1. Introduction
Aging is a heterogeneous natural process that can affect all kind of living species particularly humans. This process is characterized by a decrease in functional abilities of the person. One of the major consequences of aging in humans is fragility. As a result, the aging person is subject to many incidents particularly falls. Falls are common incidents that accompany aging. They are very critical if they happen and in some cases they are fatal. Statistics show that l out of 3 persons over the age of 65 fall each year [1]. In addition, these events have many impacts on different levels. As a matter of fact, falls do not only affect the person himself by increasing his dependencies, but also impacts his environment where the cost of hospitalization and elderly care management become more significant. In this context, the need for fall detection became important. Many devices and systems were developed to detect falls. These devices use different sensor technologies. These are divided in two categories: wearable sensors systems and non-wearable sensor systems. The formers commonly use inertial sensors such as accelerometers, gyroscopes and Inertial Measurement Units (IMU), while the latter exploit environmental sensors such as pressure, motion, vibration, acoustic, and infrared sensors, etc. There are also other environmental sensors that use vision techniques through camera or radar deployment.