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Implementation of wireless MEMS sensor network for detection of gait events

Implementation of wireless MEMS sensor network for detection of gait events

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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.

Inspec keywords: bioMEMS; microsensors; data acquisition; calibration; virtual instrumentation; gait analysis; patient rehabilitation; medical computing; body area networks; accelerometers; body sensor networks; patient monitoring

Other keywords: biophysical parameters; MEMS-based sensor systems; sensor modules; Biometrics Lab System; inertial sensors; LabVIEW software; data acquisition; gravity sensor system; gyro sensor; accelerometer; real-time human health monitoring; calibration; optical system; wireless MEMS sensor network; continuous monitoring; gait event detection; human body; magnetic field angular rate; optical motion systems; timely monitoring; body sensor nodes; XBee-based WSN; wireless body area network; wireless transmission; human gait; real-time ambulatory recording; rehabilitation programmes; gait analysis; home-based rehabilitation; standard system; microelectromechanical system-based wireless sensor network; gait parameters

Subjects: Biomedical communication; Wireless sensor networks; Data handling techniques; Biomedical measurement and imaging; Microsensors and nanosensors; Physics of body movements; Measurement standards and calibration; Patient diagnostic methods and instrumentation; MEMS and NEMS device technology; Biology and medical computing; Micromechanical and nanomechanical devices and systems; Computerised instrumentation; Measurement standards and calibration; Patient care and treatment; Sensing and detecting devices; Computerised instrumentation; Patient care and treatment


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