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

AbdelRahman Tamer AbdelGawad, S. Toha, Nor Hidayati, Diyana Nordin, Ahmad Syahrin Idris
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Abstract

: 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.
实时可穿戴设备,用于预测长期covid患者的病情
:本文旨在开发一种可穿戴设备,能够预测covid-19患者的长期病情,实时通知医生。长期covid-19患者在日常活动中遭受很大痛苦,特别是如果持续症状与呼吸系统有关。通过开发一种在日常生活中佩戴方便舒适的系统,我们相信我们将能够预测covid-19患者的长期病情。该系统应首先使用人工智能检测和分析患者的呼吸模式,然后将患者的呼吸模式及其状态存储在在线数据库中,然后在紧急情况下通知医生。为了训练模型,研究人员在日常活动(如走路、坐着和爬楼梯)中捕捉了当前长期covid - 19患者和正常人的呼吸模式。我们希望开发的系统能够通过更好地监测长期患者的健康状况,帮助减轻他们的痛苦。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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