context-related adaptations in female footballers and have implications in ACL injury prevention strategies. Highlights: Talented youth female football players showed kinematical differences between the lab condition and the on-field ones, thus adopting a context-related motor strategy. Lower sagittal plane range of motion, greater ankle eversion, and pelvic rotation were found on the field. Such differences pertain to the ACL injury mechanism and prevention strategies. Preventative training should support the adoption of non-linear motor learning to stimulate greater self-organization and adaptability. It is recommended to test football players in an ecological environment to improve subsequent primary ACL injury prevention programmes.
A low-cost sensornode is introduced to monitor the 5G EMF exposure in the Netherlands for the four FR1 frequency bands. The sensornode is validated with in-lab measurements both with CW signals as for QAM signals and perform for both cases and for all frequency bands an error less than 1 dB for a dynamic range of 40 dB. This sensor is a follow up of the earlier version of our previously developed sensor and have substantial improvements in terms of linearity, error, and stability.
The AR in Staged Entertainment project focuses on utilizing immersive technologies to strengthen performances and create resiliency in live events. In this project The Experiencelab at BUas explores this by comparing live as well as pre-recorded events that utilize Augmented Reality technology to provide an added layer to the experience of the user. Experiences will be measured among others through observational measurements using biometrics. This projects runs in the Experience lab of BUas with partners The Effenaar and 4DR Studio and is connected to the networks and goals related to Chronosphere, Digireal and Makerspace. Project is powered by Fieldlab Events (PPS / ClickNL)..
Evaluating player game experiences through biometric measurementsThe BD4CG (Biometric Design for Casual Games project) worked in a highly interdisciplinary context with several international partners. The aim of our project was to popularize the biometric method, which is a neuro-scientific approach to evaluating the player experience. We specifically aimed at the casual games sector, where casual games can be defined as video or web-based games with simple and accessible game mechanics, non threatening themes and generally short play sessions. Popular examples of casual games are Angry Birds and FarmVille. We focussed on this sector because it is growing fast, but its methodologies have not grown with it yet. Especially the biometrics method has so far been almost exclusively used domain by the very large game developers (such as Valve and EA). The insights and scientific output of this project have been enthusiastically embraced by the international academic arena. The aim of the grant was to focus on game producers in the casual sector, and we have done so but we also established further contacts with the game sector in general. Thirty-one outputs were generated, in the form of presentations, workshops, and accepted papers in prominent academic and industry journals in the field of game studies and game user research. Partners: University of Antwerpen, RANJ, Forward Games, Double Jungle, Realgames, Dreams of Danu, Codemasters, Dezzel, Truimph Studios, Golabi Studios
Electronic Sports (esports) is a form of digital entertainment, referred to as "an organised and competitive approach to playing computer games". Its popularity is growing rapidly as a result of an increased prevalence of online gaming, accessibility to technology and access to elite competition.Esports teams are always looking to improve their performance, but with fast-paced interaction, it can be difficult to establish where and how performance can be improved. While qualitative methods are commonly employed and effective, their widespread use provides little differentiation among competitors and struggles with pinpointing specific issues during fast interactions. This is where recent developments in both wearable sensor technology and machine learning can offer a solution. They enable a deep dive into player reactions and strategies, offering insights that surpass traditional qualitative coaching techniquesBy combining insights from gameplay data, team communication data, physiological measurements, and visual tracking, this project aims to develop comprehensive tools that coaches and players can use to gain insight into the performance of individual players and teams, thereby aiming to improve competitive outcomes. Societal IssueAt a societal level, the project aims to revolutionize esports coaching and performance analysis, providing teams with a multi-faceted view of their gameplay. The success of this project could lead to widespread adoption of similar technologies in other competitive fields. At a scientific level, the project could be the starting point for establishing and maintaining further collaboration within the Dutch esports research domain. It will enhance the contribution from Dutch universities to esports research and foster discussions on optimizing coaching and performance analytics. In addition, the study into capturing and analysing gameplay and player data can help deepen our understanding into the intricacies and complexities of teamwork and team performance in high-paced situations/environments. Collaborating partnersTilburg University, Breda Guardians.
