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Proposal for Post Hoc Quality Control in Instrumented Motion Analysis Using Markerless Motion Capture: Development and Usability Study.

Hanna Marie RöhlingPatrik AlthoffRadina ArsenovaDaniel DrebingerNorman GigengackAnna ChorschewDaniel KronebergMaria RönnefarthTobias EllermeyerSina Cathérine RosenkranzChristoph HeesenBehnoush BehniaShigeki HiranoSatoshi KuwabaraFriedemann PaulAlexander Ulrich BrandtTanja Schmitz-Hübsch
Published in: JMIR human factors (2022)
We present a QC pipeline that seems feasible and useful for instant quality screening in the clinical setting. Results confirm the need of QC despite using standard test setups, testing protocols, and operator training for the employed system and by extension, for other task-based motor assessment technologies. Results of the QC process can be used to clean existing data sets, optimize quality assurance measures, as well as foster the development of automated QC approaches and therefore improve the overall reliability of kinematic data sets.
Keyphrases
  • quality control
  • electronic health record
  • big data
  • machine learning
  • deep learning
  • high throughput
  • data analysis
  • high resolution
  • artificial intelligence
  • single cell
  • upper limb