Development Of A Respiratory Gating System Based On Back Pressure Sensing

Radiotherapy is a local medical intervention that uses radiation to treat malignant tumors.Respiration,as an important physiological activity of the human body,causes the treatment target in the thoracic or abdominal cavity to move.In fact,it is a major destabilizing factor in radiotherapy.Clinically,4-dimensional computed tomography(4D-CT)technology is often used to evaluate the movement of the target.In other words,the patient’s respiratory signal is simultaneously recorded while the patient is undergoing a CT scan,and then the CT slices are reconstructed according to the respiratory phase to form 4D-CT images.Traditional respiratory signal acquisition often has limitations in clinical applicability and patient comfort.In this thesis work,based on the characteristics of the pressure between the muscles of the human back and the CT couch,a novel respiratory signal acquisition system is designed for 4D-CT data acquisition.The main content of the thesis work is as follows.(1)The design and development of the system hardware.Firstly,12 thin-film piezoresistive sensors are used for multi-point pressure collection on the back of body to ensure that effective respiratory signals can be collected.Then a signal conditioning circuit for signal conversion and filtering is designed to convert the resistance signal to voltage signal and suppress the noise.Then Arduino Mega 2560 is used to realize the analog-to-digital conversion and signal transmission.(2)The design of the system software and signal processing algorithms.Firstly,a graphic user interface is designed to realize real-time signal display and recording.Then,the signal-to-noise ratio is defined according to the frequency characteristics of the respiratory signal,and the optimal respiratory data extraction from the 12-channel pressure signal is realized.Since the collected digital pressure signal has a large amount of noise,which may impair the subsequent analyses,three filtering methods are implemented and compared,including the classic digital filtering,wavelet denoising,and empirical mode decomposition.Finally,the peaks and valleys of the respiratory signal are detected through extreme point detection and prominence threshold setting,and then the respiratory phase is calculated.The real-time position management(RPM)system is used as the reference system for the performance evaluation of the proposed system in this thesis.In the first experiment,the motion of a phantom is used to simulate the respiration and the results indicate that the proposed and the RPM systems perform equally well.In the second experiment,both the proposed and the RPM systems are used to acquire human respiratory signals.With signals collected from 10 healthy subjects,between the two systems,the correlation coefficient is 0.85 ± 0.10(mean ± standard deviation),the root mean square error is 0.17 ± 0.04,and the time shift is 0.26 ± 0.16 second.In conclusion,the multi-channel respiratory signal acquisition system based on back pressure proposed in this thesis can successfully collect respiratory signal for 4D-CT imaging.The respiratory signal acquired by the proposed system is highly correlated with the RPM system,indicating that the proposed system may be used as an alternative to the RPM system.Hopefully,the proposed respiratory signal acquisition system may play a role in radiotherapy applications.