Heart Rate Variability Based Arrhythmia Disease Detection And Cardiac State Study Under Music Stimulation

Heart rate variability(HRV)measures the time intervals between consecutive heartbeats,which can reflect changes in sympathetic and parasympathetic nerves.So HRV analysis has become the most valuable non-invasive method for assessing the autonomic nervous system.Bundle branch block is a kind of arrhythmia disease.Because the electrocardiogram(ECG)characteristics of bundle branch block are very complex,improving the accuracy of the automatic detection algorithm for the disease is a very challenging task.People have different feelings when they are stimulated by different music.How this feeling affects the heart state is still unclear.The characteristics of the bundle branch block signal and the effects of musical stimulation can be expressed by the heart rate variability parameter.In view of the above two research questions,this paper proposes to apply heart rate variability analysis to the detection of left and right bundle branch block(LBBB and RBBB)for constructing an accurate and effective bundle branch block detection method.What's more,The HRV parameters are used to characterize the state of the heart and analyze how musical stimuli affect the human body.Therefore,this paper has carried out the following two studies:(1)Bundle branch block detection method based on heart rate variabilityFirstly,the ECG signals of the LBBB,the RBBB and healthy individuals were obtained from the MIT-BIH Arrhythmia and Fantasia databases.The ECG data was preprocessed using the moving window median filtering method,and the R wave was detected by the quadratic polynomial fitting method.Then,the candidate thirty-three HRV parameters are calculated based on the ECG data.The independent sample t-test was used to make the comparative analysis for screening out the HRV parameters which with significant differences related to the LBBB and RBBB.The HRV characteristic parameters was built by the exhaustive method and then they were combined with support vector machine(SVM)and linear discriminant analysis(LDA)to construct the detection models of LBBB and RBBB.Finally,the optimal detection model is selected according to the area under the curve(AUC),sensitivity,specificity,positive predictivity and accuracy.Experiments showed that the five HRV characteristic parameters(including HR mean,HR SD,peakLF,?1 and ?2)+ SVM constituted theoptimal detection model of LBBB,the accuracy rate of which is 88.89% and the AUC value is 0.977.The optimal detection model of RBBB was composed of three characteristic parameters(SD1,SampEn and DET)+SVM.It had the accuracy rate of83.33% and the AUC value of 0.926.(2)Heart state study based on heart rate variabilityFirst,the subjects' ECG data was collected under the stimulation of three different types of music: soothing music,explosive music and non-music.Then,thirty-three HRV parameters were extracted from the ECG data of each subject.The t-test and repeated measures analysis of variance(ANONA)were used to make the comparative analysis for screening the HRV parameters which with significant differences.Finally,the effect of musical stimulation on cardiac status was revealed for each contrast situation based on the analysis of screened HRV parameters.The obtained experimental results were as follows:(i)Subjects were more excited when received soothing music stimulation,and the music with faster pace and speed can make the participants feel more relaxed and calm.In addition,the balance of autonomic nervous system changes most under the stimulation of soothing music.(ii)Males have higher sympathetic activity than females under the same type of music stimulation,and have lower vagal activity than females under soothing music and explosive music.Moreover,men's autonomic nervous system balance changes more than women when receiving music stimulation.(iii)Short-term soothing music can relax the subject.However,it needs to take a long time of the explosive music stimulation for making the subject excited.This study is of great significance for improving the accuracy of the automatic detection algorithm of bundle branch block,and is conductive to understand the effect mechanism of music stimulation on cardiac state.