Gait analysis with the Kinect v2: normative study with healthy individuals and comprehensive study of its sensitivity, validity, and reliability in individuals with stroke

Abstract

Background Gait is usually assessed by clinical tests, which may have poor accuracy and be biased, or instrumented systems, which potentially solve these limitations at the cost of being time-consuming and expensive. The different versions of the Microsoft Kinect have enabled human motion tracking without using wearable sensors at a low-cost and with acceptable reliability. This study aims: First, to determine the sensitivity of an open-access Kinect v2-based gait analysis system to motor disability and aging; Second, to determine its concurrent validity with standardized clinical tests in individuals with stroke; Third, to quantify its inter and intra-rater reliability, standard error of measurement, minimal detectable change; And, finally, to investigate its ability to identify fall risk after stroke. Methods The most widely used spatiotemporal and kinematic gait parameters of 82 individuals post-stroke and 355 healthy subjects were estimated with the Kinect v2-based system. In addition, participants with stroke were assessed with the Dynamic Gait Index, the 1-min Walking Test, and the 10-m Walking Test. Results The system successfully characterized the performance of both groups. Significant concurrent validity with correlations of variable strength was detected between all clinical tests and gait measures. Excellent inter and intra-rater reliability was evidenced for almost all measures. Minimal detectable change was variable, with poorer results for kinematic parameters. Almost all gait parameters proved to identify fall risk. Conclusions Results suggest that although its limited sensitivity to kinematic parameters, the Kinect v2-based gait analysis could be used as a low-cost alternative to laboratory-grade systems to complement gait assessment in clinical settings.

Test-Retest, Inter-Rater and Intra-Rater Reliability for Spatiotemporal Gait Parameters Using SANE (an eaSy gAit aNalysis systEm) as Measuring Instrument

“…SEM% < 5% is considered acceptable in this study. Score interpretation of SDC% is shown in Table 5 [25,36]. All statistical calculations were carried out in Matlab 2017b (MathWorks Inc., Natick, MA, USA); ICC algorithms in [37,38] were used.…”

“…In [25], inter and intra-rater reliability, standard error of measurement and minimal detectable change of gait parameters were calculated for a depth sensor-based system (Kinect v2). In [25], the intra-rater reliability for spatiotemporal parameters ranged approximability from 0.77 to 0.98 and the inter-rater reliability from 0.64 to 0.98.…”

“…In [25], inter and intra-rater reliability, standard error of measurement and minimal detectable change of gait parameters were calculated for a depth sensor-based system (Kinect v2). In [25], the intra-rater reliability for spatiotemporal parameters ranged approximability from 0.77 to 0.98 and the inter-rater reliability from 0.64 to 0.98. The sessions for the intra-rater reliability were carried out within 24 h. The intra-rater reliability of SANE ranged from 0.74 to 0.92 being comparable to the intra-rater reliability values found in [25].…”

“…Other comparable results are described in detail in the focused review about the validity of Kinect for gait assessment in [1], when the inter-method reliability is addressed for Kinect-based systems, generally at the same time the intra-rater reliability is assessed [10,23]. However, few studies include test-retest reliability, the intra-rater reliability and inter-rater reliability of Kinect-based systems when it is used for assessing spatiotemporal parameters of the human gait [24][25][26]; particularly, inter-rater reliability is almost never addressed. However, the three-test-retest, inter-rater and intra-rater reliability-are important to assess the agreement between measures of an instrument.…”

People Walking Classification Using Automotive Radar

“…While being a low cost sensor, Microsoft Kinect is able to track human motion without using wearable sensors and with acceptable reliability. In Reference [34], the standard error of measurement and minimal detectable change sing Kinect is evaluated, confirming the validity of this sensor with standardized clinical tests in individuals with stroke.…”