## 1 Introduction  
According to the Department of Economic and Social Affairs of the United Nations Secretariat, the elderly population (persons of age 60 years and over) in the world in 2010 was 759 million and projected to be 1,198 million in 2025, or 15% of world population [1]. Since the people belonging to this age group are susceptible to various health issues, they tend to require more frequent healthcare treatment. However, it is considered inconvenient and costly if they have to periodically do medical check-ups in healthcare facilities that are located far from their home, not to mention the fact that they are much less mobile than younger ones. Moreover, the cost of healthcare for the elderly is more expensive than that for other aged groups. Since most of healthcare expenditures are intended to serve elderly people, this situation could become a big challenge in the future if not taken seriously, given the limited resources. Besides the healthcare cost issue, the traditional health monitoring system imposes the problem of inaccuracy. Usually, patients are monitored only at a certain point of time, and the next monitoring occurs after a considerable period of time. This would lead to incomprehensive health diagnosis. For example, a healthy patient might be diagnosed to have high blood pressure, whereas, in fact, that misdiagnosis is caused by exhaustion after he walks to the clinic. Therefore, a non-intrusive, ambulatory, continuous, yet economical health monitoring system needs to be developed to achieve a better and complete picture of health diagnosis and reduce the cost of healthcare. Currently, small and intelligent sensor devices can be attached on or even implanted into the human body, thanks to the advancement of microelectronics and micro-electro-mechanical systems (MEMS). These battery-powered devices gather patients' vital signs and send it to medical workers, e.g., physicians and nurses, for further examination and analysis. There might be more than one sensor device attached to the body. The wired connections between devices for collecting data are not effective, troublesome or even impossible for daily use. As a solution, the sensors are equipped with wireless transceivers, so that they can communicate wirelessly to transmit the sensed data. This type of network is called Wireless Body Sensor Networks (WBSNs) or, sometimes, also called Body Sensor Networks (BSNs); hereafter WBSNs. Since WBSNs are actually a subset of Wireless Sensor Networks (WSNs), WBSNs inherit the typical challenges and issues of WSNs. WBSNS are a wireless network optimized for low power devices and operation on, in or around the human body (but not limited to humans) to serve a variety of applications, including medical, consumer electronics/personal entertainment and others [2]. By this definition, WBSNs can be used in many application areas. However, current studies in WBSNs are mostly focused on medical applications, since this is the main purpose and reason for developing WBSNs. A WBSN consists of one or more sensor devices positioned on, in or around the human body. The sensor devices sense and collect data from the human body and then transmit the data to a central device, called a sink, that can be in the form of a smartphone or PDA. After collecting all information, this sink then forwards the data to the medical workers through external networks. A general example of WBSNs is shown in Figure 1.  
Despite the promising applications for healthcare systems, WBSNs also impose several challenges in network design and implementation. As the devices are attached to the human body, a careful design must be made to protect human tissue from heat caused by the radiation and device operation. Human safety becomes the most important factor in WBSNs. Another challenge is about energy efficiency. In several applications, devices are intended to operate for a long period of time. Therefore, it is not practical if the devices require frequent battery replacement, considering their location inside the human body.