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 snor...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
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| Series: | Measurement: Sensors |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2665917424003738 |
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| _version_ | 1846145957545115648 |
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| author | Hernan Paz Penagos Esteban Morales Mahecha Adriana Melo Camargo Edison Sanchez Jimenez Diego Arturo Coy Sarmiento Sara Valentina Hernández Salazar |
| author_facet | Hernan Paz Penagos Esteban Morales Mahecha Adriana Melo Camargo Edison Sanchez Jimenez Diego Arturo Coy Sarmiento Sara Valentina Hernández Salazar |
| author_sort | Hernan Paz Penagos |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-6eb49aedf8ac4d1d822df452bc492dcc |
| institution | Kabale University |
| issn | 2665-9174 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Measurement: Sensors |
| spelling | doaj-art-6eb49aedf8ac4d1d822df452bc492dcc2024-12-02T05:05:24ZengElsevierMeasurement: Sensors2665-91742024-12-0136101397Detection, recognition and transmission of snoring signals by ESP32Hernan Paz Penagos0Esteban Morales Mahecha1Adriana Melo Camargo2Edison Sanchez Jimenez3Diego Arturo Coy Sarmiento4Sara Valentina Hernández Salazar5Electronic Engineering Program, University Colombian School of Engineering Julio Garavito, Bogotá, ColombiaElectronic Engineering Program, University Colombian School of Engineering Julio Garavito, Bogotá, ColombiaElectronic Engineering Program, University Colombian School of Engineering Julio Garavito, Bogotá, ColombiaElectronic Engineering Program, University Colombian School of Engineering Julio Garavito, Bogotá, ColombiaElectronic Engineering Program, University Colombian School of Engineering Julio Garavito, Bogotá, ColombiaCorresponding author.; Electronic Engineering Program, University Colombian School of Engineering Julio Garavito, Bogotá, ColombiaThis 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.http://www.sciencedirect.com/science/article/pii/S2665917424003738SnoringParameter identificationRecognitionArtificial intelligence |
| spellingShingle | Hernan Paz Penagos Esteban Morales Mahecha Adriana Melo Camargo Edison Sanchez Jimenez Diego Arturo Coy Sarmiento Sara Valentina Hernández Salazar Detection, recognition and transmission of snoring signals by ESP32 Measurement: Sensors Snoring Parameter identification Recognition Artificial intelligence |
| title | Detection, recognition and transmission of snoring signals by ESP32 |
| title_full | Detection, recognition and transmission of snoring signals by ESP32 |
| title_fullStr | Detection, recognition and transmission of snoring signals by ESP32 |
| title_full_unstemmed | Detection, recognition and transmission of snoring signals by ESP32 |
| title_short | Detection, recognition and transmission of snoring signals by ESP32 |
| title_sort | detection recognition and transmission of snoring signals by esp32 |
| topic | Snoring Parameter identification Recognition Artificial intelligence |
| url | http://www.sciencedirect.com/science/article/pii/S2665917424003738 |
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