## 4 Discussion
The standard errors for between-laboratory intraobserver analysis (maximum abduction at stance phase \(\sigma^{\text{sess(lab)}}=4.2\), maximum abduction at swing phase \(\sigma^{\text{sess(lab)}}=3.4\), maximum second abduction swing phase \(\sigma^{\text{sess(lab)}}=3.2\)) supports the low between-laboratory intraobserver reliability found for the knee (ICC\({}_{\text{mean}}=0.46\), Table 2). These values are twice as large as for inter- (maximum first abduction stance phase \(\sigma^{\text{observer}}=2.4\); maximum abduction/abduction swing phase \(\sigma^{\text{observer}}=1.5\); maximum second abduction swing phase \(\sigma^{\text{observer}}=1.3\)) and intraobserver reliability (maximum first abduction stance phase \(\sigma^{\text{repeated}}=0.8\); maximum abduction/abduction swing phase \(\sigma^{\text{repeated}}=1.0\); maximum second abduction swing phase \(\sigma^{\text{repeated}}=0.7\)). The lower between-laboratory intraobserver reliability and significant differences observed indicate an influence of the applied motion capturing camera technology on the captured CGA data between testing sites. In contrast to our measure of intra- and interobserver variability in the between-laboratory comparison, the effect of different hardware (cameras, lenses, Analog-to-digital (A/D) converter, etc. ), as well as marker removal and replacement between data sets can also contribute to lower reliability. The reduction in reliability suggests that the detection of tracked markers may be affected by the different camera resolutions investigated (Vcam with 0.3 million pixels, 659 x 439 black/white pixel sensor resolution vs. MXF with 2 million pixels, 1600 x 1280 grayscale pixel sensor resolution). We believe the effect of the measurement protocol and observer dependence are probably small in comparison to available technical requirements, existing in the different generations of cameras (i.e., sensor technology) because the ICC values of the one-site interobserver reliability were much higher, falling well within the excellent classification. These findings were somewhat different than those reported by [PERSON] et al. [11], who observed apparent differences during motion data captured simultaneously using three camera systems (612, MX-13 and MX-F40). Results of this study support the findings of [PERSON] et al. [8] and [PERSON] et al. [11], which showed a dependence of CGA data quality on system resources, as well as applying standardized measurement protocols. The fact that CGA data quality could be affected by different camera types, even ones from the same manufacturer, is problematic, not only in the context of multicenter investigations, but it could also be a problem when comparing CGA data within institutions that have recently updated their laboratory equipment. Based on these findings when multicenter investigations are considered, it is important that both laboratories use the same or comparable camera equipment and software. A limitation of this investigation was the sample size (\(n=3\)). Each subject performed 20 barefoot gait trials using a self-selected walking speed. Subjects had no gait pathologies, resulting in similar gait patterns. This approach included the risk of correlated observations. On the other hand, it was not feasible to conduct our investigation with actual patients (with gait pathologies) and a powered sample, due to time restrictions in subject preparation (e.g., time required for marker application) and transportation limitations between testing sites.