Wireless Detector for Lung Sound Disorder Based on DSP TMS320C6416T Module

DOI

10.2991/ahe.k.210205.102How to use a DOI?

Keywords

Lung Sound, Detector, Stethoscope

Abstract

Lung sound disorder can be one of the signs that indicate the human respiratory problems. The conventional stethoscope can be used to determine the imperfection of the lung; however, it only depends on the ability of hearing. When someone’s has problem of hearing, they cannot use this device. In addition, the sound of the conventional stethoscope sometimes cannot be heard clearly. This paper proposed a digital stethoscope that can be visualized. This research focuses on the ability of the system to transfer the signal sound into digital display that can be monitored in mobile phone. In this research, the recorded data of lung sound is stored in the PC using the ‘record sound’ program. The data was then analyzed using the waveform graph time-domain, FFT Power Spectrum, STFT Spectrogram and Wavelet Scalogram. For the communication between DSP TMS320C6416T and LabView 2012, a LabView 8.6 is used. In this research, the authors also use NodeMCU ESP826 as the Access Point of the communication. On the other hand, for generating the communication between the LabView and NodeMCU, the author used VISA (Virtual Instrument Software Architecture) of LabView 2012. From experiment to 6 patients, it can be found that the proposed device can run well and can visualize the normal lung with the frequency of 300 Hz – 600 Hz.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Nyayu Latifah Husni
AU  - Arganda Meranda
AU  - Destra Andika Pratama
AU  - Ekawati Prihatini
AU  - Selamat Muslimin
AU  - Ade Silvia Handayani
PY  - 2021
DA  - 2021/02/09
TI  - Wireless Detector for Lung Sound Disorder Based on DSP TMS320C6416T Module
BT  - Proceedings of the 4th Forum in Research, Science, and Technology (FIRST-T1-T2-2020)
PB  - Atlantis Press
SP  - 620
EP  - 626
SN  - 2589-4943
UR  - https://doi.org/10.2991/ahe.k.210205.102
DO  - 10.2991/ahe.k.210205.102
ID  - Husni2021
ER  -