The Research On The Remote Heart Sound Monitoring Platform Which Is Based On The IOT And CS Theory

With the continuous improvement of people's lives and medical standards, the real-time monitoring on human health characteristics has become the inevitable trend of social development. The development of IOT provides a more effective way to remote monitoring of human health characteristics. The application of compressed sensing theory reduces the energy consumption of data acquisition and transmission in the IOT, and greatly increases the efficiency of the network.The subjects used the theoretical research, applied technology development and experimental verification methods.In the theory part,I learned IOT and CS theory, and analyzed the characteristics of heart sound signal and working principle of optoelectronic displacement sensor. Because of traditional CS theory applications require signal must be a sparse signal or compressible signal, we must do the sparse representation before the signal compression and recovery. In the process of compression and recovery of the heart sounds signal, which is a sparse signal, was compressed without sparse representation. But the heart sound signals need a denoising process.As for the Application of technology part, firstly, I designed a photoelectric heart sounds sensor which is based on the optical displacement sensor. And then, I improved the treatment effect on the heart sound signal because of the application of CS theory in the process of collection and transmission of heart sounds. At last, I designed an aggregation node which is based on the embedded technology and the of wireless sensor networks. The results show: the principle of the heart sound sensor is practicable; the CS theory can acquire the applications expected in compression and recovery of the heart sound; the convergence node of WSN can work normally and staidly.