Validation of Foot Placement Locations from Ankle Data of a Kinect v2 Sensor

D.J. Geerse*, B. Coolen, D.T.T.I. Kolijn, M. Roerdink

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


The Kinect v2 sensor may be a cheap and easy to use sensor to quantify gait in clinical settings, especially when applied in set-ups integrating multiple Kinect sensors to increase the measurement volume. Reliable estimates of foot placement locations are required to quantify spatial gait parameters. This study aimed to systematically evaluate the effects of distance from the sensor, side and step length on estimates of foot placement locations based on Kinect’s ankle body points. Subjects (n = 12) performed stepping trials at imposed foot placement locations distanced 2 m or 3 m from the Kinect sensor (distance), for left and right foot placement locations (side), and for five imposed step lengths. Body points’ time series of the lower extremities were recorded with a Kinect v2 sensor, placed frontoparallelly on the left side, and a gold-standard motion-registration system. Foot placement locations, step lengths, and stepping accuracies were compared between systems using repeated-measures ANOVAs, agreement statistics and two one-sided t-tests to test equivalence. For the right side at the 2 m distance from the sensor we found significant between-systems differences in foot placement locations and step lengths, and evidence for nonequivalence. This distance by side effect was likely caused by differences in body orientation relative to the Kinect sensor. It can be reduced by using Kinect’s higher-dimensional depth data to estimate foot placement locations directly from the foot’s point cloud and/or by using smaller inter-sensor distances in the case of a multi-Kinect v2 set-up to estimate foot placement locations at greater distances from the sensor.
Original languageEnglish
Article number2301
Issue number10
Publication statusPublished - 2017


Acknowledgments: We are grateful to Microsoft for accepting Bert Coolen and Melvyn Roerdink as members of the Kinect for Windows developers program, allowing us to work with the Kinect v2 sensor and SDK before its commercial release. We would like to acknowledge John Stins from the Department of Human Movement Sciences for introducing us to the TOST procedure. This work is part of the research program Technology in Motion (TIM [628.004.001]), which is financed by the Netherlands Organisation for Scientific Research (NWO).

FundersFunder number
Nederlandse Organisatie voor Wetenschappelijk Onderzoek


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