Postural control assessment via Microsoft Azure Kinect DK: An evaluation study. (September 2021)

• Record Type: Journal Article
• Authors: Antico, Mauro; Balletti, Nicoletta; Laudato, Gennaro; Lazich, Aldo; Notarantonio, Marco; Oliveto, Rocco; Ricciardi, Stefano; Scalabrino, Simone; Simeone, Jonathan
• Is Part Of: Computer methods and programs in biomedicine. Volume 209(2021)
• Publication Date: 2021-09
• Subjects: Postural control -- Microsoft Azure Kinect -- Vicon 3D -- Empirical studies; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2021.106324
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: Azure Kinect is applicable in home rehabilitation contexts. Azure Kinect shows tracking capabilities comparable to multi-cameras systems. Azure Kinect is highly accurate in tracking upper body movements. Azure Kinect is more accurate than its predecessor. 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.