Document Type : Technical note


Ph.D Student, Bioelectric Department, Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran


Falls are one of the main reasons to injury, especially in the elderly people. These injuries can be reduced by quick and accurate response or reaction, but this is not possible often in elderly people because they usually live alone and after injury caused the falling, cannot call for help. This paper presents a fall detection system to do twomajor tasks properly and quickly; firstly, it shoulddetect fall from other daily activities andsecondly, transmit falling person’s necessary information to help. This system is implemented on Android-based smartphone and it used tri-axial accelerometer and microphone to fall detection. Everydayinteraction with the smartphone makes our system more familiarto the user. The accelerometer is used to record variations of acceleration in three directions.Thissystem isimproved with detecting the noise caused the falling, by analyzing environmental sounds. After fall detection, a warning text message that contains information about time and location of the falling will besent to the caregivers. A comprehensive evaluation with 18 volunteers shows that the proposed system has sensitivity of 96% and specificity of 77% for different types of fall in quiet and noisy environments.


Main Subjects

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