IoT Based Sleeping Disorder Recognition System for Cognitive Impairment Diseases

Abstract

In the present scenario, healthcare has made significant progress with the assistance of smart devices involving effective sensors and Internet of Things devices. In context to this, the combination of IoT and cloud architectures are rigorously exploited in order to process the large amount of data that would be generated by the wearable sensor networks in near real-time applications by making use of Artificial Intelligence supporting smart healthcare systems. In the current scenario of globalization, in addition to the increased facilities, a wide variety of other challenges are worked upon for providing quality and efficient healthcare benefits and facilities by making use of cost-effective instruments and world class technologies.<br><br>&nbsp;An important factor for the physical and mental health of a human being, the performance throughout the day as well as safety is the sleep quality. Effective quality of sleep can help avoid the risk of mental depression and chronic diseases. Sleep promotes the brain to actively get associated with the activity that is being performed and helps in preventing various accidents that might be caused due to falling asleep. For the analysis of the sleep quality, a continuous monitoring system is necessary which generates effective results. With the aid of rapid improvisation of mobile and sensor technology as well as the emerging trends of Internet of things technology, there is a good opportunity of development of a reliable and effective sleep quality monitoring system. This chapter effectively describes the background and applicability of Internet of things for such systems involved in sleep monitoring. The study begins with the review of the quality of sleep, the importance related to the monitoring of sleep quality, the employability of Internet of things in this and its relevant field, as well as the open issues and challenges in this and its related fields. <br><br>The IoT technology supports the preamble which would promote a cost effective and consistent system in order to monitor the quality of sleep-in individuals. There are several existing systems for the same purpose which involves a large amount of cost and are cumbersome to implement. To overcome the same issue, the chapter narrates an inventive system for monitoring and analyzing sleep patterns by making use of effective parameters. In this domain, a combination of clinical medicine, bioengineering, neuroscience, epidemiology, mHealth, Computer Science, as well as Human Computer interactio,n in order to approach the challenge of digitization of sleep from a multidisciplinary perspective. This chapter describes the state of art technologies involved in sleep monitoring and discusses the challenges and opportunities involved from the initial step of acquiring the data to the applicability of the acquired data based on the consumer level and clinical settings.