Respiratory Rate Measurement Method Based on Singular Value Decomposition

In order to enhance the measurement accuracy of respiratory rate, a respiratory rate measurement method based on high-speed vision is presented in this paper. Initially, a high-speed camera is utilized to capture the experimenter's chest breathing movement video sequence, and singular value decomposition (SVD) is applied to extract the displacement resulting from respiratory movement. However, the extracted motion waveform contains some noise signals due to the poor denoising capabilities of SVD. To address this issue, an improved wavelet denoising approach is proposed in this paper to enhance the accuracy of respiratory measurement frequency. Finally, the respiratory frequency measurement method based on high-speed vision is simulated and experimented, and the respiratory rate is calculated through spectral analysis. The experiments indicate that the proposed method can accurately extract the respiratory displacement signal and effectively denoise it, making it convenient for practical use.