###### Abstract  
This study aimed to investigate how --external perturbations caused by a treadmill belt's acceleration (Acc) and deceleration (Dec) during the Initial-Contact (Initial), Mid-Stance (Mid), and Pre-Swing (ToeOff) phases affect gait regularity in young adults. **Methods:** Twenty-one healthy young females walked on a treadmill in a virtual environment (Motek GRAIL), in which four unexpected perturbations were applied to the left belt at the Initial, Mid, and ToeOff stages. Sample entropy (SampEn) was calculated for the center of mass (CoM) displacements for six perturbation scenarios in three directions--anterior-posterior (AP), medial-lateral (ML), and vertical (vert)--with SampEn vector lengths (\(m\)) ranging from 2 to 10. **Results:** The CoM displacement exhibited is highest regularity (low SampEn values) in the AP and vert directions during Dec-ToeOff, across all \(m\) values. Similarly, this pattern was observed in the ML direction, but exclusively for \(m=2\) and 4. The least-regular CoM trajectories (high SampEn values) were for Dec-Mid in the AP direction, across all \(m\) values. This trend persisted in the ML direction only for \(m=2\) and 4. However, the most irregular CoM displacements in the ML direction occurred during Dec-ToeOff for the remaining \(m\) values. Vertical CoM displacements exhibited the highest irregularities during Dec-Initial for \(m\geq 4\). **Conclusions:** Evaluating the regularity of CoM displacements using SampEn can be a useful tool for assessing how gait perturbations are handled. Keywords: gait; perturbations; treadmill; provoked trips; provoked slips; entropy +
Footnote †: journal: Medical  
which involves using specialized equipment such as force plates, motion capture systems, or wearable sensors. These tools provide detailed information on gait parameters, which are then analyzed to assess gait stability. Clinical and quantitative gait-analysis methods offer distinct yet complementary perspectives when assessing gait stability. Clinical methods provide valuable insights into overall performance and are easily applicable in clinical settings. Quantitative methods (instrumented gait analysis) provide detailed data on joint angles, forces exerted, timing, and spatial parameters during walking. This quantitative approach offers a more comprehensive and in-depth understanding of gait mechanics and can detect subtle abnormalities that might not be evident through clinical observation alone. Integrating findings from both clinical and quantitative analyses allows for a more holistic evaluation and understanding of an individual's gait stability. The synergy between clinical and quantitative gait analysis methods enriches the assessment of gait stability by providing a multi-dimensional perspective that combines functional observations with detailed biomechanical insights. The above-mentioned methods are commonly employed to evaluate gait stability, providing fundamental data regarding an individual's behavior. However, it is essential to note that their analysis extends beyond basic measurements. Specifically, the manner in which these data are studied opens up an entirely different perspective, allowing for a comprehensive examination of how individuals respond to perturbations and maintain stability. According to Hamacher et al. [10], both linear and nonlinear measures can be used to assess gait stability. Among the linear methods used to assess gait stability, the authors listed the following: step-and-stride length variability, step-and-stride time variability, double support time, gait speed, cadence, and the standard deviation of the analyzed time series. However, in recent years, a method associated with the margin-of-stability (MoS) determination has gained popularity [11]. Among the nonlinear measures, Hamacher et al. [10] listed wavelets and detrended fluctuation analysis, the fractal scaling index, Lyapunov exponents, and Floquet multipliers. Similar methods were mentioned in the review by Bruijn et al. [6].