In this study, we examined the effects of a defender contesting jump shots on performance and gaze behaviors of basketball players taking jump shots. Thirteen skilled youth basketball players performed 48 shots from about 5 m from the basket; 24 uncontested and 24 contested. The participants wore mobile eye tracking glasses to measure their gaze behavior. As expected, an approaching defender trying to contest the shot led to significant changes in movement execution and gaze behavior including shorter shot execution time, longer jump time, longer ball flight time, later final fixation onset, and longer fixation on the defender. Overall, no effects were found for shooting accuracy. However, the effects on shot accuracy were not similar for all participants: six participants showed worse performance and six participants showed better performance in the contested compared to the uncontested condition. These changes in performance were accompanied by differences in gaze behavior. The participants with worse performance showed shorter absolute and relative final fixation duration and a tendency for an earlier final fixation offset in the contested condition compared to the uncontested condition, whereas gaze behavior of the participants with better performance for contested shots was relatively unaffected. The results confirm that a defender contesting the shot is a relevant constraint for basketball shooting suggesting that representative training designs should also include contested shots, and more generally other constraints that are representative of the actual performance setting such as time or mental pressure.
From an evidence-based perspective, cardiopulmonary exercise testing (CPX) is a well-supported assessment technique in both the United States (US) and Europe. The combination of standard exercise testing (ET) [i.e. progressive exercise provocation in association with serial electrocardiograms (ECGs), haemodynamics, oxygen saturation, and subjective symptoms] and measurement of ventilatory gas exchange amounts to a superior method to: (i) accurately quantify cardiorespiratory fitness (CRF), (ii) delineate the physiologic system(s) underlying exercise responses, which can be applied as a means to identify the exercise-limiting pathophysiological mechanism(s) and/or performance differences, and (iii) formulate function-based prognostic stratification. Cardiopulmonary ET certainly carries an additional cost as well as competency requirements and is not an essential component of evaluation in all patient populations. However, there are several conditions of confirmed, suspected, or unknown aetiology where the data gained from this form of ET is highly valuable in terms of clinical decision making.1
Formula scoring (FS) is the use of a don't know option (DKO) with subtraction of points for wrong answers. Its effect on construct validity and reliability of progress test scores, is subject of discussion. Choosing a DKO may not only be affected by knowledge level, but also by risk taking tendency, and may thus introduce construct-irrelevant variance into the knowledge measurement. On the other hand, FS may result in more reliable test scores. To evaluate the impact of FS on construct validity and reliability of progress test scores, a progress test for radiology residents was divided into two tests of 100 parallel items (A and B). Each test had a FS and a number-right (NR) version, A-FS, B-FS, A-NR, and B-NR. Participants (337) were randomly divided into two groups. One group took test A-FS followed by B-NR, and the second group test B-FS followed by A-NR. Evidence for impaired construct validity was sought in a hierarchical regression analysis by investigating how much of the participants' FS-score variance was explained by the DKO-score, compared to the contribution of the knowledge level (NR-score), while controlling for Group, Gender, and Training length. Cronbach's alpha was used to estimate NR and FS-score reliability per year group. NR score was found to explain 27 % of the variance of FS [F(1,332) = 219.2, p < 0.0005], DKO-score, and the interaction of DKO and Gender were found to explain 8 % [F(2,330) = 41.5, p < 0.0005], and the interaction of DKO and NR 1.6 % [F(1,329) = 16.6, p < 0.0005], supporting our hypothesis that FS introduces construct-irrelevant variance into the knowledge measurement. However, NR-scores showed considerably lower reliabilities than FS-scores (mean year-test group Cronbach's alphas were 0.62 and 0.74, respectively). Decisions about FS with progress tests should be a careful trade-off between systematic and random measurement error.
In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
The automobile industry is presently going through a rapid transformation towards autonomous driving. Nearly all vehicle manufacturers (such as Mercedes Benz, Tesla, BMW) have commercial products, promising some level of vehicle automation. Even though the safe and reliable introduction of technology depends on the quality standards and certification process, but the focus is primarily on the introduction of (uncertified) technology and not on developing knowledge for certification. Both industry and governments see the lack of knowledge about certification, which can ensure the safety of autonomous technology and thus will guarantee the safety of the driver, passenger, and environment. HAN-AR recognized the lack of knowledge and the need for novel certification methodology for emerging vehicle technology and initiated the PRAUTOCOL project together with its SME partners. The PRAUTOCOL project investigated certification methodology for two use-cases: certification for automated highway overtaking pilot; and certification for automatic valet parking. The PRAUTOCOL research is conducted in two parallel streams: certification of the driver by human factors experts and certification of vehicle by technology experts. The results from both streams are published and presented in respective but limited target groups. Also, an overview of the PRAUTOCOL certification methodology is missing, which can enable its translation to different use-cases of automated technology (other than the used ones). Therefore, to realize a better pass-through of PRAUTOCOL's results to a broader audience, the top-up is required. Firstly, to write a (peer-reviewed) Open Access article, focusing on the application and translation of PRAUTOCOL's methodology to other automated technology use-cases. Secondly, to write a journal article, focusing on the validation of automatic highway overtaking system using naturalistic driving data. Thirdly, to organize a workshop to present PRAUTOCOL's results (valorization) to industrial, research, and government representatives and to discuss a follow-up initiative.
