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Hip osteoarthritis (OA) affects the entire joint and significantly alters gait. Assessing gait through a single trunk inertial measurement unit (IMU) in clinical settings offers a more practical alternative to complex laboratory settings, allowing for the capture of natural gait movements with valuable biomechanical insights. We evaluated (1) whether gait quality differs between individuals with hip OA and healthy controls during habitual and fast walking, (2) whether gait changes from habitual to fast walking differ between groups. Forty individuals with hip OA and 40 age-matched healthy controls underwent 25-m habitual walk and 40-m fast walk. Six gait quality parameters—step symmetry, stride symmetry, stability, smoothness, regularity, and complexity—were analyzed from the IMU signals. During habitual walking, individuals with hip OA exhibited reduced symmetry and stability and several vertical impairments. During fast walking, individuals with hip OA continued to show reduced step symmetry and a more constrained gait in the mediolateral direction. Additionally, people with hip OA also showed limited adjustments when transitioning from habitual to fast walking, in contrast to the significant adjustments observed in healthy controls. These findings indicate that gait in individuals with hip OA is impaired during habitual and fast walking, with limited adaptations across the transition between the two conditions.

The concept of the 'extrapolated center of mass (XcoM)', introduced by Hof et al., (2005, J. Biomechanics 38 (1), p. 1–8), extends the classical inverted pendulum model to dynamic situations. The vector quantity XcoM combines the center of mass position plus its velocity divided by the pendulum eigenfrequency. In this concept, the margin of stability (MoS), i.e., the minimum signed distance from the XcoM to the boundaries of the base of support was proposed as a measure of dynamic stability. Here we describe the conceptual evolution of the XcoM, discuss key considerations in the estimation of the XcoM and MoS, and provide a critical perspective on the interpretation of the MoS as a measure of instantaneous mechanical stability.

Humans regularly follow curvilinear trajectories during everyday ambulation. However, globally-defined and locally-defined reference frames fall out of alignment during turning gait, which complicates spatiotemporal and biomechanical analyses. Thus, the choice of the locally-defined reference frame is an important methodological consideration. This study investigated how different definitions of reference frame change the results and interpretations of common gait measures during turning. Nine healthy adults completed two walking trials around a circular track. Kinematic data were collected via motion capture and used to calculate step length, step width, anteroposterior margin of stability, and mediolateral margin of stability using three different locally-defined reference frames: walkway-fixed, body-fixed, and trajectory-fixed. Linear-mixed effects models compared the effect of reference frame on each gait measure, and the effect of reference frame on conclusions about a known effect of turning gait – asymmetrical stepping patterns. All four gait measures differed significantly across the three reference frames. A significant interaction of reference frame and step type (i.e. inside vs outside step) on step length (p < 0.001), anteroposterior margin of stability (p < 0.001), and mediolateral margin of stability (p < 0.001) indicated conclusions about asymmetry differed based on the choice of reference frame. The choice of reference frame will change the calculated gait measures and may alter the conclusions of studies investigating turning gait. Care should be taken when comparing studies that used different reference frames, as results cannot be easily harmonized. Future studies of turning gait need to justify and detail their choice of reference frame.

This study aimed to assess the responsiveness to the rehabilitation of three trunk acceleration-derived gait indexes, namely the harmonic ratio (HR), the short-term longest Lyapunov’s exponent (sLLE), and the step-to-step coefficient of variation (CV), in a sample of subjects with primary degenerative cerebellar ataxia (swCA), and investigate the correlations between their improvements (∆), clinical characteristics, and spatio-temporal and kinematic gait features. The trunk acceleration patterns in the antero-posterior (AP), medio-lateral (ML), and vertical (V) directions during gait of 21 swCA were recorded using a magneto-inertial measurement unit placed at the lower back before (T0) and after (T1) a period of inpatient rehabilitation. For comparison, a sample of 21 age- and gait speed-matched healthy subjects (HS matched ) was also included. At T1, sLLE in the AP (sLLE AP ) and ML (sLLE ML ) directions significantly improved with moderate to large effect sizes, as well as SARA scores, stride length, and pelvic rotation. sLLE ML and pelvic rotation also approached the HS matched values at T1, suggesting a normalization of the parameter. HRs and CV did not significantly modify after rehabilitation. ∆sLLE ML correlated with ∆ of the gait subscore of the SARA scale (SARA GAIT ) and ∆stride length and ∆sLLE AP correlated with ∆pelvic rotation and ∆SARA GAIT . The minimal clinically important differences for sLLE ML and sLLE AP were ≥ 36.16% and ≥ 28.19%, respectively, as the minimal score reflects a clinical improvement in SARA scores. When using inertial measurement units, sLLE AP and sLLE ML can be considered responsive outcome measures for assessing the effectiveness of rehabilitation on trunk stability during walking in swCA.

This study proposes a wearable gait assessment method using inertial measurement units (IMUs) to evaluate gait ability in daily environments. By focusing on the estimation of the margin of stability (MoS), a key kinematic stability parameter, a method using a convolutional neural network, was developed to estimate the MoS from IMU acceleration time-series data. The relationship between MoS and other stability indices, such as the Lyapunov exponent and the multi-site time-series (MSTS) index, using data from five IMU sensors placed on various body parts was also examined. To simulate diverse gait conditions, treadmill speed was varied, and a knee–ankle–foot orthosis was used to restrict left knee extension, inducing gait asymmetry. The model achieved over 90% accuracy in classifying MoS in both forward and lateral directions using three-axis acceleration data from the IMUs. However, the correlation between MoS and the Lyapunov exponent or MSTS index was weak, suggesting that these indices may capture different aspects of gait stability.

Detecting motor fatigue during rigorous activities is essential for preventing injuries, falls, and over-exertion. While research has focused on developing fatigue indices using motion capture or wearable sensors, the method of inducing fatigue can impact movement patterns differently. This study compared the effects of whole-body motor fatigue induced by incline treadmill walking with localized fatigue induced by leg presses and isolated ankle movements, as investigated in our prior study. Twenty healthy young participants walked at 1.25 m/s for 5 min before (PRE) and after (POST) motor fatigue. We computed POST-to-PRE ratios for walking stability and variability measures, including dynamic margins of stability (MOS), step spatiotemporal measures, kinematic variability, and local dynamic stability based on short-term local divergence exponents (LDEs) of trunk movement. Localized fatigue increased mean step width (p = 0.002), mean mediolateral MOS (p = 0.015), knee joint angle variability (p < 0.001), and the mean peak mediolateral center of mass velocity (p < 0.001) more than whole-body fatigue. Whole-body fatigue reduced short-term LDE values of anterior–posterior trunk motion (p = 0.021), indicating greater improvement in local dynamic stability. The findings indicate that localized fatigue has a greater impact on gait variability and stability than whole-body fatigue. The methods of inducing motor fatigue led to different changes in gait.

Unpredictable gait disturbances, particularly in the mediolateral direction, pose a significant challenge to stability and are a common contributor to falls. Although the corticospinal tract is critical for gait and postural control, its response to such instabilities remains unclear. To investigate if corticospinal excitability increases during laterally destabilised gait, single‐pulse transcranial magnetic stimulations were delivered over the primary motor cortex of 15 healthy individuals during steady‐state and laterally destabilised treadmill gait. Full‐body kinematics were recorded using an optoelectronic motion capture system. Stimulations with coil displacement >5 mm from the targeted location were excluded. Corticospinal excitability was quantified for four upper‐ and three lower‐leg muscles by the motor evoked potential (MEP) amplitude and compared between steady‐state and destabilised gait. Destabilisation resulted in a wider step width and shorter stride duration with increased variability and greater dynamic instability. Foot placement control was increased at mid‐swing, along with greater average foot placement error. No differences in corticospinal excitability were observed in the lower‐leg muscles. All upper‐leg muscles demonstrated greater absolute MEPs in destabilised relative to steady‐state gait. After normalising MEP to the pre‐stimulus muscle activity, these periods became less pronounced; however, increases were observed in all but the gastrocnemius muscles. These findings suggest heightened readiness of the corticospinal tract projecting to upper‐leg muscles during destabilised gait, which could reflect general stabilising strategies such as decreasing stride time and increasing step width. What is the central question of this study? Does corticospinal excitability in upper‐ and lower‐leg muscles change in response to mediolateral gait instability? What is the main finding and its importance? Absolute motor evoked potentials of all upper‐leg muscles increased during destabilised gait. After normalising to pre‐stimulus muscle activity, these increases were smaller but remained in all muscles except the gastrocnemius. This suggests heightened readiness of the corticospinal tract projecting to upper‐leg muscles, which may reflect general stabilising strategies such as decreasing stride time and increasing step width.

The capacity to maintain upright balance by minimising upper body oscillations during walking, also referred to as gait stability, has been associated with a decreased risk of fall. Although it is well known that fall is a common complication after stroke, no study considered the role of both trunk and head when assessing gait stability in this population. The primary aim of this study was to propose a multi-sensor protocol to quantify gait stability in patients with subacute stroke using gait quality indices derived from pelvis, sternum, and head accelerations. Second, the association of these indices with the level of walking ability, with traditional clinical scale scores, and with fall events occurring within the six months after patients’ dismissal was investigated. The accelerations corresponding to the three abovementioned body levels were measured using inertial sensors during a 10-Meter Walk Test performed by 45 inpatients and 25 control healthy subjects. A set of indices related to gait stability were estimated and clinical performance scales were administered to each patient. The amplitude of the accelerations, the way it is attenuated/amplified from lower to upper body levels, and the gait symmetry provide valuable information about subject-specific motor strategies, discriminate between different levels of walking ability, and correlate with clinical scales. In conclusion, the proposed multi-sensor protocol could represent a useful tool to quantify gait stability, support clinicians in the identification of patients potentially exposed to a high risk of falling, and assess the effectiveness of rehabilitation protocols in the clinical routine.

Multiple sclerosis (MS) research requires new, more sensitive, behavioral biomarkers that map to subtle central nervous system injury. Although gait speed, as measured using the Timed 25 Foot Walk Test, is used clinically to track MS progression, it is less useful in people with MS who do not have overt gait impairment. This study aimed to identify specific spatiotemporal gait parameters that predict corticospinal tract (CST) function in individuals with MS. We recruited consecutive patients attending a neurology clinic and evaluated CST excitatory and inhibitory function using single pulse transcranial magnetic stimulation of the primary motor cortex representation of the first dorsal interosseous muscle. We generated excitatory and inhibitory recruitment curves by calculating the area under the curve for motor-evoked potential amplitudes and cortical silent period durations, respectively, across stimulation intensities from 105 to 155% of active motor threshold in 10% increments. Spatiotemporal gait parameters were assessed using an electronic walkway. We built predictive models with gait parameters as the predictors and CST function as the outcome. We evaluated 78 individuals with MS (58 females). Longer distance of the center of pressure movement during single support was the strongest predictor of higher excitability (lower active motor threshold; accounting for 25.8% of variance, R² = 0.258), while less time in double support accounted for a smaller portion of variability in excitatory recruitment curve (13.3% variance explained, R² = 0.133). For inhibitory CST function, slower stride time (30.5% variance explained, R² = 0.305) and wider stride (6.3% variance explained, R² = 0.063) predicted greater inhibition. Notably, in all models, measures of gait stability, not gait speed, predicted CST function. Our results suggest that even among people with MS who have normal gait speed and can easily cross an urban intersection, subtle postural control impairments exist which may not be apparent to them or to their clinician.

Unstable gait increases the risk of falls, posing a significant danger, particularly for frail older adults. The margin of stability (MoS) is a quantitative index that reflects the risk of falling due to postural imbalance in both the anterior-posterior and mediolateral directions during walking. Although MoS is a reliable indicator, its computation typically requires specialized equipment, such as motion capture systems, limiting its application to laboratory settings. To address this limitation, we propose a method for estimating MoS using time-series data from the translational and angular velocities of a single body segment—the pelvis. By applying principal motion analysis to process the multivariate time-series data, we successfully estimated MoS. Our results demonstrate that the estimated MoS in the mediolateral direction achieved an RMSE of 0.88 cm and a correlation coefficient of 0.72 with measured values, while in the anterior-posterior direction, the RMSE was 0.73 cm with a correlation coefficient of 0.87. These values for the mediolateral direction are better than those obtained in previous studies using only the three translational velocity components of the pelvis, whereas the values for the anterior direction are comparable to previous approaches. Our findings suggest that MoS can be reliably estimated using six-axial kinematic data of the pelvis, offering a more accessible method for assessing gait stability.