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A novel cost-effective postural tracking algorithm using marker-based video processing.

Ramtin NazerianOrhan KorhanEhsan Shakeri
Published in: International journal of occupational safety and ergonomics : JOSE (2021)
Recently, many postural analysis techniques have been developed in order to reduce the risk of musculoskeletal problems. Methods such as rapid entire body assessment are capable of analyzing the most constant or awkward positions, but the selection of these postures is subjective. To make an objective postural analysis, devices such as electromagnetic trackers can be used continuously during the job task, but utilizing such devices is costly. Therefore, in this study a cost-effective marker-based video processing algorithm is developed for measuring three-dimensional (3D) information regarding both the location and the orientation of human posture. To investigate the precision of the measurements, an experiment was designed. With the average of 2.88 mm and 1.34° for location and orientation, respectively, the algorithm was able to measure six degrees of freedom information regarding 3D space. Furthermore, the precision of the algorithm is found to be significantly affected by the marker pattern.
Keyphrases
  • machine learning
  • deep learning
  • mental health
  • endothelial cells
  • neural network
  • high frequency
  • social media
  • sleep quality