Detection, recognition and transmission of snoring signals by ESP32

This study focuses on the monitoring, transmission, recognition and detection of snoring signals and their relationship with obstructive sleep apnea. To achieve this purpose, the ESP32 microcontroller and a MEMS technology microphone were used to capture and measure characteristic parameters of snoring signals, such as their intensity, frequency and duration. In addition, the WiFi radio interface was used to send the signals to a server where the information was processed, the snoring was detected, linked to a chatbot in Nodred to show the user in a graphical interface his diagnosis of the snoring level. This comprehensive approach allows real-time, wireless monitoring of snoring, leading to a less invasive diagnosis of obstructive sleep apnea.

Authors

Institutions

Publication Details

Journal
Measurement Sensors
Published
2024-10-24
DOI
https://doi.org/10.1016/j.measen.2024.101397
Citations
1
Primary Topic
Obstructive Sleep Apnea Research
Type
article
Field-Weighted Citation Impact
0.33
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Detection, recognition and transmission of snoring signals by ESP32

Abdigal Camargo, Hernán Paz Penagos, E Jiménez, Spencer Salazar et al.
1 citations
Measurement Sensors
Obstructive Sleep Apnea Research
0.33
article

Detection, recognition and transmission of snoring signals by ESP32

Abdigal Camargo, Hernán Paz Penagos, E Jiménez, Spencer Salazar, Esteban Morales Mahecha, Diego Arturo Coy Sarmiento
article en
1 citations

Abstract

This study focuses on the monitoring, transmission, recognition and detection of snoring signals and their relationship with obstructive sleep apnea. To achieve this purpose, the ESP32 microcontroller and a MEMS technology microphone were used to capture and measure characteristic parameters of snoring signals, such as their intensity, frequency and duration. In addition, the WiFi radio interface was used to send the signals to a server where the information was processed, the snoring was detected, linked to a chatbot in Nodred to show the user in a graphical interface his diagnosis of the snoring level. This comprehensive approach allows real-time, wireless monitoring of snoring, leading to a less invasive diagnosis of obstructive sleep apnea.

Measurement SensorsVol. 36
Escuela Colombiana de Ingenieria Julio Garavito (CO)
Openalex Percentile: Top 37%
Obstructive Sleep Apnea Research
0.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.