| Literature DB >> 32537483 |
Hafedh Ben Hassen1,2, Nadia Ayari1, Belgacem Hamdi1,3.
Abstract
In recent years, the world has witnessed a significant increase in the number of elderly who often suffer from chronic diseases, and has witnessed in recent months a major spread of the new coronavirus (COVID-19), which has led to thousands of deaths, especially among the elderly and people who suffer from chronic diseases. Coronavirus has also caused many problems in hospitals, where these are no longer able to accommodate a large number of patients. This virus has also begun to spread between medical and paramedical teams, and this causes a major risk to the health of patients staying in hospitals. To reduce the spread of the virus and maintain the health of patients who need a hospital stay, home hospitalization is one of the best possible solutions. This paper proposes a home hospitalization system based on the Internet of Things (IoT), Fog computing, and Cloud computing, which are among the most important technologies that have contributed to the development of the healthcare sector in a significant way. These systems allow patients to recover and receive treatment in their homes and among their families, where patient health and the hospitalization room environmental state are monitored, to enable doctors to follow the hospitalization process and make recommendations to patients and their supervisors, through monitoring units and mobile applications developed for this purpose. The results of evaluation have shown great acceptance of this system by patients and doctors alike.Entities:
Keywords: Cloud computing; Coronavirus; Fog computing; Health monitoring; Home hospitalization; Internet of Things (IoT)
Year: 2020 PMID: 32537483 PMCID: PMC7282767 DOI: 10.1016/j.imu.2020.100368
Source DB: PubMed Journal: Inform Med Unlocked ISSN: 2352-9148
Fig. 1The general architecture of the proposed home hospitalization system.
The components of the proposed environmental sensing unit.
| Component | Description |
|---|---|
| NodeMCU V3 | The NodeMCU V3 is an open-source ESP12E module based development platform for creating IoT connected objects [ |
| Temperature and humidity detection module (DHT 11) | This sensor-based module provides a digital output proportional to the temperature and humidity measured by the sensor. The technology used to produce the DHT 11 sensor guarantees high reliability, excellent long-term stability and very fast response time. |
| Smoke detection module (MQ2 sensor) | This module is based on the MQ2 gas sensor to detect smoke, hydrogen, LPG, I-butane, propane, methane and alcohol. It provides high sensitivity, which is adjustable by a potentiometer, and fast response time. |
| Gas leak detection module (MQ5 sensor) | This module is based on the MQ5 gas sensor to detect (for demotic and industrial uses) gas leaks. It can detect LPG, natural gas, city gas... With a fast response time, it is ideal for quickly detecting the presence of a gas. It is equipped with a potentiometer to adjust the sensitivity. |
| Analog to digital converter (ADC) | This module is an analog-to-digital converter (ADC) that converts an analog quantity into a digital value (coded over several bits), proportional to the ratio between the input analog quantity and the maximum value of the signal. Since we have in this system analog sensors (gas sensor MQ2 and gas sensor MQ5) then we need an analog-to-digital converter because the NodeMCU V3 contains a single analog input and for that, we will use the MCP3008-I/P analog-digital converter from Microchip Technologie Inc. The MCP3008-I/P communication with the NodeMCU V3 is performed using a simple serial interface compatible with the SPI protocol. |
| Power supply | For the power supply to the NodeMCU V3, the voltage must be between 3.3 V and 9 V. Under no circumstances should this input voltage be exceeded. It can thus be seen that the card is powered by connecting a 3.3 V power source to one of the 3.3 V terminals, by connecting to a micro USB with a USB cable or by connecting a source to VIN. For this, we used a 5 V power supply to power the NodeMCU V3 and the other modules of the system. |
Fig. 2The architecture of the proposed Cloud computing.
Fig. 3The environmental sensing unit and the Android application interfaces.
Fig. 4Some Android application interfaces for patient health monitoring.
Fig. 5Measurement process of SpO2, heart rate, and body temperature.
Fig. 6Measurement process of ECG.
Fig. 7The medical report creation process.
Fig. 8Some Android application interfaces for the doctors.
Fig. 9Some Android application interfaces for the patient and their relatives and the administrators.
Fig. 10The system usability scale (SUS).
Patients’ SUS score.
| Patient 1 | Patient 2 | Patient 3 | Patient 4 | Patient 5 | |
|---|---|---|---|---|---|
| 5 | 4 | 5 | 5 | 5 | |
| 1 | 1 | 2 | 2 | 1 | |
| 4 | 5 | 5 | 5 | 5 | |
| 1 | 2 | 2 | 2 | 1 | |
| 5 | 5 | 4 | 5 | 5 | |
| 2 | 2 | 1 | 1 | 1 | |
| 4 | 5 | 5 | 4 | 5 | |
| 1 | 2 | 1 | 2 | 2 | |
| 5 | 5 | 4 | 5 | 4 | |
| 1 | 1 | 2 | 1 | 1 | |
Doctors’ SUS score.
| Doctor 1 | Doctor 2 | Doctor 3 | Doctor 4 | Doctor 5 | |
|---|---|---|---|---|---|
| 5 | 5 | 5 | 5 | 5 | |
| 1 | 2 | 1 | 1 | 2 | |
| 5 | 5 | 5 | 4 | 5 | |
| 1 | 2 | 2 | 1 | 1 | |
| 5 | 5 | 4 | 4 | 4 | |
| 2 | 1 | 1 | 1 | 1 | |
| 5 | 5 | 5 | 5 | 5 | |
| 1 | 1 | 2 | 2 | 1 | |
| 4 | 4 | 5 | 5 | 5 | |
| 1 | 1 | 2 | 1 | 1 | |