A Real Time Fall Detection System Using Tri-Axial Accelerometer and Clinometer Based on Smart Phones

In this paper, we design a method to use smart phone to detect when fall accident happened, it can inform outside people or organization automatically to get help from them. The smart phone has implemented several sensors, such as the tri-axial accelerometer, electronic compass, global positioning system (GPS) etc. We will use those sensors to do fall detection. This detection system is used by placing in the waist pocket. Because people activity can be recorded real time by center of gravity in the body. We collect data for normal movements and fall events to setup a database, and then do the data analysis real time to identify if it is normal movement or fall event. To offload system operation loading and increase the efficiency on the fall detection, this paper will be divided into two parts. In the first part, in order to make the identification more lightweight, the collected data will be used to do the data blurring by weighted moving average. This way can make system easy to comparison and will not lose fall event feature. In the second part, we input the processed data to do fall detection. Three features weightlessness, impact and stillness are used to identify if it is fall event or not. If fall accident is true, system will send warning message and location automatically to the people or organization who we predefined in the system to get help. The results of our research can be used by everyone and everywhere if wireless network connection is valid. This system can be used in various environments and it is very convenient to hand carry and easy to use. So the acceptance from general people should be very high for them can use this system to get help in time to save their life or mitigate the damage.