ABSTRACT

With the rapid increase in the older population coupled with enhancement in their life span, the number of patients who require continuous monitoring rises tremendously. It would lead to higher costs of hospitalization and patient care globally. Hence, the requirement of smart interfaces and systems for observing health may be employed in lessening the hospitalization stay, weight on clinical staff, counseling time, holding up records, and, in general, social insurance costs. Different smart interfaces frameworks are characterized into three subcategories: remote health monitoring system (RHMS), mobile health monitoring system (MHMS), and wearable health monitoring system (WHMS). The RHMS alludes those with remote access or frameworks to communicate back and forth information or multiple patient parameters from a remote location or region. MHMSs refer to mobile phones, personal digital assistants, and pocket-personal-computer-based monitoring systems, which are utilized as the principle preparing station or at times as the primary working modules. The RHMS and MHMS are considered to be more advantageous and practical than the traditional institutional care mechanism. They empower patients to stay at their respective locations while getting access to proficient healthcare. WHMSs refer to wearable gadgets or biosensors that can be worn by patients comprising of WHMS, RHMS, and MHMS. Shrewd health monitoring systems are referred to as trendsetting innovations with regard to patient’s continuous health monitoring (R. Roine, A. Ohinmaa, and D. Hailey, “Assessing telemedicine: A systematic review of the literature,” 194 Can. Med. Assoc. J., vol. 165, no. 6, pp. 765–771, 2001). They comprise smart gadgets that could be employed to address several health-related issues. The devices measure heart rate, blood pressure, electrocardiogram, oxygen saturation levels, body temperature, and respiratory rate. This chapter would explore the development of smart interfaces for available comprehensive health monitoring systems built on artificial intelligence tools, cognitive computing systems, and machine learning algorithms.