Abstract
The aim of this paper is to show a method that can be used to monitor the human posture in an industrial environment. The method is based on the fu- sion of the data coming from two different sensors: a time-of-flight camera (Microsoft Kinect V2) and a wearable motion capture system that uses inertial measurement units to identify the body posture (Notch Wearable). The combined use of these two systems overcomes the intrinsic limitations of the two methods, deriving from occlusions and electromagnetic interferences, respectively. First, the algorithms implemented and the calibration of the two measurement systems in a controlled environment are described. Second, the method applied in a workplace to monitor the posture of the workers during different tailoring operations, is explained. The data acquired have been analyzed in the time domain, and used to compute the cumulative probability density function of different body angles. The results are compared to the subjective evaluation of occupational doctors, and used to compute the OCRA index in an auto- mated way, for the assessment of workers exposure to repetitive movements of the upper limbs.
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Tarabini, M. et al. (2019). Real-Time Monitoring of the Posture at the Workplace Using Low Cost Sensors. In: Bagnara, S., Tartaglia, R., Albolino, S., Alexander, T., Fujita, Y. (eds) Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018). IEA 2018. Advances in Intelligent Systems and Computing, vol 820. Springer, Cham. https://doi.org/10.1007/978-3-319-96083-8_85
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DOI: https://doi.org/10.1007/978-3-319-96083-8_85
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