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Real Time Floor Sitting Posture Monitoring using K-Means Clustering

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Published:10 January 2019Publication History

ABSTRACT

The production of Emping Melinjo is one of cottage industries in Cilegon, Banten, which has a great potential to grow because of the high demand of the product. The major workforces in the production are females who do the labor at home. However, due to the traditional practice in the activity, workforces conduct their activities while sitting on the floor and this turned to be a potential health problem during work, such as LBP (Low Back Pain). In this paper, we proposed to build the data acquisition system for working posture and build the monitoring system that can prevent static postures. This proposed system is based on positioning posture with data clustering method using pressure measurement by 4 position sensors. Based on these 5 clusters, we defined the tracking postures as: in the middle position, backward position, forward sitting posture, and laterally tilted left or right sitting posture.

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  1. Real Time Floor Sitting Posture Monitoring using K-Means Clustering

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    • Published in

      cover image ACM Other conferences
      ICSIM '19: Proceedings of the 2nd International Conference on Software Engineering and Information Management
      January 2019
      293 pages
      ISBN:9781450366427
      DOI:10.1145/3305160

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      Publication History

      • Published: 10 January 2019

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