Traditional gait analysis devices, such as force plates or Instrumented Treadmills (I-TM), often require laboratory settings and can be costly and restrictive, containing their applicability outside controlled environments. To overcome these limitations, we developed the Instrumented Socks Wireless Data Acquisition Module (IS-WDAQ). The accuracy of our developed IS-WDAQ was examined by calculating important temporal parameters (TPs) like step time, stance time, cadence, stance percentage, and swing percentage and compared with I-TM equipment. Participants (n = 250) were divided into groups depending on their age and Body Mass Index (BMI). Categorizing groups by BMI helps to evaluate both systems and ensures accurate, consistent measurements across body types. The Mean Bias Error (MBE) analysis was performed for the two different systems based on their generated TPs. Cadence had the lowest MBE (less than 2 %) among the three conditions tested:​ Normal (Group N), Overweight (Group OV), and Obese (Group OB). MBE was highest in step time (−5.32 to 7.29 %) and stride time (−9.35 to 4.55 %). For the three BMI groups, stance and swing percentage inaccuracies ranged from −0.78 to 5.18 %. The Intraclass Correlation Coefficient (ICC) showed a very strong cadence association (>0.9) for the three BMI categories across five age groups, while stance and swing percentages were also strongly correlated. The Bland-Altman plot spreads are also within acceptable limits. The study findings imply that the IS-WDAQ is a viable alternative to I-TM for calculating numerous TPs, including cadence, step time, stride time, stance, and swing percentages, especially for use outside laboratory settings.