{"title":"声音效应对神经-心血管系统的生理模拟","authors":"M. Yahya, E. Supriyanto","doi":"10.1109/ICORAS.2016.7872619","DOIUrl":null,"url":null,"abstract":"Blood pressure and heart rate are easily influenced by factors such as nutrition, medications, exercises, emotional stress and environment. Sound is one of the environmental factors that can influence blood pressure and heart rate. Different sounds have specific characteristics that affect the neuro-cardiovascular system differently. A physiological model of the neuro-cardiovascular system has been developed to simulate the effects of sound to the blood pressure and heart rate. The purpose of this model is to obtain the explanation on how different types of sound can effects the heart rate and blood pressure measurements of a person. The model was divided into two: nervous system model and cardiovascular system model. The nervous system model were modeled using artificial neural network (ANN) while the cardiovascular system were modeled using the software Modelica. The ANN for the nervous system model managed to classify the sound with 80% accuracy for systole and diastole. As for the heart rate, the accuracy of the ANN testing is 70%. The model for the cardiovascular system were developed and managed to produce the signal for the blood pressure and heart rate without error. The present systems are not fully developed as most of the processes are still carried out manually. In conclusion, the physiological model of sound effect on neuro-cardiovascular system has been developed but improvements are still required to make the model more accurate and efficient.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Physiological modeling of sound effect on neuro-cardiovascular system\",\"authors\":\"M. Yahya, E. Supriyanto\",\"doi\":\"10.1109/ICORAS.2016.7872619\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Blood pressure and heart rate are easily influenced by factors such as nutrition, medications, exercises, emotional stress and environment. Sound is one of the environmental factors that can influence blood pressure and heart rate. Different sounds have specific characteristics that affect the neuro-cardiovascular system differently. A physiological model of the neuro-cardiovascular system has been developed to simulate the effects of sound to the blood pressure and heart rate. The purpose of this model is to obtain the explanation on how different types of sound can effects the heart rate and blood pressure measurements of a person. The model was divided into two: nervous system model and cardiovascular system model. The nervous system model were modeled using artificial neural network (ANN) while the cardiovascular system were modeled using the software Modelica. The ANN for the nervous system model managed to classify the sound with 80% accuracy for systole and diastole. As for the heart rate, the accuracy of the ANN testing is 70%. The model for the cardiovascular system were developed and managed to produce the signal for the blood pressure and heart rate without error. The present systems are not fully developed as most of the processes are still carried out manually. In conclusion, the physiological model of sound effect on neuro-cardiovascular system has been developed but improvements are still required to make the model more accurate and efficient.\",\"PeriodicalId\":393534,\"journal\":{\"name\":\"2016 International Conference on Robotics, Automation and Sciences (ICORAS)\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Robotics, Automation and Sciences (ICORAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICORAS.2016.7872619\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICORAS.2016.7872619","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Physiological modeling of sound effect on neuro-cardiovascular system
Blood pressure and heart rate are easily influenced by factors such as nutrition, medications, exercises, emotional stress and environment. Sound is one of the environmental factors that can influence blood pressure and heart rate. Different sounds have specific characteristics that affect the neuro-cardiovascular system differently. A physiological model of the neuro-cardiovascular system has been developed to simulate the effects of sound to the blood pressure and heart rate. The purpose of this model is to obtain the explanation on how different types of sound can effects the heart rate and blood pressure measurements of a person. The model was divided into two: nervous system model and cardiovascular system model. The nervous system model were modeled using artificial neural network (ANN) while the cardiovascular system were modeled using the software Modelica. The ANN for the nervous system model managed to classify the sound with 80% accuracy for systole and diastole. As for the heart rate, the accuracy of the ANN testing is 70%. The model for the cardiovascular system were developed and managed to produce the signal for the blood pressure and heart rate without error. The present systems are not fully developed as most of the processes are still carried out manually. In conclusion, the physiological model of sound effect on neuro-cardiovascular system has been developed but improvements are still required to make the model more accurate and efficient.