Assessment of Gait Parameters Using XSENS Dot Sensors among Typically Developing Ghanaian Children

Results provide insightful differences in gait dynamics,  reflecting potential variations in physical activities, health policies, or school environments. A significant difference in the DFA Alpha values (U = 5331.0, p < .001, effect size = 8.606) suggests that gait signals from students at private schools exhibit more pronounced long-range correlations compared to those from public schools. Both ApEn (U = 5124.0, p < .001, effect size = 7.879) and SampEn (U = 3798.0, p = .001, effect size = 3.223) showed significant differences, indicating more complexity and unpredictability in the gait patterns among private school students. The results indicated a significant difference in the sensitivity of gait dynamics to initial conditions between students from private and public schools (U = 4691.0, p < .001, effect size = 6.358). This study seeks to address the shortage of region-specific gait data by utilizing wearable XSENS Dot sensors to assess clinical gait parameters among selected typically developing Ghanaian children. By extrapolating this data, the study aims to provide reliable, evidence-based insights to support clinical practice in Ghana. Furthermore, the cost-effectiveness and practicality of using XSENS Dot sensors in low-resource settings have the potential to revolutionize paediatric gait analysis across Africa.  This cross-sectional descriptive study involved 150 children [mean age: 3.28±0.55 years; male (69, 46.0%), female (81, 54.0%); mean weight: 15.61±2.75 kg; mean BMI: 15.91±2.09 kg/m²] from public and private nursery schools. Gait parameters were measured using Xsens DOT wearable sensors (XS-T02 – IP68 FCC ID – XPYANNAB1) connected to an iPhone. The gait signals were analysed using inertial measurement units (IMUs) to assess differences between the two groups. Metrics such as Wolf's Lyapunov Exponent (Wolf_LyE), Detrended Fluctuation Analysis (DFA Alpha), Approximate Entropy (ApEn), and Sample Entropy (SampEn) were used to explore the complexities and dynamics of walking patterns, revealing insights into how their daily activities and school environments might influence the children's gait. Wearable XSENS Dot sensors provide a cost-effective, portable solution for paediatric gait analysis in Ghana, addressing local data gaps. These insights can guide physiotherapy, education, and policy, promoting tailored interventions and equitable access to diagnostic tools. The results suggest that private school students displayed more variability and sensitivity in their gait patterns, possibly due to differences in physical activity curricula or school environments. Longitudinal studies are needed to explore how gait patterns evolve with changes in educational settings, physical activities, and growth.