"基于随机解调结构的心电信号压缩采样方法研究"

The research presented in the document "基于随机解调结构的心电信号压缩采样方法_毕业论文.pdf" explores a novel approach to compressing and sampling electrocardiogram (ECG) signals using a random demodulation structure. The study investigates the impact of pseudo-random sequence frequency on sampling frequency and reconstruction accuracy through simulations conducted in Simulink. The findings indicate that the proposed compressed sampling method utilizing a random demodulator is capable of sampling the ECG signal at a sub-Nyquist frequency while achieving a similar sampling effect as Nyquist frequency through a reconstruction algorithm. This demonstrates the potential of the method for efficiently capturing ECG signals with reduced sampling rates, offering a foundation for the development of electric circuits for random demodulation. Furthermore, the document outlines the design and implementation of an electrical system based on random demodulation. This system is aimed at improving the compression and sampling of ECG signals, providing a practical application of the proposed methodology. By leveraging the benefits of random demodulation, the system can enhance the efficiency and accuracy of ECG signal acquisition, contributing to advancements in medical monitoring and diagnostic technologies. In summary, the research introduces a cutting-edge approach to compressing and sampling ECG signals using a random demodulation structure. Through thorough simulations and experimental implementations, the study demonstrates the feasibility and effectiveness of the proposed method in achieving high-quality signal acquisition with reduced sampling requirements. The findings pave the way for further developments in signal processing and electronic systems for medical applications, showcasing the potential impact of random demodulation in revolutionizing ECG signal analysis and monitoring.