Search

Aim: The aim of this study is to study the frequency of sudden death in sports from the year 2004–2020 in the city of Kashan, Iran. Materials and Methods: This case series research included fatal sports injuries from the years 2004 to year 2020. Anecdotal data were collected by interviewing different sports organizations and close relatives of the victims. Result: The result of descriptive analysis of collected data showed that 17 cases of sudden sports death occurred during the years 2004 until 2020. The highest frequency of the cases occurred in mountain claiming with 9 (52.9%), followed by swimming with 3 (17.6%), and handball with 2 (11.8%), horse riding 1 (5.9%), basketball 1 (5.9%), and martial arts 1 (5.9%). All the analysis was performed using the SPSS: pc version 21. Conclusion: Fatal sports injuries are rare; however, they occur incidentally due to poor knowledge and education of the sport participants. It was concluded that nearly all fatal incidents were preventable. [ABSTRACT FROM AUTHOR]

Background: Given the increased casualties of swimming at sea, there is an urgent need for an intelligent warning drowning detection system in the coasts. In order to provide such a system, image processing techniques in combination with the artificial intelligence are used. These challenges include the high noise of sea images, the presence of frequent moves in the image, and the size of the drowned from far distance. Methods: In this article, for monitoring the sea and automatic drowning detection, the swimmer is detected and the features of images are extracted through using image processing techniques and background omission. Then, using the artificial neural network, a network training and testing is done, and the drowning swimmer will be detected. This neural network of the perceptron type contains two hidden layers. There are 7 neurons in the first layer and 3 neurons in the second layer. Results: The results indicated that the neural network has detected drowning cases with the precision of 94.46%. Conclusion: For detecting drowning in sea beaches, the neural network is the best approach with the highest precision. [ABSTRACT FROM AUTHOR]