12 Exploiting Fog Computing in Health Monitoring

Tuan Nguyen Gia and Mingzhe Jiang

12.1 Introduction

The number of people with cardiovascular diseases is at an alarming rate. According to the National Center for Health, more than 28.4 million people in the United States have cardiovascular diseases in 2015 [1]. Risks for heart diseases become higher for people with diabetes, obesity, and physical inactivity. Cardiovascular diseases can cause serious consequences such as kidney trauma, nerves injury, and even death [2]. For example, stroke, which is one of the cardiovascular diseases, kills about 129,000 Americans each year [2, 3]. To lessen the severe effects of cardiovascular diseases, health‐monitoring systems are often used in many hospitals and healthcare centers. These systems monitor vital signals such as electrocardiography (ECG), body temperature, and blood pressure. Based on the collected biosignals, medical doctors apply suitable treatment methods.

More than 30% of people over 50 years old fall every year with severe consequences [4]. Only half of those fall cases are reported to medical doctors or caregivers [5]. Dealing with injuries from an unreported fall is difficult, time‐consuming, and costly. Together with cardiovascular diseases, falling is one of the leading causes of adult disability and many other serious injuries such as brain injuries [2, 4]. Therefore, there is an urgent need for fall detection systems that can inform the incident to medical ...

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