Postural control assessment via Microsoft Azure Kinect DK: An evaluation study

Mauro Antico; Nicoletta Balletti; Gennaro Laudato; Aldo Lazich; Marco Notarantonio; Rocco Oliveto; Stefano Ricciardi; Simone Scalabrino; Jonathan Simeone

doi:10.1016/j.cmpb.2021.106324

Postural control assessment via Microsoft Azure Kinect DK: An evaluation study

Comput Methods Programs Biomed. 2021 Sep:209:106324. doi: 10.1016/j.cmpb.2021.106324. Epub 2021 Aug 4.

Authors

Mauro Antico¹, Nicoletta Balletti², Gennaro Laudato³, Aldo Lazich⁴, Marco Notarantonio⁵, Rocco Oliveto⁶, Stefano Ricciardi³, Simone Scalabrino⁷, Jonathan Simeone⁸

Affiliations

¹ Atlantica spa, Rome, Italy.
² Defense Veterans Center, Ministry of Defense, Rome, Italy; STAKE Lab, University of Molise, Pesche, IS, Italy.
³ STAKE Lab, University of Molise, Pesche, IS, Italy.
⁴ Defense Veterans Center, Ministry of Defense, Rome, Italy; DIAG, University of Rome "Sapienza", Rome, Italy.
⁵ Defense Veterans Center, Ministry of Defense, Rome, Italy.
⁶ STAKE Lab, University of Molise, Pesche, IS, Italy; Datasound srl, Pesche, IS, Italy. Electronic address: rocco.oliveto@unimol.it.
⁷ STAKE Lab, University of Molise, Pesche, IS, Italy; Datasound srl, Pesche, IS, Italy.
⁸ Datasound srl, Pesche, IS, Italy.

PMID: 34375852
DOI: 10.1016/j.cmpb.2021.106324

Abstract

Background and objective: Equipments generally used for entertainment, such as Microsoft Kinect, have been widely used for postural control as well. Such systems-compared to professional motion tracking systems-allow to obtain non-invasive and low-cost tracking. This makes them particularly suitable for the implementation of home rehabilitation systems. Microsoft has recently released a new version of Kinect, namely Azure Kinect DK, that is meant for developers, not consumers, and it has been specifically designed to implement professional applications. The hardware of this new version of the Kinect has been substantially improved as compared with previous versions. However, the accuracy of the Azure Kinect DK has not been evaluated yet in the context of the assessment of postural control as done for its predecessors.

Methods: We present a study to compare the motion traces of the Azure Kinect DK with those of a Vicon 3D system, typically considered the gold standard for high-accuracy motion tracking. The study involved 26 subjects performing specific functional reach and functional balance exercises.

Results: The results clearly indicates that the Azure Kinect DK provides a very accurate tracking of the main joints of the body for all the recording taken during the lateral reach movement. The Root Mean Square Error (RMSE) between the two tracking systems obtained is approximately 0.2 for the lateral and forward exercises while for the balance exercise it is around 0.47 considering the average of the results among all the joints. The angular Mean Absolute Error is approximately in the range 5-15 degrees for all the upper joints and independently on the exercise. The lower body joints show a higher angular error between the two systems. Not surprisingly, it was found that results are much better in correspondence of slow movements.

Conclusions: The results achieved that the Azure Kinect DK has an incredibly high potential to be used in applications of home rehabilitation, where the assessment of postural control is a fundamental and crucial activity.

Keywords: Empirical studies; Microsoft Azure Kinect; Postural control; Vicon 3D.

MeSH terms

Biomechanical Phenomena
Humans
Motion
Movement*
Postural Balance*
Reproducibility of Results