Accuracy of the Microsoft Kinect sensor for measuring movement in people with Parkinson's disease

Brook Galna, Gillian Barry, Daniel Jackson, Dadirayi Mhiripiri, Patrick Olivier, Lynn Rochester

Research output: Contribution to journalArticlepeer-review

420 Citations (Scopus)


Background The Microsoft Kinect sensor (Kinect) is potentially a low-cost solution for clinical and home-based assessment of movement symptoms in people with Parkinson's disease (PD). The purpose of this study was to establish the accuracy of the Kinect in measuring clinically relevant movements in people with PD. Methods Nine people with PD and 10 controls performed a series of movements which were measured concurrently with a Vicon three-dimensional motion analysis system (gold-standard) and the Kinect. The movements included quiet standing, multidirectional reaching and stepping and walking on the spot, and the following items from the Unified Parkinson's Disease Rating Scale: hand clasping, finger tapping, foot, leg agility, chair rising and hand pronation. Outcomes included mean timing and range of motion across movement repetitions. Results The Kinect measured timing of movement repetitions very accurately (low bias, 95% limits of agreement 0.9 and Pearson's r > 0.9). However, the Kinect had varied success measuring spatial characteristics, ranging from excellent for gross movements such as sit-to-stand (ICC = .989) to very poor for fine movement such as hand clasping (ICC = .012). Despite this, results from the Kinect related strongly to those obtained with the Vicon system (Pearson's r > 0.8) for most movements. Conclusions The Kinect can accurately measure timing and gross spatial characteristics of clinically relevant movements but not with the same spatial accuracy for smaller movements, such as hand clasping.
Original languageEnglish
Pages (from-to)1062-1068
JournalGait and Posture
Issue number4
Early online date22 Jan 2014
Publication statusPublished - Apr 2014


Dive into the research topics of 'Accuracy of the Microsoft Kinect sensor for measuring movement in people with Parkinson's disease'. Together they form a unique fingerprint.

Cite this