# Establishing Reference Data for Electromyographic Activity in Gait: Age and Gender Variations
## 5 Limitations and Future Studies  
In this study, we focused on the effects of age and gender on EMG patterns, as these were identified as key variables by expert consensus in our previous Delphi survey [6]. While factors such as height, leg length, weight, BMI, and gait speed may also influence EMG data, our primary aim was to establish an initial reference framework based on the most clinically relevant and widely recognized parameters. Furthermore, in many clinical settings, EMG patterns are not routinely adjusted for these factors, nor are they always categorized by age or gender. Thus, our findings provide a practical and meaningful step toward standardizing EMG interpretation in clinical practice. Future studies should expand upon this work by incorporating additional variables to enhance the comprehensiveness of EMG reference data. In addition, the SPM analysis inherently accounts for variability across the gait cycle, incorporating all EMG patterns within confidence intervals. Future studies could also explore within-subject variability across gait cycles to assess whether individual fluctuations fit within the established reference range. Moreover, EMG signals were normalized in this study using the mean signal, following SENIAM guidelines [20]. This method allows for the general comparison of muscle activation patterns across participants without requiring maximum-effort tasks. While alternative normalization methods, such as maximum isometric voluntary contraction (MVIC) or peak dynamic activation, could provide insights into muscle capacities during specific movements, they were not used in this study. However, it is important to acknowledge that mean signal normalization may be influenced by inter-group differences in baseline muscle activity, particularly when comparing younger and older individuals with different muscle strengths. Future studies may benefit from exploring complementary normalization techniques to enhance the comparability of EMG signals across age groups. Furthermore, this study focused on EMG envelope patterns across the gait cycle rather than raw signal characteristics or muscle activation onset detection. Detailed firing sequences and the influence of factors such as age or gender were not investigated, as they were beyond the scope of the current analysis. A potential limitation of this study is the exclusion of the adolescent age group due to a small sample size. While this decision ensures statistical robustness in our comparisons, it also creates a gap in understanding the developmental transition between childhood and adulthood. Adolescence is a critical period for neuromuscular development, and individuals within this age range (13-18 years) may exhibit distinct EMG activation patterns. Younger adolescents may demonstrate patterns more similar to children, while older adolescents may align more closely with adults. Future studies including a larger adolescent sample could provide valuable insights into these transitional changes. Additionally, the influence of gait speed on EMG patterns was not analyzed. [PERSON] et al. [36] demonstrated that average EMG profiles consist of both speed-dependent and speed-independent components, suggesting that normalizing EMG patterns to gait speed could help mitigate confounding effects. In this study, participants walked at their self-selected speed without constraints, as the primary objective was to establish clinical EMG reference data while focusing on age- and gender-related differences. While we did not perform a statistical comparison of gait speed between age groups, we acknowledge that differences in self-selected speed could have influenced EMG patterns. Future studies should consider incorporating statistical adjustments, such as ANCOVA, to better account for the interaction effects of gait speed with age and gender. Furthermore, the focus of our study was on electromyographic activity in the sagittal plane due to its relevance to gait analysis and the primary motor functions in this plane.