Welwalk WW-1000 is a gait exercise robotic assist system that allows subjects to walk on treadmill by attaching a knee-ankle-foot robot to a paralyzed limb. Abnormal gait patterns during exercise using Welwalk WW-1000 are evaluated by gait observation or marker-based motion analysis systems. However, gait observation is a subjective and ordinal measure, and marker-based motion analysis systems are challenging to implement due to the complexity of preparing equipment and attaching markers to subjects. In this study, we propose the Welwalk WW-2000 system, which incorporated a marker-less motion analysis system that detects abnormal gait patterns during exercise using the robotic system. Using this system, it is expected that a gait exercise program can be planned from easily obtainable, objective information. This system detects the features of abnormal gait patterns using the body position coordinates of the subject obtained from three-dimensional, inertial, knee angle, and load sensors. The purpose of this study was to validate the marker-less motion analysis system against marker-based motion analysis systems. One healthy male simulated the seven abnormal gait patterns which occur frequently in stroke patients, with four grades of severity. Spearman's rank correlation coefficients were calculated for the relationship between the abnormal gait pattern parameters calculated by each motion analysis system. The correlations between the two systems ranged from 0.81 to 0.95. Therefore, it was confirmed that the marker-less motion analysis system of the Welwalk WW-2000 was valid.