Effects of digital filtering on peak acceleration and force measurements for artistic gymnastics skills

Current issues and future directions in gymnastics research: biomechanics, motor control and coaching interface

The sport of gymnastics is undergoing a global examination of its culture and the relationship between the gymnast, coach and environment is a central focus. The aim of this review is to explore biomechanics and motor control research in skill development and technique selection in artistic gymnastics with a focus on the underlying concepts and scientific principles that allow performance enhancement, skill development and injury risk reduction. The current review examines peer reviewed papers from 2000 onwards, with a focus on contemporary approaches in the field of gymnastics research, and highlights several key directions for future gymnastics research. Based on our review and the integration of the models of Newell (1986) and Irwin et al. (2005), we recommend that future gymnastics research should embrace at the very least a multidisciplinary approach and aim for an interdisciplinary paradigm.

The use of inertial measurement units to quantify forearm loading and symmetry during gymnastics vault training sessions

The upper limbs are important in gymnastics vaulting, as the success of the flight phase is dependent on a quick and forceful push-off from the vault. This places the upper limbs under stress, which has been associated with pain and injury. This study aimed to quantify forearm segmental loading and symmetry when performing foundation to advanced-level vaulting skills during training. Twelve advanced-level artistic gymnasts (female, n = 6; male, n = 6) wore bilaterally forearm-mounted inertial measurement units while completing their vaulting sessions. The peak resultant acceleration for the leading and non-leading forearms during contact were calculated. Female gymnasts performed variations of Yurchenko vaults, while male gymnasts performed Handspring and Tsukahara vaults. Descriptive statistics (median and inter-quartile range), symmetry index scores, and total session impact load (measure of cumulative loading) were calculated between the lead and non-lead forearms. High asymmetrical loading was identified for some Yurchenko, Handspring, and Tsukahara vaults, with large variations identified between gymnasts. Some gymnasts experienced greater loading at their lead forearm, while others experienced greater loading at their non-lead forearm. Results indicate that limb loading patterns in advanced gymnastics are highly individualised, indicating that individual analysis is needed to identify gymnasts (or limbs) at an increased risk for overuse injury.

Real-world measurements of ground reaction forces of normal gait of young adults wearing various footwear

For years, researchers have been recognizing patterns in gait for purposes of medical diagnostics, rehabilitation, and biometrics. A method for observing gait is to measure ground reaction forces (GRFs) between the foot and solid plate with tension sensors. The presented dataset consists of 13,702 measurements of bipedal GRFs of one step of normal gait of 324 students wearing shoes of various types. Each measurement includes raw digital signals of two force plates. A signal comprises stance-related samples but also preceding and following ones, in which one can observe noise, interferences, and artifacts caused by imperfections of devices and walkway. Such real-world time series can be used to study methods for detecting foot-strike and foot-off events, and for coping with artifacts. For user convenience, processed data are also available, which describe only the stance phase of gait and form ready-to-use patterns suitable for experiments in GRF-based recognition of persons and footwear, and for generating synthetic GRF waveforms. The dataset is accompanied by Matlab and Python programs for organizing and validating data.

THE EFFECTS OF STRETCHING ON TRAINING CYCLISTS

ABSTRACT Introduction Scientific and rational post-competition training can help athletes mobilize their competitive state. Stretching is an integral part of the physical recovery program after a cycling event, increasing muscle extensibility, decreasing muscle soreness, and the likelihood of injury. Objective This study aims to analyze the effect of stretching training on cyclists. Methods This paper selects 20 cyclists who perform stretching training after the competition. The athletes’ fatigue recovery after stretching training and the probability of sports injuries after stretching exercise are statistically analyzed. Results The athletes demonstrated poor physical flexibility before stretching. In the forward bending test, the athletes demonstrated scores of 15.31 and 17.89, respectively. After stretching training, the athletes improved to 23.68 and 25.36 in the seated forward flexion test. The data collected were statistically significant (P<0.05). Conclusion Stretching exercises can effectively improve the competitive ability of cyclists. It is recommended that athletes devote about 10 to 15 minutes of relaxation and stretching exercises after cycling. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

SYSTEMATIC SKILL PRACTICE IN WOMEN's FLOOR EXERCISE

ABSTRACT Introduction Ground exercise is a high-level event of Chinese women's gymnastics. Maintaining the dominant strength of women's floor exercise in China has become one of the issues that coaches, athletes and gymnastics researchers should actively discuss. A research analysis on athletes’ competition in the National Games can better reflect and illustrate the fundamental level of athletes and their overall developmental status. Objective To verify the relationship between women's floor exercise skills and competition performance. Methods The analysis and study of 65 female athletes participating in floor exercises at the National Games was carried out. In this paper, the on-the-spot statistical method is used to perform statistics on the skills and the athletes’ completion in the four games. Movement training and choreography experts were consulted. Results The performance of women's floor drills in the National Games was discussed from three aspects: the difficulty and arrangement of movements, the initial score and bonus points, and the completion of movements. Conclusion Most athletes can adapt to the changes in the new rules and master many complex movements. This also gets them a higher score. However, the choreography of the athletes’ complete movements is relatively simple and lacks features. Strength training in the lower limbs should be the key to improving the athletes’ ability in floor exercise. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

The Application of RBF Neural Network Model Based on Deep Learning for Flower Pattern Design in Art Teaching

The rapid growth of artificial intelligence technology has been deployed in art teaching and learning. Radial basis function (RBF) networks have a completely different design compared to most neural network architectures. Most neural networks consist of multiple layers that can introduce nonlinearity by repetitive application of nonlinear activation functions. In this research, people will study the application of the RBF neural network model based on deep learning in flower pattern design in art teaching. The image classification process is finding and labeling groups of pixels or vectors inside an image based on rules. Deep learning is a type of machine learning that uses artificial neural networks to replicate the structure and function of the human brain. The proposed model uses the RBF neural network-based deep learning model in flower pattern design in art teaching and provides efficient results.

The Application of Artificial Intelligence Technology in Art Teaching Taking Architectural Painting as an Example

In the current era of technology, artificial intelligence has grown rapidly in such a way that it has established its presence in all fields. The purpose of artificial intelligence is to reduce human intervention and complete tasks with an enhanced result. In this research, we are going to study the application of artificial intelligence technology in art teaching, taking architectural painting as an example. Architectural painting is a type of painting that focuses only on architecture, including indoor and outdoor views of the buildings. In earlier stages, architecture was shown only in the background of paintings that had different objects as the main subject. Later, architecture itself became a mainstream genre in the field of painting. As has been shown by other researchers, the latest technologies such as Internet technology, wireless sensor networks (WSNs), and artificial intelligence like deep learning technologies are deployed in art teaching. Artificial intelligence has made teaching easier. This proposed system makes use of Internet technology, WSNs, artificial intelligence, and lightweight deep learning models in the field of art teaching. The teaching method is enhanced by adapting to this new technology. For performing the analysis of the proposed system, the Limited Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) art algorithm is implemented. This L-BFGS algorithm focuses on finding the local minima in any given application. In this art teaching of architectural painting, the proposed algorithm will aid in explaining the minute works to be noted while doing the artwork. The proposed algorithm is then compared with the traditional Gradient Descent, Adam, and Adadelta algorithms. From the results, it can be observed that the proposed algorithm has achieved accuracy of 97% and 98% in the training and testing phases, respectively.

The Use of Wearable Sensor Technology to Detect Shock Impacts in Sports and Occupational Settings: A Scoping Review

Shock impacts during activity may cause damage to the joints, muscles, bones, or inner organs. To define thresholds for tolerable impacts, there is a need for methods that can accurately monitor shock impacts in real-life settings. Therefore, the main aim of this scoping review was to present an overview of existing methods for assessments of shock impacts using wearable sensor technology within two domains: sports and occupational settings. Online databases were used to identify papers published in 2010-2020, from which we selected 34 papers that used wearable sensor technology to measure shock impacts. No studies were found on occupational settings. For the sports domain, accelerometry was the dominant type of wearable sensor technology utilized, interpreting peak acceleration as a proxy for impact. Of the included studies, 28 assessed foot strike in running, head impacts in invasion and team sports, or different forms of jump landings or plyometric movements. The included studies revealed a lack of consensus regarding sensor placement and interpretation of the results. Furthermore, the identified high proportion of validation studies support previous concerns that wearable sensors at present are inadequate as a stand-alone method for valid and accurate data on shock impacts in the field.