Towards Detecting Pneumonia Progression in COVID-19 Patients by Monitoring Sleep Disturbance Using Data Streams of Non-Invasive Sensor Networks

Abstract

Pneumonia caused by COVID-19 is a severe health risk that sometimes leads to fatal outcomes. Due to constraints in medical care systems, technological solutions should be applied to diagnose, monitor, and alert about the disease’s progress for patients receiving care at home. Some sleep disturbances, such as obstructive sleep apnea syndrome, can increase the risk for COVID-19 patients. This paper proposes an approach to evaluating patients’ sleep quality with the aim of detecting sleep disturbances caused by pneumonia and other COVID-19-related pathologies. We describe a non-invasive sensor network that is used for sleep monitoring and evaluate the feasibility of an approach for training a machine learning model to detect possible COVID-19-related sleep disturbances. We also discuss a cloud-based approach for the implementation of the proposed system for processing the data streams. Based on the preliminary results, we conclude that sleep disturbances are detectable with affordable and non-invasive sensors.

Noninvasive monitoring technologies to identify discomfort and distressing symptoms in persons with limited communication at the end of life: a scoping review

“…Only a few studies have experimented with the use of multiple noncontact sensors. Sleep or agitation was monitored using (infrared) cameras, acoustic sensors, and pressure mats in healthy adults, people with COVID-19, community-dwelling older adults, and people with dementia [ 146 – 148 ].…”

“…The reliability of the measurements of heart rate and respiration rate of healthy adults and people with dementia differed depending on the setting [ 146 ]. Infrared cameras and a pressure mat complimented each other in their registration of movement of patients with COVID-19 [ 148 ].…”

Rural Healthcare IoT Architecture Based on Low-Energy LoRa

“…More precisely, we consider how sleep monitoring of a person can be used to indicate underlying health conditions. In our previous work, we have elaborated that a combination of piezoelectric and PIR sensors that measure different physical properties, thus minimizing the possibility of noise signal contamination, show a strong correlation, and can be used to detect the person’s movement in bed during sleep [ 35 ]. For the data collection, the microcontroller can operate in the ESP32 Deep Sleep state.…”

Caring jacket: health monitoring jacket integrated with the internet of things for COVID-19 patients

“…Some research with the purpose to create pulse oximetry, detecting fatigue levels, and developing the application system of physical distancing has been done. Iswanto and Megantoro [29] created a device to detect hypoxia early symptoms using the non-invasive method with MAX30100, while Ace et al [30] use piezoelectric and a passive infrared sensor (PIR) sensors to detect pneumonia through sleep disturbance. Patel et al [31] create heart rate monitoring based on IoT to detect a heart attack.…”