To improve the accuracy of lung disease diagnosis,a lung disease automatic diagnosis system based on acoustic signal analysis is proposed. The system collects respiratory sound signals through a high-precision microphone array and analog-to-digital conversion chip,and adopts a parallel computing architecture based on Field Programmable Gate Array (FPGA) to mine and optimize key features from the preprocessed signals. The experimental results indicate that the system has high diagnostic accuracy in bronchial asthma,pneumonia,and chronic obstructive pulmonary disease.
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