## 4 Discussion  
The purpose of the present study was to compare the accuracy of gyroscopes and electrogoniometers when measuring evVel and t_evVel. The results of evVel revealed a small MD between 10.4 \(\pm\) 49.3 and 49.8 \(\pm\) 46.9 deg/s, which was lower than the difference reported by [PERSON] et al. [10]. They compared angular velocities in the frontal plane obtained from an optoelectronic system and a gyroscope and found an MD of 77.9 deg/s. The greatest MD found in our study (49.8 \(\pm\) 46.9 deg/s) was distinctly lower than the repeatability coefficient found by [PERSON] et al. [7] when investigating within-subject variability of the maximum version velocity (169.0 deg/s). This means that our MDs were within the limits of total measurement variability, and therefore were considered non-relevant. Furthermore, high standard deviations--in some cases higher than MD--show that there was also a high variability within the subjects. One reason could be the individual walking and running gait of the subjects, which can slightly influence the measurement of evVel_Gonio and evVel_Gyro. Additionally, footwear conditions and locomotion velocities can influence rearfoot motion of subjects [4; 5; 9; 12; 22]. In our study, the softest shoe (AS) showed the lowest evVel compared to the harder shoes (PU and AD). This is in line with previous findings [4; 5; 23]. While MD was similar for the footwear conditions during walking, there was a general trend of decreasing differences between evVel_Gyro and evVel_Gonio seen for all running velocities with decreasing footwear stiffness (AD > PU > AS) (Table 2 and Figure 1). MD was even negative for the softest shoe (AS), which means that higher evVel was measured with the electrogoniometer than with the gyroscope. It seems that MD is influenced by footwear conditions and locomotion velocities. We could not conclusively determine which measurement device was influenced by which conditions. However, as mentioned, MD was small and within the variability, and therefore, MD can be declared non-relevant, regardless of positive or negative values. Furthermore, Pearson's correlation coefficient showed a very large positive correlation of at least \(r\geq 0.88\) for all tested footwear conditions and locomotion speeds between evVel_Gonio and evVel_Gyro. The correlations in our study are larger than those reported in previous studies comparing maximum angular velocities of gyroscopes with optoelectronic systems [8; 10; 14]. One reason for the lower correlations in the mentioned studies may be marker-artifacts due to wobbling during initial ground contact and the subsequent problematic foot model calculations by the respective software. In our study, both devices were attached firmly to the heel cap of the right shoe to minimize wobbling, \begin{table}
\begin{tabular}{c c c c c c} \hline
**Speed** & **Footwear Condition** & **MD (ms)** & **SD (ms)** & \(r\) & \(R^{2}\) \\ \hline \multirow{3}{*}{1.5 m/s} & AD & 4.1 & 2.4 & 0.88 [1] & 0.77 [2] \\  & AS & 5.2 & 4.4 & 0.78 [1] & 0.60 [2] \\  & PU & 5.3 & 3.5 & 0.86 [1] & 0.73 [2] \\ \hline \multirow{3}{*}{2.5 m/s} & AD & 3.4 & 3.4 & 0.89 [1] & 0.77 [2] \\  & AS & 1.6 & 3.7 & 0.88 [1] & 0.76 [2] \\  & PU & 1.0 & 6.6 & 0.71 [1] & 0.49 [2] \\ \hline \multirow{3}{*}{3.5 m/s} & AD & 3.2 & 2.0 & 0.91 [1] & 0.83 [2] \\  & AS & 2.8 & 2.2 & 0.92 [1] & 0.84 [2] \\  & PU & 1.9 & 4.3 & 0.83 [1] & 0.67 [2] \\ \hline \multirow{3}{*}{Individual speed} & AD & 3.3 & 1.8 & 0.94 [1] & 0.87 [2] \\  & AS & 2.5 & 2.4 & 0.89 [1] & 0.79 [2] \\  & PU & 1.3 & 4.0 & 0.85 [1] & 0.72 [2] \\ \hline \end{tabular} \({}^{1}\) [PERSON]’s correlation coefficient: \(p\) < 0.001; \({}^{2}\) Regression analyses: \(p\) < 0.001.  
\end{table}