Research on kinematic parameters of multiple gait pattern transitions

Gait recognition technology is the key technology in the field of exoskeletons. In the current research of gait recognition technology, there is less focus on the recognition of the transition between gait patterns. This study aims to determine which kinematic parameters have significant differences in the transitions (between level and stair walking and between level and ramp walking) of different gait patterns, to determine whether these parameters change differently in different gait pattern transitions, and the order the significant differences occur through a comparative analysis of various kinematic parameters between the transition stride and the before stride in the former pattern. We analyzed 18 parameters concerning both lower limbs and trunk. We compared each time point of the transition strides to the corresponding time points of the before stride using a series of two-sample t-tests, and we then evaluated the difference between the transition stride and the before stride based upon the number of time points within the gait cycle that were statistically different. We found that the sagittal plane angular velocity and the angular acceleration of all joints and the resultant velocity of the thigh and shank of the leading limb had significant differences in the process of transition; the sagittal plane angular velocity of all joints of the trailing limb and the velocity of the trunk in the coronary axis direction also showed a significant difference. The angular acceleration of all joints, the sagittal plane angular velocity of the ankle joint of the leading limb, and the acceleration of the trunk in the coronal axis direction showed a difference in the early stage of the transition. In general, the leading limb had a significant difference earlier than the trailing limb, and the acceleration parameters changed earlier than the velocity parameters. These parameters showed different combinations of changes in the transition of different gait patterns, and the changes in these parameters reflected different gait pattern transitions. Therefore, we believe that the results of this study can provide a reference for the gait pattern transition recognition of wearable exoskeletons.