Kinetic and Kinematic Analysis of Gait Termination: A Comparison between Planned and Unplanned Conditions

Abstract

Purpose: Gait termination (GT) is the transition from steady-state walking to a complete stop, occurring under planned gait termination (PGT) or unplanned gait termination (UGT) conditions. This study aimed to investigate the biomechanical differences between PGT and UGT, which could help develop therapeutic interventions for individuals experiencing difficulty with GT. Methods: Twenty healthy adults performed three walking trials, followed by PGT and UGT trials. Gait termination was analyzed in three phases as follows: Phase 1 (pre-stopping), Phase 2 (initial stopping phase), and Phase 3 (terminal stopping phase). Spatiotemporal, kinematic, and kinetic data during each phase were compared between conditions. Results: The GT time and GT step length were significantly different between the PGT and UGT trials. Ankle range of motion (ROM) demonstrated significant differences in Phase 1, with the PGT having a slightly lower ankle ROM than the UGT. In Phase 2, the hip, knee, and ankle ROM exhibited significant differences between the conditions. Finally, in Phase 3, UGT showed reduced hip ROM but increased knee ROM and kinetic parameters compared to PGT. Conclusion: Our results indicate that the ankle joint primarily contributes to deceleration during the initial preparation for generating braking force during PGT. Conversely, UGT reveals disrupted kinesthetic control due to instability, leading to a preference for a hip and knee strategy to absorb force and control the center of mass for a safe and rapid GT in response to unexpected stimuli. These findings provide valuable insights into the biomechanical mechanisms underlying body stability during GT and may contribute to the development of effective rehabilitation strategies for individuals with gait impairment.

Robot-Aided Motion Analysis in Neurorehabilitation: Benefits and Challenges

“…Nowadays, motion analysis can be performed using marker-less systems that use sophisticated human body models, computer vision, and machine learning algorithms [17]. Biomechanical parameters that are considered during motion analysis include kinematic and kinetic parameters [18,19]. In particular, kinematic parameters [20] include the spatial and temporal aspects of movement.…”