Implementation of wireless MEMS sensor network for detection of gait events. (1st February 2019)

• Record Type: Journal Article
• Authors: Bora, Dhruba Jyoti; Kumar, Neelesh; Dutta, Ritushree
• Is Part Of: IET wireless sensor systems. Volume 9:Number 1(2019)
• Page Start: 48
• Page End: 52
• Publication Date: 2019-02-01
• Subjects: body area networks -- patient rehabilitation -- body sensor networks -- accelerometers -- patient monitoring -- gait analysis -- microsensors -- data acquisition -- bioMEMS -- virtual instrumentation -- calibration -- medical computing; timely monitoring -- biophysical parameters -- real‐time ambulatory recording -- rehabilitation programmes -- XBee‐based WSN -- human gait -- optical motion systems -- gait analysis -- optical system -- MEMS‐based sensor systems -- gravity sensor system -- sensor modules -- inertial sensors -- gyro sensor -- body sensor nodes -- Biometrics Lab System -- standard system -- wireless transmission -- gait parameters -- wireless MEMS sensor network -- real‐time human health monitoring -- home‐based rehabilitation -- human body -- wireless body area network -- continuous monitoring -- gait event detection -- microelectromechanical system‐based wireless sensor network -- magnetic field angular rate -- accelerometer -- LabVIEW software -- data acquisition -- calibration; Wireless sensor networks -- Periodicals; 681.2
• DOI: 10.1049/iet-wss.2018.5049
• Languages: English
• ISSNs: 2043-6386

Abstract

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.