## 4 Discussion  
Gait quality has been shown to closely correlate with overall health status in neurotypical individuals [27]. In individuals with neurodevelopmental disorders, gait quality is associated with the severity of their condition, suggesting that comprehensive gait assessment may possibly offer valuable insights into their overall health status [14; 28]. Much of the existing literature describing the motoric characteristics of individuals with SRD have come from observational surveys, primarily focused on fundamental motor skills and fine motor skills related to activities of daily living. More formal surveys have included the use of the Alberta Infant Motor Scale, various subtests of the Bayley Scale of Infant and Toddler Development, and the Gross Motor Function Measure (GMFM). Gait quality is increasingly being considered as a possible non-invasive biomarker [29]. Therefore, it is important that gait metrics of individuals with SRD are accurately measured quantitatively and objectively using state-of-the art motion analysis technologies and analyzed with a variety of techniques. To explore the possibility that gait could serve as a biomarker, more laboratory-based studies with significant numbers of participants need to be conducted. However, as mentioned previously, the only laboratory-based evaluation of gait with SRD participants was conducted by [15], and this study had limited generalizability as only one individual with SRD participated. Expansion of the number of SRD gait studies as well as increased numbers of participants are needed before meaningful examination of potential relationships between clinically accepted motor scales and gait measures can be conducted. The current report characterizes the gait of eight participants with SRD and compares the outcomes to those of age-matched controls, thereby representing a significant increase in the number of participants compared to the previous report from our group. As there are no differences in stride times between the two groups (Table 2), potential changes in the additional gait measures can be interpreted as results from differences in coordination or control, and not temporal features of the stride. The SDs for the two groups also indicate that stride time variability is very similar for the two groups. As the SRD and NT groups are composed of age-matched participants, the stride time data suggests that \begin{table}
\begin{tabular}{l l l l l} \hline
**CVs** & & **Hip** & **Knee** & **Ankle** \\ \hline \multirow{2}{*}{ROM} & SRD & 23.8 & 22.3 & 57.4 \\ \cline{2-5}  & NT & 11.9 & 9.0 & 19.3 \\ \hline \multirow{4}{*}{\begin{tabular}{l} Peak \\ Velocity \\ \end{tabular} } & \% Delta & 100 & 148 & 197 \\ \cline{2-5}  & SRD & 16.1 & 14.1 & 45.4 \\ \hline \multirow{4}{*}{\begin{tabular}{l} Peak \\ Velocity \\ \end{tabular} } & NT & 10.9 & 5.6 & 24.8 \\ \hline \multirow{4}{*}{\begin{tabular}{l} A-A Area \\ \end{tabular} } & \% Delta & 48 & 152 & 83 \\ \cline{2-5}  & \multicolumn{3}{c}{} & Hip vs. Knee & Knee vs. Ankle \\ \cline{2-5}  & SRD & 38.2 & 51.1 \\ \cline{2-5}  & NT & 18.7 & 20.0 \\ \hline \multirow{4}{*}{\
\begin{tabular}{l} P-P Area \\ \end{tabular} } & \% Delta & 104 & 156 \\ \cline{2-5}  & \multicolumn{3}{c}{} & Hip & Knee & Ankle \\ \cline{2-5}  & SRD & 65.5 & 70.3 & 174.3 \\ \cline{2-5}  & NT & 40.0 & 33.2 & 51.5 \\ \hline \multirow{4}{*}{
\begin{tabular}{l} P-P Delta \\ \end{tabular} } & \% Delta & 68 & 156 & 214 \\ \hline \end{tabular}
\end{table} 
Table 8: CVs of SRD and NT groups of ROMs, peak velocities, A-A, and P-P areas. individuals with SRD are quite capable of producing gait cadence that match the slow speed of NT individuals, at least during motorized-driven treadmill walking. The rhythmical pattern of lower-limb motion is proposed to be generated by a complex of spinal neurons requiring the intervention of higher-order structures to produce functional walking [30; 31]. This spinal complex is labeled as a central pattern generator, more commonly known as a CPG.