Acceso usuarios
Smog has always been one of the initiators that affect human health. In a severe haze environment, all functions of the human body will decline or even fail. In this paper, the influence of outdoor volleyball on human cardiopulmonary function in severe haze environment is studied. Whether heart sounds and lung sounds are normal or not can directly reflect the health status of human heart and lungs. Therefore, based on DNN (Deep Neural Network), this paper realizes the detection, separation and detection algorithm of heart and lung sounds, and analyzes the influence of outdoor volleyball on human cardiopulmonary function in Haze environment. In this paper, a set of lung sound data acquisition paradigm and evaluation method is designed, and the collected lung sounds are preprocessed by band-pass filtering to suppress noise interference. And the original features of lung sounds are extracted by using Mel spectrogram. Experimental results show that this method has high separation accuracy and robustness, the average SNR (Signal to Noise Ratio) reaches 24,307, and the error is only 0.104. It effectively improves the accuracy and recognition rate of cardiopulmonary sound separation. This shows that the improved relationship modeling method can accurately reflect the influence of outdoor volleyball on cardiopulmonary system in severe haze environment, and provides an accurate theoretical basis for outdoor volleyball training in severe haze environment.
