Amperawan Amperawan, Destra Andika, Dewi Permatasari, Sabilal Rasyad, Aldi Wijaya, Muhammad Taufiqurahman Arrasyid, Zainudin b Mat Taib, Nuwairani Azurawati bt Siha
{"title":"基于Arduino Mega、NodeMCU ESP32和物联网的肺部异常分析硬件设计及肺声检测仿真","authors":"Amperawan Amperawan, Destra Andika, Dewi Permatasari, Sabilal Rasyad, Aldi Wijaya, Muhammad Taufiqurahman Arrasyid, Zainudin b Mat Taib, Nuwairani Azurawati bt Siha","doi":"10.2991/ahe.k.220205.044","DOIUrl":null,"url":null,"abstract":"Hardware Design and Simulation of Lung Sound Detector to Analyze Lung Abnormalities Based on Arduino Mega and NodeMCU ESP32 is a development of auscultation technique which is supported by signal display on oscilloscope, organic light-emitting diodes and computer on the lung sound detection circuit system connected to NodeMCU ESP32. The design and simulation consists of a stethoscope as an initial detection, then amplified with a mic-condenser pre-amp circuit connected a band pass filter, a buffer amplifier entering ADC 0 (GPIO36) processed by NodeMCU ESP32 and sending data in the form of free frequency via Arduino Mega and NodeMCU ESP32 as transmitters. and mobile phones as receivers of the frequency form display of lung sounds. Software for NodeMCU ESP32 communication with mobile phone using Blink software based on Internet of Things (IoT). In detecting the condition of the patient's lungs, it provides information that on the signal display on oscilloscopes, organic lightemitting diodes, computers and mobile phone, namely by displaying the sound of the lungs when exhaling and inhaling air from the test results can detect lung sounds which have a frequency limit of 20 Hz. up to 1000 Hz. to make it easier for doctors to analyze the patient's lung abnormalities from the observed frequency.","PeriodicalId":177278,"journal":{"name":"Atlantis Highlights in Engineering","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hardware Design and Lung Sound Detection Simulation to Analyze Lung Abnormalities Based on Arduino Mega, NodeMCU ESP32 and Internet of Things\",\"authors\":\"Amperawan Amperawan, Destra Andika, Dewi Permatasari, Sabilal Rasyad, Aldi Wijaya, Muhammad Taufiqurahman Arrasyid, Zainudin b Mat Taib, Nuwairani Azurawati bt Siha\",\"doi\":\"10.2991/ahe.k.220205.044\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hardware Design and Simulation of Lung Sound Detector to Analyze Lung Abnormalities Based on Arduino Mega and NodeMCU ESP32 is a development of auscultation technique which is supported by signal display on oscilloscope, organic light-emitting diodes and computer on the lung sound detection circuit system connected to NodeMCU ESP32. The design and simulation consists of a stethoscope as an initial detection, then amplified with a mic-condenser pre-amp circuit connected a band pass filter, a buffer amplifier entering ADC 0 (GPIO36) processed by NodeMCU ESP32 and sending data in the form of free frequency via Arduino Mega and NodeMCU ESP32 as transmitters. and mobile phones as receivers of the frequency form display of lung sounds. Software for NodeMCU ESP32 communication with mobile phone using Blink software based on Internet of Things (IoT). In detecting the condition of the patient's lungs, it provides information that on the signal display on oscilloscopes, organic lightemitting diodes, computers and mobile phone, namely by displaying the sound of the lungs when exhaling and inhaling air from the test results can detect lung sounds which have a frequency limit of 20 Hz. up to 1000 Hz. to make it easier for doctors to analyze the patient's lung abnormalities from the observed frequency.\",\"PeriodicalId\":177278,\"journal\":{\"name\":\"Atlantis Highlights in Engineering\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atlantis Highlights in Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2991/ahe.k.220205.044\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atlantis Highlights in Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/ahe.k.220205.044","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hardware Design and Lung Sound Detection Simulation to Analyze Lung Abnormalities Based on Arduino Mega, NodeMCU ESP32 and Internet of Things
Hardware Design and Simulation of Lung Sound Detector to Analyze Lung Abnormalities Based on Arduino Mega and NodeMCU ESP32 is a development of auscultation technique which is supported by signal display on oscilloscope, organic light-emitting diodes and computer on the lung sound detection circuit system connected to NodeMCU ESP32. The design and simulation consists of a stethoscope as an initial detection, then amplified with a mic-condenser pre-amp circuit connected a band pass filter, a buffer amplifier entering ADC 0 (GPIO36) processed by NodeMCU ESP32 and sending data in the form of free frequency via Arduino Mega and NodeMCU ESP32 as transmitters. and mobile phones as receivers of the frequency form display of lung sounds. Software for NodeMCU ESP32 communication with mobile phone using Blink software based on Internet of Things (IoT). In detecting the condition of the patient's lungs, it provides information that on the signal display on oscilloscopes, organic lightemitting diodes, computers and mobile phone, namely by displaying the sound of the lungs when exhaling and inhaling air from the test results can detect lung sounds which have a frequency limit of 20 Hz. up to 1000 Hz. to make it easier for doctors to analyze the patient's lung abnormalities from the observed frequency.