EEMD Algorithm Research And Implementation Of Respiratory Frequency Measuring Instrument

Respiratory frequency is one of the important indicators to assess the physiological state and is an important basis for the prevention and diagnosis of diseases.At present,the clinical uses the traditional methods that are the spirometer or the pressure sensor to detect respiratory frequency.These methods obtain respiratory wave signal through the respiratory airflow directly or indirectly,but limit the patient's movement and can't integrate into remote monitoring system.People are increasingly concerned about the early warning of the disease and desirable to apply respiratory rate to remote monitoring system with the social progress and deterioration of the air environment.It is great significance to carry out effective and accurate measurement of respiratory frequency.In this thesis,respiratory rate is taken as the background and photoplethysmographic(PPG)is used as the research object,which used to research on the non-invasive continuous respiratory rate measuring methods.First,the advantages and disadvantages of the existing methods of breathing frequency measurement are analyzed.Then,an improved Ensemble Empirical Mode Decomposition(EEMD)algorithm is proposed by the shortcomings of extracting respiratory waves from PPG and the characteristics of PPG signal.In this algorithm,the noise intensity is determined by the average sub-peak amplitude of the PPG signal and the average instantaneous frequency of each layer of the decomposition is computed to reconstruct the respiratory wave by selecting the proper intrinsic mode function(IMF)and to reduce the number of decomposition layers.In order to ensure the accuracy of the algorithm,the algorithm is tested on MIMIC database and reveal that the relative correlation co-efficient(RCC)is above 0.65 and the magnitude squared coherence(MSC)is above 0.98.Finally,through the hardware design and software programming,develops a respiratory frequency measuring instrument prototype,based on DSP.It is verified that the reliability of the improving EEMD algorithm to extract respiratory rate and the accuracy of respiratory frequency measuring instrument though experimental testing and data analysis.