ICOST 2016: Inclusive Smart Cities and Digital Health pp 180-187 | Cite as
Design and Implementation of Fall Detection System Using MPU6050 Arduino
Abstract
Fall is the most significant causes of injury for Elderly or Epilepsy. This has led to develop a many types of automatic fall-detection systems. However, prevalent methods only use accelerometers to isolate falls from activities of daily living (ADL). This paper proposes combination of a simple threshold method and acceleration measurement to detect falls and fall-detection. To demonstrate the activity of proposed scheme a device has been designed. We used an Arduino-UNO, also we used MPU6050 as a sensor and we can measure the velocity and acceleration by calculate the derivative for the phase this program was C-language. Several fall-feature parameters and possible falls are calibrated through an algorithm. The implementation of program built to read an analogue variable from its port as an additional adjustment to fixed the upper and the lower. The total sum acceleration vector ACC to distinguish between falling and ADL. The results using the simple threshold, PMU, and combination of the simple method and MPU were compared and analyzed. The proposed MPU reduced the complexity of the hardware also the algorithm exhibited high accuracy.
Keywords
Fall Detection Systems (FDS) Activities of Daily Living (ADL) MPU6050-ArduinoReferences
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