Adaptive Step Length Estimation Algorithm Using Low-Cost MEMS Inertial Sensors

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Shin, S. H.; Park, C. G.; Kim, J. W.; Hong, H. S.; Lee, J. M.

Issue Date
SAS 2007 - IEEE Sensors Applications Symposium, San Diego, California USA, 6-8 February 2007
Adaptive algorithmStep detectionStep length estimationPedestrianPNS
In this paper we introduce a MEMS based
pedestrian navigation system (PNS) which consists of the low cost
MEMS inertial sensor. An adaptive step length estimation
algorithm using the awareness of the walk or run status is
presented. Future u-Health monitoring systems will be essential
equipment for mobile users under the ubiquitous computing
environment. It is well known that the cost of energy expenditure
in human walk or run changes with the speed of movement. Also
the accurate walking distance is an important factor in calculating
energy expenditure in human daily life. In order to compute the
walking distance precisely, the number of occurred steps has to be
counted exactly and the step length should be exactly estimated as
well. However the step length varies considerably with the
movements speed and status. Therefore, we recognize the
movement status such as walk or run of a pedestrian using the
small-sized MEMS inertial sensors. Based on the result, a step
length is estimated adaptively. The developed method can be
applied to PNS and health monitoring mobile system.
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College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Mechanical Aerospace Engineering (기계항공공학부)Others_기계항공공학부
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