Real-time Sleep Monitoring System for Nursing Hospitals

Abstract

Purpose Recently, the fourth industrial revolution (or Industry 4.0) has become an essential mainstream tool for transitioning to digital, fully automated environments and cyber-physical systems in the medical field (Ćwiklicki et al., 2020). In particular, internet of things (IoT), big data analytics, blockchain, cloud computing, and artificial intelligence have found successive applications in the medical and healthcare sector (Yu et al., 2022). The Internet of Things (IoT) is a new concept, providing the possibility of healthcare monitoring using wearable devices. The IoT is defined as the network of physical objects which are supported by embedded technology for data communication and sensors to interact with both internal and external objects states and the environment (Haghi et al., 2017). Today, the range of wearable systems, including micro-sensors seamlessly integrated into textiles, consumer electronics embedded in fashionable clothes, computerized watches, belt-worn personal computers (PCs) with a head mounted display, glasses, which are worn on various parts of the body are designed for broadband operation (Haghi et al., 2017). The field of wearable health monitoring systems is moving toward minimizing the size of wearable devices, measuring more vital signs, and sending secure and reliable data through smartphone technology (Haghi et al., 2017). Although there has been an interest in observing comprehensive bio/non-bio medical data for the full monitoring of environmental, fitness, and medical data recently (Haghi et al., 2017), but one obvious application of wearable systems is the monitoring of physiological parameters in the mobile environment. Most commercially available wearable devices are one-lead applications to monitor vital signs (Wen et al., 2017). While most of these devices are not suitable for monitoring of high-risk patients yet, these health signals can provide early detection of diseases. Method For this study, we developed a real-time health monitoring system that constantly collect different vital signs and provide quantitative data for the user, providing better healthcare for the patients. Our system consists of both wearables (eyemask, ECG patch) and embedded sensor (air cushions) for the collection of EEG/EOG, ECG and HR/BR data that can be send to the server for data storage or data analysis. The server will organize the data allow for future use either by the doctors or managers of a nursing hospital. Results and Discussion A real-time health monitoring system for nursing hospital was developed. Details of sensors, dataflow, system architecture, and feature extractions results will be presented. In addition, our system was applied at a nursing hospital to collect 20 subjects sleep data simultaneously at the nursing hospital. Initial results showed that the system designed was able to monitor patients for two different days.