Modeling of SPM-GRU ping-pong ball trajectory prediction incorporating YOLOv4-Tiny algorithm.

The research aims to lift the accuracy of table tennis trajectory prediction through advanced computer vision and deep learning techniques to achieve real-time and accurate table tennis ball position and motion trajectory tracking. The study concentrates on the innovative application of a micro-miniature fourth-generation real-time target detection algorithm with a gated loop unit to table tennis ball motion analysis by combining physical models and deep learning methods. The results show that in the comparison experiments, the improved micro-miniature fourth-generation real-time target detection algorithm outperforms the traditional target detection algorithm, with the loss value decreasing to 1.54. Its average accuracy in multi-target recognition is dramatically increased to 86.74%, which is 22.36% higher than the original model, and the ping-pong ball recognition experiments show that it has an excellent accuracy in various lighting conditions, especially in low light, with an average accuracy of 89.12%. Meanwhile, the improved model achieves a processing efficiency of 85 frames/s. In addition, compared with the traditional trajectory prediction model, the constructed model performs the best in table tennis ball trajectory prediction, with errors of 4.5 mm, 25.3 mm, and 35.58 mm. The results show that the research trajectory prediction model achieves significant results in accurately tracking table tennis ball positions and trajectories. It not only has practical application value for table tennis training and competition strategies, but also provides a useful reference for the similar techniques application in other sports.

Regular strength training effect on kung fu athletes injuries reduction / Efeito do treinamento regular de força na redução das lesões esportivas em atletas de kung fu / Efecto del entrenamiento de fuerza regular en la reducción de lesiones deportivas en atletas de kung fu

ABSTRACT Introduction: As the competitive level of martial arts keeps improving, the requirements for athletes' skills are also getting more elevated. Against this background, implementing preventive protocols for sports practice injuries is necessary. Regular strength training is a practice that aims to prevent injuries, but the approach in Kung Fu practitioners is still empirical. Objective: Explore the effect of regular strength training on Kung Fu athletes' exercise injury. Methods: 40 athletes with similar ages and grades are randomly grouped into control and experimental groups. While the control group practiced regular training, strength training lasting 90 minutes was implemented three times a week for five months in the experimental group. Physical test results have been analyzed before and after the experiment. Results: After a detailed analysis of the quality and ability data, the indicators are significantly different. Although the athletes in the control group also improved to varying degrees, they are not as good as those in the experimental group. Conclusion: Regular strength training has a positive impact on reducing exercise injury in martial arts athletes and helps improve the athletic level of athletes. After much regular strength training, the quality and ability of the athletes were significantly improved. Evidence Level II; Therapeutic Studies - Investigating the result.

RESUMO Introdução: Com a melhora contínua do nível competitivo das artes marciais, os requisitos para as habilidades dos atletas também estão ficando cada vez mais altos. Nesse contexto, surge a necessidade de implementar protocolos preventivos para lesões ocasionadas durante a prática esportiva. Treinamentos regulares de força são práticas que visam a prevenção de lesões, porém a abordagem em praticantes de Kung Fu ainda é empírica. Objetivo: Explorar o efeito do treinamento regular de força para reduzir a lesão de exercício nos atletas de Kung Fu. Métodos: 40 esportistas com idades e notas semelhantes são agrupados aleatoriamente em grupos controle e experimental. Enquanto o grupo controle praticava os treinamentos regulares, no grupo experimental foi implementado o treino de força com duração de 90 minutos, três vezes por semana por cinco meses. Resultados de testes físicos foram analisados antes e depois do experimento. Resultados: Após a análise especial dos dados de qualidade e habilidade, os indicadores são significativamente diferentes. Embora os atletas do grupo de controle também tenham melhorado em graus variados, eles não são tão bons quanto os do grupo experimental. Conclusão: O treinamento regular de força tem um impacto positivo na redução da lesão de exercício dos atletas de artes marciais e ajuda a melhorar o nível esportivo dos atletas. Depois de muito treinamento regular de força, a qualidade e habilidade dos esportistas foram significativamente aprimoradas. Nível de evidência II; Estudos Terapêuticos - Investigação de Resultados.

RESUMEN Introducción: Con la continua mejora del nivel competitivo de las artes marciales, los requisitos para las habilidades de los atletas también son cada vez más altos. En este contexto, surge la necesidad de implementar protocolos preventivos para las lesiones causadas durante la práctica deportiva. El entrenamiento de fuerza regular es una práctica destinada a la prevención de lesiones, pero el enfoque en los practicantes de Kung Fu sigue siendo empírico. Objetivo: Explorar el efecto del entrenamiento de fuerza regular para reducir las lesiones por ejercicio en los atletas de Kung Fu. Métodos: 40 atletas de edad y grado similares se agrupan aleatoriamente en grupos de control y experimental. Mientras que el grupo de control practicó el entrenamiento habitual, en el grupo experimental se implementó un entrenamiento de fuerza de 90 minutos de duración tres veces por semana durante cinco meses. Los resultados de las pruebas físicas se analizaron antes y después del experimento. Resultados: Tras un análisis especial de los datos de calidad y capacidad, los indicadores son significativamente diferentes. Aunque los atletas del grupo de control también mejoraron en diversos grados, no son tan buenos como los del grupo experimental. Conclusión: El entrenamiento de fuerza regular tiene un impacto positivo en la reducción de las lesiones por ejercicio en los atletas de artes marciales y ayuda a mejorar el nivel deportivo de los atletas. Tras un entrenamiento de fuerza muy regular, la calidad y la capacidad de los atletas mejoraron significativamente. Nivel de evidencia II; Estudios terapéuticos -Investigación de resultados.

The Identification of ECG Signals Using Wavelet Transform and WOA-PNN.

Electrocardiogram (ECG) signal identification technology is rapidly replacing traditional fingerprint, face, iris and other recognition technologies, avoiding the vulnerability of traditional recognition technologies. This paper proposes an ECG signal identification method based on the wavelet transform algorithm and the probabilistic neural network by whale optimization algorithm (WOA-PNN). Firstly, Q, R and S waves are detected by wavelet transform, and the P and T waves are detected by local windowed wavelet transform. The characteristic values are constructed by the detected time points, and the ECG data dimension is smaller than that of the non-reference detection. Secondly, combined with the probabilistic neural network, the mean impact value algorithm is used to screen the characteristic values, the characteristic values with low influence are eliminated, and the input and complexity of the model are simplified. Finally, a WOA-PNN combined classification method is proposed to intelligently optimize the hyper parameters in the probabilistic neural network algorithm to improve the model accuracy. According to the simulation verification on three databases, ECG-ID, MIT-BIH Normal Sinus Rhythm and MIT-BIH Arrhythmia, the identification accuracy of a single ECG cycle is 96.97%, and the identification accuracy of three ECG cycles is 99.43%.

The Identification of ECG Signals Using WT-UKF and IPSO-SVM.

The biometric identification method is a current research hotspot in the pattern recognition field. Due to the advantages of electrocardiogram (ECG) signals, which are difficult to replicate and easy to obtain, ECG-based identity identification has become a new direction in biometric recognition research. In order to improve the accuracy of ECG signal identification, this paper proposes an ECG identification method based on a multi-scale wavelet transform combined with the unscented Kalman filter (WT-UKF) algorithm and the improved particle swarm optimization-support vector machine (IPSO-SVM). First, the WT-UKF algorithm can effectively eliminate the noise components and preserve the characteristics of ECG signals when denoising the ECG data. Then, the wavelet positioning method is used to detect the feature points of the denoised signals, and the obtained feature points are combined with multiple feature vectors to characterize the ECG signals, thus reducing the data dimension in identity identification. Finally, SVM is used for ECG signal identification, and the improved particle swarm optimization (IPSO) algorithm is used for parameter optimization in SVM. According to the analysis of simulation experiments, compared with the traditional WT denoising, the WT-UKF method proposed in this paper improves the accuracy of feature point detection and increases the final recognition rate by 1.5%. The highest recognition accuracy of a single individual in the entire ECG identification system achieves 100%, and the average recognition accuracy can reach 95.17%.