Smart health system to monitor people in COVID-19 quarantine

The global coronavirus pandemic has spread to 187 countries and territories, infecting more than 4.17 million people. Most countries, especially those with a skyrocketing caseload, grapple with a lack of hospital beds and facilities to cater to every patient infected with the virus. Now, a team of researchers may have the solution to this problem – a smart health system to monitor patients who are in home isolation.

The researchers from Cairo University in Egypt suggest a smart health system may help reduce the burden on hospitals, leaving only severe and critical patients in the facilities. Known as the EQuarantine system, the new technology monitors coronavirus patients remotely, especially those in home-quarantine.

The proposed smart health system for monitoring infected coronavirus remotely based on Internet-of-Things devices
The proposed smart health system for monitoring infected coronavirus remotely based on Internet-of-Things devices

Monitoring patients remotely

Amid the coronavirus crisis, many patients who are infected with the virus are left without the care they need, particularly those who are experiencing mild to moderate symptoms. It is essential to monitor them because of the nature of the disease, which may lead to drastic and abrupt changes in their health status.

The new system is based on combined data from various sensors to detect disease progression and severity. The patient's heart rate, blood pressure, and respiratory rate can be monitored. Further, the blood pH of the patient can also be measured in real-time. Blood pH can indicate the patient's overall health status.

The vital signs readings and other data gathered will be combined to determine the patient's health status. The EQuarantine system could also help monitor many uses simultaneously.

The research team proposes the use of artificial intelligence to monitor patients remotely, with the guarantee that patients still receive medicines and the care they need, without overwhelming the health system.

"The proposed system enables monitoring patients from their homes that save governmental cost and time through measuring the changes in patient's medical readings. It will serve humanity in the reduction of coronavirus infection and save healthcare members around the world. It also saves hospital places for emergency cases," the researchers wrote in the paper.

The EQuarantine system monitors the patient's case flow and estimates the emergency causes in 24 hours by as much as 98.7 percent. It bases its result from five parameters – heart rate, blood pressure, respiratory rate, body temperature, and blood pH level.

What is smart health?

The primary purpose of smart health is remotely monitored patients for a disease that can help save lives, time, and cost. Monitoring the patient's condition in real-time can help reduce hospital costs, especially during a pandemic where most hospitals are grappling with high numbers of patients.

With the remote monitoring of patients, those who are in home isolation or quarantine during the pandemic are still taken care of without the risk of infecting others, such as health workers.

Due to the technological advancements in the field of medicine, smart health has been the focus of research. Smart health can provide aid in situations like this since it can monitor the patient in several ways – text, audio, and video. Sensors are used to get a real-time update of the patient's health condition.

Combining machine learning algorithms and artificial intelligence, the novel technology can predict and evaluate patients who are quarantined in their homes.

Combining data for health workers

Aside from smart health, the researchers explored the use of deep learning and the data fusion process to come up with an idea for a home monitoring system, which was published in the open-source preprint server Arxiv.

Deep learning is a type of artificial intelligence function that mimics the works of the brain in processing data and generating patterns for decision making. It is also called a deep neural network or deep neural learning. The essential idea of this function depends on artificial neural networks (ANNs), which is a new trend in active research. It involves big data analysis for many applications, such as pattern recognition, natural language processing, speech recognition, and computer vision, among others.

Further, the new system will also need a data fusion process to gather and mix multiple sources of data. Data fusion is the process needed to provide more accurate results, thanks to many data sources. With a sound data fusion system, doctors can have an idea of the patient's health status that can guide decision making in the plan for care.

"The proposed smart Health System aims at monitoring coronavirus patients for remotely quarantine. It targets saving thousands of lives from infection or death. It depends on the integration between artificial intelligence and internet-of-things for fusing multiple sensory data from various medical sensors to detect the degree of development of the disease and the seriousness of the health condition," the researchers wrote.

*Important Notice

Arxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Source:
Journal reference:
  • El-Din, D., Hassanein, A., Hassanien, E., and Hussein, W. (2020). E-Quarantine: A Smart Health System for Monitoring Coronavirus Patients for Remotely Quarantine. Arxiv. https://arxiv.org/abs/2005.04187
Angela Betsaida B. Laguipo

Written by

Angela Betsaida B. Laguipo

Angela is a nurse by profession and a writer by heart. She graduated with honors (Cum Laude) for her Bachelor of Nursing degree at the University of Baguio, Philippines. She is currently completing her Master's Degree where she specialized in Maternal and Child Nursing and worked as a clinical instructor and educator in the School of Nursing at the University of Baguio.

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