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Monitoring of Sitting Postures With Sensor Networks in Controlled and Free-living Environments: Systematic Review.

Arpita Mallikarjuna KappattanavarNico SteckhanJan Philipp SachsHarry Freitas da CruzErwin P BöttingerBert Arnrich
Published in: JMIR biomedical engineering (2021)
The included studies differed in various aspects of design and analysis. The majority of studies were rated as medium quality according to our assessment. Our study suggests that future work for posture classification can benefit from using inertial measurement unit sensors, since they make it possible to differentiate among spine movements and similar postures, considering transitional movements between postures, and using three-dimensional cameras to annotate the data for ground truth. Finally, comparing such studies is challenging, as there are no standard definitions of sitting postures that could be used for classification. In addition, this study identifies five basic sitting postures along with different combinations of limb and spine movements to help guide future research efforts.
Keyphrases
  • systematic review
  • machine learning
  • deep learning
  • case control
  • current status
  • quality improvement
  • electronic health record