Towards a Human Airbag System Using µIMU with SVM Training for Falling-Motion Recognition

which is based on MEMS accelerometers and gyro sensors is developed for real-time recognition of human body motions, specifically falling-down motions caused by slippage. A µIMU measures three-dimensional angular rates and accelerations. With an integrated microcontroller, the overall size of our µIMU is less than 26mm*20mm*20mm. We present our progress on using this µIMU based on Support Vector Machines (SVM) training to recognize falling-motions. The digital sample rate of the micro controller is 200 Hz which ensures rapid reaction to short falling time and also gives a sufficient database for SVM recognition. Experimental results show that our system can achieve a lateral falling-motion recognition rate of 100 % using selected eigenvector sets generated from 200 experimental sets. Our goal is to implement this system to a human airbag system designed to protect hip fractures of the elderly