An automatic calibration technique for force sensors in a dynamic smart floor environment
Burns, Nicholas Brent Daniel, Kathryn Huber, Manfred Zaruba, Gergely
Burns, Nicholas Brent
Daniel, Kathryn
Huber, Manfred
Zaruba, Gergely
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2021-10-17
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N. B. Burns, K. Daniel, M. Huber and G. Záruba, "An Automatic Calibration Technique for Force Sensors in a Dynamic Smart Floor Environment," 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2021, pp. 2471-2478, doi: 10.1109/SMC52423.2021.9659228.
Abstract
Pressure-sensitive smart floors deployed within homes can give great insight to the health and activity level of
individuals through gait and location information. Due to the ever-changing dynamic nature of household deployments
involving furniture movement, floor tile shifts, and sensor drift, challenges arise in ensuring the constant reliability of floor
sensor readings over time. This paper presents a procedure to automatically calibrate a smart floor’s force sensors without
specialized physical effort. The calibration algorithm automatically filters out non-human static weight while
retaining weight generated by human activity. This technique is designed to correctly translate sensor values to weight units even
when direct access to the force sensors is not available and when a shared tile floor sits above the sensor grid. These calibrated
sensor values can then feed machine learning techniques used to extract individual contact points generated by a person’s
walking cycle. Using known human weights but no knowledge of the human’s location or walking trajectory, this calibration
technique resulted in small percentage differences of -7.8%, - 4.8%, and -1.6% for the mean, median, and mode of calibrated
smart floor walking sequences, respectively.
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IEEE
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2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC);2021
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2577-1655
1062-922X
1062-922X