Implementasi Sistem Pemantauan Batuk dengan Sensor Suara dan Akselerometer Berbasis Internet of Things (IoT)

Abstract

Chronic respiratory diseases, have a significant impact on global health, especially in developing countries. Coughing is a major symptom that plays a role in the diagnosis and transmission of TB. This study aims to design an Internet of Things (IoT)-based cough monitoring tool that can measure sound intensity and body movement acceleration. Sound sensor HH_06.03 is used to measure sound intensity (dB), while MPU6050 accelerometer measures acceleration in X, Y, and Z axes. Data was processed by an ESP32 microcontroller and presented via the Blynk app for real-time monitoring. Overall, during the clinical trial, the average cough frequency for participants with TB was significantly higher, at approximately 8 coughs in 90 seconds, compared to healthy participants, who showed an average of 4 coughs in the same duration, with a characteristic sound intensity of ±80 dB. Average accelerations were recorded at ±1.1 m/s² in the X-axis, ±2.5 m/s² in the Y-axis, and ±3.5 m/s² in the Z-axis. This finding suggests a close relationship between cough intensity and body movement. Coughs with high intensity (above 70 dB) are often accompanied by significant body movements in the Y and Z axes, indicating that loud coughs trigger stronger physical movements.