Wrist motion assessment using Microsoft Azure Kinect DK: A reliability study in healthy individuals

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Motion Analysis

Background:

• Motion analysis systems are crucial in orthopedics and rehabilitation for diagnostics and monitoring.
• The Microsoft Azure Kinect Developer Kit (DK) has potential for clinical applications, but its use in wrist motion assessment is under-explored.
• Standardized, reliable, valid, and responsive examinations for wrist motion remain a challenge.

Purpose of the Study:

• To evaluate the reliability of hand and forearm range of motion (ROM) measurements using novel software with the Microsoft Azure Kinect DK.
• To assess the intra-day and inter-day reliability of the developed system.

Main Methods:

• Twenty-eight males and 28 females underwent active ROM measurements for wrist and forearm movements.
• Measurements were taken on three separate occasions (two sessions same day, one session one week later).
• Data were collected using custom software integrated with the Microsoft Azure Kinect DK, with reliability assessed via intraclass correlation coefficient (ICC).

Main Results:

• The software demonstrated high intra-day and inter-day reliability in both male and female participants.
• The lowest intraclass correlation coefficient (ICC) values for males were 0.846 (intra-day) and 0.816 (inter-day).
• For females, the lowest ICC values were 0.826 (intra-day) and 0.833 (inter-day).

Conclusions:

• The developed software utilizing the Microsoft Azure Kinect DK exhibits high reliability for wrist and forearm active ROM measurements.
• These findings suggest the Microsoft Azure Kinect DK is a viable tool for clinical hand assessments.
• The technology shows potential as an effective tool for hand rehabilitation programs.