Browse > Article
http://dx.doi.org/10.12674/ptk.2019.26.1.001

Accuracy Comparison of Spatiotemporal Gait Variables Measured by the Microsoft Kinect 2 Sensor Directed Toward and Oblique to the Movement Direction  

Hwang, Jisun (Department of Physical Therapy, Graduate School of Hoseo University)
Kim, Eun-jin (Department of Physical Therapy, Hoseo University)
Hwang, Seonhong (Department of Physical Therapy, Hoseo University)
Publication Information
Physical Therapy Korea / v.26, no.1, 2019 , pp. 1-7 More about this Journal
Abstract
Background: The Microsoft Kinect which is a low-cost gaming device has been studied as a promise clinical gait analysis tool having satisfactory reliability and validity. However, its accuracy is only guaranteed when it is properly positioned in front of a subject. Objects: The purpose of this study was to identify the error when the Kinect was positioned at a $45^{\circ}$ angle to the longitudinal walking plane compare with those when the Kinect was positioned in front of a subject. Methods: Sixteen healthy adults performed two testing sessions consisting of walking toward and $45^{\circ}$ obliquely the Kinect. Spatiotemporal outcome measures related to stride length, stride time, step length, step time and walking speed were examined. To assess the error between Kinect and 3D motion analysis systems, mean absolute errors (MAE) were determined and compared. Results: MAE of stride length, stride time, step time and walking speed when the Kinect set in front of subjects were investigated as .36, .04, .20 and .32 respectively. MAE of those when the Kinect placed obliquely were investigated as .67, .09, .37, and .58 respectively. There were significant differences in spatiotemporal outcomes between the two conditions. Conclusion: Based on our study experience, positioning the Kinect directly in front of the person walking towards it provides the optimal spatiotemporal data. Therefore, we concluded that the Kinect should be placed carefully and adequately in clinical settings.
Keywords
Gait analysis; Kinect; Motion capture; Spatiotemporal parameter;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
연도 인용수 순위
1 Chae YS. A serious game design and prototype development for rehabiltation using KINECT tools. J Korean Multimed Soc. 2014;17(2):248-256.   DOI
2 Choi HS. Kinect-based motion recognition model for the 3D contents control. International Journal Of Contents. 2014;14(1):24-29.
3 Chung CY, Park MS, Choi IH, et el. Three dimensional gait analysis in normal korean A preliminary report. J Korean Orthop Assoc. 2005;40(1):83-88.   DOI
4 Corazza S, Mundermann L, Chaudhari AM, et al. A markerless motion capture system to study musculoskeletal biomechanics: Visual hull and simulated annealing approach. Ann Biomed Eng. 2006;34(6):1019-1029. https://doi.org/10.1007/s10439-006-9122-8   DOI
5 Daphne JG, Bert HC, Melvyn R. Kinematic validation of a multi-kinect v2 instrumented 10-meter walkway for quantitative gait assessments. PLoS ONE. 2015;10(10):1-15. https://doi.org/10.1371/journal.pone.0139913
6 Kim G, Yoon NM. A study on kinetic gait analysis of the normal adult. J Kor Soc Phys Ther. 2009;21(2):87-95.
7 Hollmn JH, McDade EM, Petersen RC. Normative spatiotemporal gait parameters in older adults. Gait Posture. 2011;34(1):111-118. https://doi.org/10.1016/j.gaitpost.2011.03.024   DOI
8 Jung GI. A New approach for measuring of stride length using optical method. Seoul, Konkuk University, Master Thesis. 2010.
9 Kim CK, Son WJ. Trends analysis of animation technology using motion capture system. Journal of Korea Design Forum. 2008;19:203-211.
10 Kim JJ, Gwon SJ, Lee YS. Smart remote rehabilitation system based on the measurement of heart rate from ECG sensor and kinect motion-recognition. J Sens Sci Tech. 2015;24(1):69-77.   DOI
11 Lee G, Cho CH, Lim KJ, et al. Efect of direction to be used for the timed up and go test on walking time in stroke patients. Phys Ther Kor. 2016;23(2):1-19. https://doi.org/10.12674/ptk.2016.23.2.011   DOI
12 Mentiplay BF, Perraton LG, Bower KJ, et al. Gait assessment using the Microsoft Xbox One Kinect: Concurrent validity and inter-day reliability of spatiotemporal and kinematic variables. J Biomech. 2015;48(10):2166-2170. https://doi.org/10.1016/j.jbiomech.2015.05.021   DOI
13 Oh YS, Woo YK. The effects of backward walking training with inclined treadmil on the gait in chronic stroke patients. Phys Ther Kor. 2016;23(3):1-10. https://doi.org/10.12674/ptk.2016.23.3.001   DOI
14 Pfister A, West AM, Bronner S, et al. Comparative abilities of Microsoft Kinect and Vicon 3D motion capture for gait analysis. J Med Eng Technol. 2014;38(5):274-280. https://doi.org/10.3109/03091902.2014.909540   DOI
15 Yang ST, Kang DW, Seo JW, et al. Evaluation of balance ability of the elderly using kinect sensor. Trans Korean Inst Electr Eng. 2017;66(2):439-446.   DOI
16 Valmassy R. Clinical Biomechanics of the Lower Extremities. Height. MD, MO. Mosby, 1996.
17 Xu X, McGorry RW, Chou LS, et al. Accuracy of the Microsoft Kinect for measuring gait parameters during treadmill walking. Gait Posture. 2015;42(2):145-151. https://doi.org/10.1016/j.gaitpost.2015.05.002   DOI
18 Yang HD. Conditional random field based gesture recognition with Kinect sensor. Journal of KISS : Software and applications. 2013;40(11);716-723.