Implementation of wireless MEMS sensor network for detection of gait events. (1st February 2019) - Bora, Dhruba Jyoti; Kumar, Neelesh; Dutta, Ritushree
Abstract : MEMS based wireless sensor network (WSN) for real‐time human health monitoring is promising in home‐based rehabilitation. It requires effective integration of a number of MEMS sensors and their placement on the human body to create a wireless body area network for continuous and timely monitoring of various biophysical parameters. This study attempts to develop an XBee‐based WSN for real‐time monitoring of human gait. Traditionally, the optical motion systems were used for gait analysis but they suffer from certain limitations such as the development of the complex algorithm and constrains in the work space. In comparison to the optical system, the attractive benefits of MEMS‐based sensor systems are small size and low cost. Magnetic field angular rate and gravity sensor system can perform a complete analysis of the human gait. The sensor modules were developed using the inertial sensors mainly accelerometer and gyro sensor. LabVIEW software is used for data acquisition from the body sensor nodes and gait analysis. Biometrics Lab System is used as the standard system for calibration of data obtained from sensors. The joint angle range of motion was calculated using both the systems. The advantage of the proposed system is that it facilitates wireless transmission of gait parameters (joint angle measurement) for easy monitoring of human gait in various rehabilitation programmes.