Using Virtual Reality to increase technical performance during rowing workouts

Technology is advancing rapidly in virtual reality (VR) and sensors, gathering feedback from our body and the environment we are interacting in. Combining the two technologies gives us the opportunity to create personalized and reactive immersive environments. These environments can be used e.g. for training in dangerous situations (e.g. fire, crashes, etc), or to improve skills with less distraction than regular natural environments would have. The pilot study described in this thesis puts an athlete who is rowing on a stationary rowing machine into a virtual environment. The VR takes movement from several sensors of the ergo-meter and displays those in VR. In addition, metrics on technique are being derived from the sensor data and physiological data. All this is used to investigate if, and to which extent, VR may improve the technical skills of the athlete during the complex sport of rowing. Furthermore, athletes are giving subjective feedback about their experience comparing a standard rowing workout, with the workout using VR. First results indicate better performance and an enhanced experience by the athlete

Biomechanical Spectrum of Human Sport Performance

Writing or managing a scientific book, as it is known today, depends on a series of major activities, such as regrouping researchers, reviewing chapters, informing and exchanging with contributors, and at the very least, motivating them to achieve the objective of publication. The idea of this book arose from many years of work in biomechanics, health disease, and rehabilitation. Through exchanges with authors from several countries, we learned much from each other, and we decided with the publisher to transfer this knowledge to readers interested in the current understanding of the impact of biomechanics in the analysis of movement and its optimization. The main objective is to provide some interesting articles that show the scope of biomechanical analysis and technologies in human behavior tasks. Engineers, researchers, and students from biomedical engineering and health sciences, as well as industrial professionals, can benefit from this compendium of knowledge about biomechanics applied to the human body

Levitation Simulator: Prototyping Ultrasonic Levitation Interfaces in Virtual Reality

We present the Levitation Simulator, a system that enables researchers and designers to iteratively develop and prototype levitation interface ideas in Virtual Reality. This includes user tests and formal experiments. We derive a model of the movement of a levitating particle in such an interface. Based on this, we develop an interactive simulation of the levitation interface in VR, which exhibits the dynamical properties of the real interface. The results of a Fitts' Law pointing study show that the Levitation Simulator enables performance, comparable to the real prototype. We developed the first two interactive games, dedicated for levitation interfaces: LeviShooter and BeadBounce, in the Levitation Simulator, and then implemented them on the real interface. Our results indicate that participants experienced similar levels of user engagement when playing the games, in the two environments. We share our Levitation Simulator as Open Source, thereby democratizing levitation research, without the need for a levitation apparatus.Comment: 12 pages, 14 figures, CHI'2

Sport World

The idea of this project is to develop a virtual reality video game in which the users, through various mini-games, perform cardiovascular exercises playfully to promote sport among young people and without the need to leave the house. This idea came to me during the pandemic, while being locked down. After several days of being at home, my body needed movement and fresh air, beyond of what my window could provide me. The main goal of the present thesis is to develop a video game containing various elements that facilitate the immersion and involvement of users in order to enhance their internal motivation of exercising and improving their physical health. There will be other external motivations to maintain the routine of doing virtual exercise like a rewarding system that reflects effort through rewards such as skins, medals or extra score

Feasibility and safety of an immersive virtual reality-based vestibular rehabilitation programme in people with multiple sclerosis experiencing vestibular impairment: a protocol for a pilot randomised controlled trial

Introduction: Vestibular system damage in patients with multiple sclerosis (MS) may have a central and/or peripheral origin. Subsequent vestibular impairments may contribute to dizziness, balance disorders and fatigue in this population. Vestibular rehabilitation targeting vestibular impairments may improve these symptoms. Furthermore, as a successful tool in neurological rehabilitation, immersive virtual reality (VRi) could also be implemented within a vestibular rehabilitation intervention. Methods and analysis: This protocol describes a parallel-arm, pilot randomised controlled trial, with blinded assessments, in 30 patients with MS with vestibular impairment (Dizziness Handicap Inventory ≥16). The experimental group will receive a VRi vestibular rehabilitation intervention based on the conventional Cawthorne-Cooksey protocol; the control group will perform the conventional protocol. The duration of the intervention in both groups will be 7 weeks (20 sessions, 3 sessions/week). The primary outcomes are the feasibility and safety of the vestibular VRi intervention in patients with MS. Secondary outcome measures are dizziness symptoms, balance performance, fatigue and quality of life. Quantitative assessment will be carried out at baseline (T0), immediately after intervention (T1), and after a follow-up period of 3 and 6 months (T2 and T3). Additionally, in order to further examine the feasibility of the intervention, a qualitative assessment will be performed at T1. Ethics and dissemination: The study was approved by the Andalusian Review Board and Ethics Committee, Virgen Macarena-Virgen del Rocio Hospitals (ID 2148-N-19, 25 March 2020). Informed consent will be collected from participants who wish to participate in the research. The results of this research will be disseminated by publication in peer-reviewed scientific journals

Fast human behavior analysis for scene understanding

Human behavior analysis has become an active topic of great interest and relevance for a number of applications and areas of research. The research in recent years has been considerably driven by the growing level of criminal behavior in large urban areas and increase of terroristic actions. Also, accurate behavior studies have been applied to sports analysis systems and are emerging in healthcare. When compared to conventional action recognition used in security applications, human behavior analysis techniques designed for embedded applications should satisfy the following technical requirements: (1) Behavior analysis should provide scalable and robust results; (2) High-processing efficiency to achieve (near) real-time operation with low-cost hardware; (3) Extensibility for multiple-camera setup including 3-D modeling to facilitate human behavior understanding and description in various events. The key to our problem statement is that we intend to improve behavior analysis performance while preserving the efficiency of the designed techniques, to allow implementation in embedded environments. More specifically, we look into (1) fast multi-level algorithms incorporating specific domain knowledge, and (2) 3-D configuration techniques for overall enhanced performance. If possible, we explore the performance of the current behavior-analysis techniques for improving accuracy and scalability. To fulfill the above technical requirements and tackle the research problems, we propose a flexible behavior-analysis framework consisting of three processing-layers: (1) pixel-based processing (background modeling with pixel labeling), (2) object-based modeling (human detection, tracking and posture analysis), and (3) event-based analysis (semantic event understanding). In Chapter 3, we specifically contribute to the analysis of individual human behavior. A novel body representation is proposed for posture classification based on a silhouette feature. Only pure binary-shape information is used for posture classification without texture/color or any explicit body models. To this end, we have studied an efficient HV-PCA shape-based descriptor with temporal modeling, which achieves a posture-recognition accuracy rate of about 86% and outperforms other existing proposals. As our human motion scheme is efficient and achieves a fast performance (6-8 frames/second), it enables a fast surveillance system or further analysis of human behavior. In addition, a body-part detection approach is presented. The color and body ratio are combined to provide clues for human body detection and classification. The conventional assumption of up-right body posture is not required. Afterwards, we design and construct a specific framework for fast algorithms and apply them in two applications: tennis sports analysis and surveillance. Chapter 4 deals with tennis sports analysis and presents an automatic real-time system for multi-level analysis of tennis video sequences. First, we employ a 3-D camera model to bridge the pixel-level, object-level and scene-level of tennis sports analysis. Second, a weighted linear model combining the visual cues in the real-world domain is proposed to identify various events. The experimentally found event extraction rate of the system is about 90%. Also, audio signals are combined to enhance the scene analysis performance. The complete proposed application is efficient enough to obtain a real-time or near real-time performance (2-3 frames/second for 720×576 resolution, and 5-7 frames/second for 320×240 resolution, with a P-IV PC running at 3GHz). Chapter 5 addresses surveillance and presents a full real-time behavior-analysis framework, featuring layers at pixel, object, event and visualization level. More specifically, this framework captures the human motion, classifies its posture, infers the semantic event exploiting interaction modeling, and performs the 3-D scene reconstruction. We have introduced our system design based on a specific software architecture, by employing the well-known "4+1" view model. In addition, human behavior analysis algorithms are directly designed for real-time operation and embedded in an experimental runtime AV content-analysis architecture. This executable system is designed to be generic for multiple streaming applications with component-based architectures. To evaluate the performance, we have applied this networked system in a single-camera setup. The experimental platform operates with two Pentium Quadcore engines (2.33 GHz) and 4-GB memory. Performance evaluations have shown that this networked framework is efficient and achieves a fast performance (13-15 frames/second) for monocular video sequences. Moreover, a dual-camera setup is tested within the behavior-analysis framework. After automatic camera calibration is conducted, the 3-D reconstruction and communication among different cameras are achieved. The extra view in the multi-camera setup improves the human tracking and event detection in case of occlusion. This extension of multiple-view fusion improves the event-based semantic analysis by 8.3-16.7% in accuracy rate. The detailed studies of two experimental intelligent applications, i.e., tennis sports analysis and surveillance, have proven their value in several extensive tests in the framework of the European Candela and Cantata ITEA research programs, where our proposed system has demonstrated competitive performance with respect to accuracy and efficiency

The Examination of Slo-pitch Hitting Movement Coordination

This study developed an interdisciplinary approach by utilizing the principles of ecological task analysis and movement coordination from areas of motor leaning and biomechanics to examine the skill of slo-pitch softball hitting. The purpose of this study was to examine the influence of a task constraint, stride technique, and an environmental constraint, pitched ball location, on the participants’ movement patterns. Ten elite male softball players participated in the study and a two-way ANOVA of 2 locations of pitch (inside and outside) x 3 strides (open, parallel and closed) repeated measure study was conducted. The results showed that participants demonstrated different joint movements and different coordination patterns in slo-pitch hitting. Hence, this study supports the rationale of ecological task analysis. Further, a Euclidean distance analysis was conducted to evaluate the degree of dissimilarity between the individual and group mean results in attempt to better understand the generalizability. The results indicated that participants generally showed a low degree of dissimilarity; hence, coaches and educators may apply the findings to other players. A similar interdisciplinary approach is warranted for future research studies on other sport skills or health conditions in order to better understand the mechanics of human motion

Sports Performance and Health

Sports performance is primarily associated with elite sport, however, recreational athletes are increasingly attempting to emulate elite athletes. Performance optimization is distinctly multidisciplinary. Optimized training concepts and the use of state-of-the-art technologies are crucial for improving performance. However, sports performance enhancement is in constant conflict with the protection of athletes’ health. Notwithstanding the known positive effects of physical activity on health, the prevention and management of sports injuries remain major challenges to be addressed. Accordingly, this Special Issue on "Sports Performance and Health" consists of 17 original research papers, one review paper, and one commentary, and covers a wide range of topics related to fatigue, movement asymmetries, optimization of sports performance by training, technique, and/or tactics enhancements, prevention and management of sports injuries, optimization of sports equipment to increase performance and/or decrease the risk of injury, and innovations for sports performance, health, and load monitoring. As this Special Issue offers several new insights and multidisciplinary perspectives on sports performance and health, readers from around the world who work in these areas are expected to benefit from this Special Issue collection