Artificial Intelligence in Virtual Telemedicine Triage: A Respiratory Infection Diagnosis Tool with Electronic Measuring Device

Naythan Villafuerte, Santiago Manzano, Paulina Ayala and Marcelo V. García ()
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Naythan Villafuerte: Faculty of Systems, Electronics and Industrial Engineering, Universidad Tecnica de Ambato, UTA, Ambato 180206, Ecuador
Santiago Manzano: Faculty of Systems, Electronics and Industrial Engineering, Universidad Tecnica de Ambato, UTA, Ambato 180206, Ecuador
Paulina Ayala: Faculty of Systems, Electronics and Industrial Engineering, Universidad Tecnica de Ambato, UTA, Ambato 180206, Ecuador
Marcelo V. García: Faculty of Systems, Electronics and Industrial Engineering, Universidad Tecnica de Ambato, UTA, Ambato 180206, Ecuador

Future Internet, 2023, vol. 15, issue 7, 1-29

Abstract: Due to the similarities in symptomatology between COVID-19 and other respiratory infections, diagnosis of these diseases can be complicated. To address this issue, a web application was developed that employs a chatbot and artificial intelligence to detect COVID-19, the common cold, and allergic rhinitis. The application also integrates an electronic device that connects to the app and measures vital signs such as heart rate, blood oxygen saturation, and body temperature using two ESP8266 microcontrollers. The measured data are displayed on an OLED screen and sent to a Google Cloud server using the MQTT protocol. The AI algorithm accurately determines the respiratory disease that the patient is suffering from, achieving an accuracy rate of 0.91% after the symptomatology is entered. The app includes a user interface that allows patients to view their medical history of consultations with the assistant. The app was developed using HTML, CSS, JavaScript, MySQL, and Bootstrap 5 tools, resulting in a responsive, dynamic, and robust application that is secure for both the user and the server. Overall, this app provides an efficient and reliable way to diagnose respiratory infections using the power of artificial intelligence.

Keywords: respiratory infections; artificial intelligence; chatbot; vital signs; web application (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2023
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