Research On Mental Workload Of Music Intervention By Analysis Of ECG RR Intervals

The higher mental workload is often caused in a complex environment,Excessive mental workload can cause quickly fatigue,reduce the flexibility of the brain and reduce work performance.The mental workload in the human mind will lead to changes in the electrical activity of the sympathetic and parasympathetic nervous systems and the changes in metabolism related to the activity of the nervous system,manifested in changes in the activities of the heartbeat,ECG and EEG.Therefore,it is very important to detect and identify the mental workload.Because the ECG signal has the advantage of easy acquisition,more and more scholars use it for the study of mental workload detection and recognition.At present,most studies use a single and no intervention mental workload task,there are relatively few researches on mental workload with intervention.Therefore,based on previous studies,this thesis uses the RR interval of ECG to study the physiological mode of music intervention mental workload.The content is as follows:(1)Mental workload task design in this thesis for five digits addition and subtraction and double-digit addition and subtraction arithmetic tasks,respectively to design a music intervention conditions do arithmetic task and have no music intervention conditions do arithmetic of ECG signal acquisition experiments.Firstly,the physiological response samples of different mental loads were obtained without music intervention by relaxing the sit-ins and non-music intervention.In addition,the physiological response samples of different mental workload were obtained by relaxing the sit-ins and performing different arithmetic tasks with music intervention.Finally,combined with the scoring of the self-rating scale and the method of arithmetic task effect to determine the five-digit addition and subtraction as the high mental workload and the double digit addition and subtraction as the lower mental workload.(2)For the collected ECG data,using MATLAB for de-noising processing,the RR interval series can be obtained by using the algorithm to accurately locate and manually correct the R wave peak of the ECG signal.Then the RR interval sequence is extracted.Statistical characteristics,nonlinear characteristics,Krawtchouk moment characteristics and wavelet packet decomposition energy characteristics were extracted.It was found that the changes of physiological parameters under different state of intervention and different mental load were different.But it partly reflects the autonomic nervous activity of the heart.Under the same mental workload have music intervention status between RRmean,RRRMSSD seven physiological parameters,such as less than without music intervention,mental workload on how music intervention makes sympathetic activation,parasympathetic nerve is restrained.And the same intervention in a state of high mental workload RRmean,RR2diff five physiological parameters such as lower mental workload's value decreases,and reflect the increased mental load makes the heartbeat interval is reduced,the sympathetic nerve is activated.(3)Then use the backward feature selection algorithm to select the features,use the extreme learning machine and leave one test cross validation,BP neural network and leave one test cross validation methods to analysis physiological pattern of different intervention states with different levels of mental workload by the degree of differentiation,and the simplest feature combination under the corresponding physiological pattern is obtained.Two kinds of algorithms are used to identify and classify physiological modes with or without music intervention under the same brain load.At the same time,they recognize and classify the physiological modes of high mental load and low brain load under the same intervention state.Finally,the distinguish ability of the two datasets in the physiological mode with the task-correct and task-error under high mental load is discussed.The results show that the two datasets have poor distinguish ability.By studying the physiological mode of music intervention in mental workload,the thesis finds that physiological parameters can reflect the cardiac autonomic nervous activity of different brain loads in a certain degree.This thesis analyzes the recognition and classification of physiological pattern of different mental load under different intervention,and discusses the distinction between the task right and the task error physiology mode under the high mental workload.It can provide a certain reference value for the mental workload test in the teaching tasks.