Gait disorders are common in neurological diseases and significantly impact patients’ quality of life. While quantitative gait analysis is essential for diagnosis and rehabilitation, existing commercial systems are costly and complex, limiting their clinical application. This study developed a low-cost digital gait analysis system, "Dual Kinect-V2 System (DKS)," integrating dual Kinect-V2 sensors and open-source software to improve accessibility and feasibility in clinical and domestic settings. The system was validated against a commercial insole-based gait analysis system, Right Gait & Posture (RGP) system, in a study involving 18 healthy adults and 15 patients with neurological gait disorders. Spatial-temporal gait parameters were analyzed using Pearson’s correlation coefficient and concordance correlation coefficient to assess consistency. Results demonstrated good to excellent agreement for most spatial-temporal gait parameters, particularly in healthy participants. However, temporal parameters such as double-support, swing, and stance phases exhibited moderate agreement, with greater discrepancies observed in patients. Despite these limitations, the system provides a cost-effective, portable, and relatively accurate tool for clinical gait assessment. With further optimization, including improved motion tracking algorithms and potential sensor upgrades, the system could be a valuable tool for neurological diagnosis, rehabilitation monitoring, and fall prevention in elderly populations.