Proceedings of the 5th FIRST T1 T2 2021 International Conference (FIRST-T1-T2 2021)

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Hardware Design and Lung Sound Detection Simulation to Analyze Lung Abnormalities Based on Arduino Mega, NodeMCU ESP32 and Internet of Things

Authors
Amperawan Amperawan1, *, Destra Andika1, Dewi Permatasari1, Sabilal Rasyad1, Aldi Wijaya1, Muhammad Taufiqurahman Arrasyid1, Zainudin b Mat Taib2, Nuwairani Azurawati bt Siha2
1Department of Electronic Engineering, Politeknik Negeri Sriwijaya, JL.Srijaya Negara Bukit Besar, Palembang, 30139, Indonesia.
2Department of Electrical Engineering, Politeknik Mukah Serawak, JL. Oya-Mukah KM 7, Mukah Serawak, 9640, Malaysia
*Corresponding author: amperawan230567@gmail.com
Corresponding Author
Amperawan Amperawan
Available Online 14 February 2022.
DOI
10.2991/ahe.k.220205.044How to use a DOI?
Keywords
band pass filter; paru-paru; NodeMCU ESP32; IoT
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 light-emitting 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.

Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

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Volume Title
Proceedings of the 5th FIRST T1 T2 2021 International Conference (FIRST-T1-T2 2021)
Series
Atlantis Highlights in Engineering
Publication Date
14 February 2022
ISBN
10.2991/ahe.k.220205.044
ISSN
2589-4943
DOI
10.2991/ahe.k.220205.044How to use a DOI?
Copyright
© 2022 The Authors. Published by Atlantis Press International B.V.
Open Access
This is an open access article under the CC BY-NC license.

Cite this article

risenwbib
TY  - CONF
AU  - Amperawan Amperawan
AU  - Destra Andika
AU  - Dewi Permatasari
AU  - Sabilal Rasyad
AU  - Aldi Wijaya
AU  - Muhammad Taufiqurahman Arrasyid
AU  - Zainudin b Mat Taib
AU  - Nuwairani Azurawati bt Siha
PY  - 2022
DA  - 2022/02/14
TI  - Hardware Design and Lung Sound Detection Simulation to Analyze Lung Abnormalities Based on Arduino Mega, NodeMCU ESP32 and Internet of Things
BT  - Proceedings of the 5th FIRST T1 T2 2021 International Conference (FIRST-T1-T2 2021)
PB  - Atlantis Press
SP  - 249
EP  - 254
SN  - 2589-4943
UR  - https://doi.org/10.2991/ahe.k.220205.044
DO  - 10.2991/ahe.k.220205.044
ID  - Amperawan2022
ER  -