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Real-time wearable device for predicting a long covid patient's condition

AbdelRahman, AbdelGawad Tamer and Nordin, Nor Hidayati Diyana and Toha, Siti Fauziah and Idris, Ahmad Syahrin (2022) Real-time wearable device for predicting a long covid patient's condition. In: 8th International Conference on Mechatronics Engineering (ICOM 2022), 09-10 August 2022, Kuala Lumpur.

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This paper aims to develop a wearable device that can be able to Predict the long covid-19 patients’ conditions, to notify the doctors on a real-time basis. Long covid-19 patients suffer a lot during their daily activities especially if the lasting symptom is related to the respiratory system. By developing a system, that is easy and comfortable to wear during normal daily life, we believe that we will be able to predict the long covid-19 patients’ condition. The system should first detect and analyze the patient’s breathing pattern using artificial intelligence then store the patient’s breathing pattern along with his status in an online database, then notify the doctors in case of a critical situation. To train the model the breathing pattern of current long covid patients and normal people was captured during doing daily activities such as walking, sitting, and climbing stairs. We hope that the developed system will help in easing the suffering of long covid patients by providing better monitoring of their health.

Item Type: Conference or Workshop Item (Poster)
Subjects: T Technology > T Technology (General)
T Technology > T Technology (General) > T351 Mechanical drawing. Engineering graphics
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User: Dr. Siti Fauziah Toha
Date Deposited: 21 Dec 2022 11:26
Last Modified: 21 Dec 2022 11:28
URI: http://irep.iium.edu.my/id/eprint/101570

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