Towards HMM based human motion recognition using MEMS inertial sensors

Guangyi Shi, Yuexian Zou, Yufeng Jin, Xiaole Cui, Wen Jung Li

Abstract: This paper presents a new method of human motion recognition based on MEMS inertial sensors data. A Micro Inertial Measurement Unit (μIMU) that is 56mm*23mm*15mm in size was built. This unit consists of three dimensional MEMS accelerometers, gyroscopes, a Bluetooth module and a MCU (Micro Controller Unit), which can record and transfer inertial data to a computer through serial port wirelessly. Five categories of human motion were done including walking, running, going upstairs, fall and standing. Fourier analysis was used to extract the feature from the human motion data. The concentrated information was finally used to categorize the human motions through HMM (Hidden Markov Model) process. Experimental results show that for the given 5 human motions, correct recognition rate range from 90%–100%. Also, a full combination of 6 parameters (G x , G y , G z , A x , A y , A z ) was listed and the recognition rate of each combination (total 63) was tested.