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The aim of this study was to assess the ability of multiscale sample entropy (MSE), refined composite multiscale entropy (RCMSE), and complexity index (CI) to characterize gait complexity through trunk acceleration patterns in subjects with Parkinson’s disease (swPD) and healthy subjects, regardless of age or gait speed. The trunk acceleration patterns of 51 swPD and 50 healthy subjects (HS) were acquired using a lumbar-mounted magneto-inertial measurement unit during their walking. MSE, RCMSE, and CI were calculated on 2000 data points, using scale factors (τ) 1–6. Differences between swPD and HS were calculated at each τ, and the area under the receiver operating characteristics, optimal cutoff points, post-test probabilities, and diagnostic odds ratios were calculated. MSE, RCMSE, and CIs showed to differentiate swPD from HS. MSE in the anteroposterior direction at τ4 and τ5, and MSE in the ML direction at τ4 showed to characterize the gait disorders of swPD with the best trade-off between positive and negative posttest probabilities and correlated with the motor disability, pelvic kinematics, and stance phase. Using a time series of 2000 data points, a scale factor of 4 or 5 in the MSE procedure can yield the best trade-off in terms of post-test probabilities when compared to other scale factors for detecting gait variability and complexity in swPD.

The Harmonic Ratio (HR) is an index based on the spectral analysis of lower trunk accelerations that is commonly used to assess the quality of gait. However, it presents several issues concerning reliability and interpretability. As a consequence, the literature provides very different values albeit corresponding to the same populations. In the present work, an improved harmonic ratio (iHR) was defined, relating the power of the intrinsic harmonics (i.e. associated with the symmetric component of gait) to the total power of the signal for each stride, leading to a normalised index ranging from 0 to 100%. The effect of the considered number of harmonics and strides on the estimate of both HR and iHR was assessed. The gait of three groups of volunteers was investigated: young healthy adults, elderly women and male trans-femoral amputees. Both HR and iHR were able to discriminate gait deviations from the gait of young healthy adults. Moreover, iHR proved to be more robust with respect to the number of considered harmonics and strides, and to exhibit a lower inter-stride variability. Additionally, using a normalised index as iHR led to a more straightforward interpretation and improved comparability. The importance of standardised conditions for the index evaluation was unveiled, and, in order to enhance the future comparability of the index, the following guidelines were presented: considering at least 20 harmonics and 20 strides; expressing the acceleration components in a repeatable, anatomical, local system of reference; and evaluating the iHR index, rather than the traditional HR.

Nowadays, gait assessment in the real life environment is gaining more attention. Therefore, it is desirable to know how some factors, such as surfaces (natural, artificial) or dual-tasking, influence real life gait pattern. The aim of this study was to assess gait variability and gait complexity during single and dual-task walking on different surfaces in an outdoor environment. Twenty-nine healthy young adults aged 23.31 ± 2.26 years (18 females, 11 males) walked at their preferred walking speed on three different surfaces (asphalt, cobbles, grass) in single-task and in two dual-task conditions (manual task—carrying a cup filled with water, cognitive task—subtracting the number 7). A triaxial inertial sensor attached to the lower trunk was used to record trunk acceleration during gait. From 15 strides, sample entropy (SampEn) as an indicator of gait complexity and root mean square (RMS) as an indicator of gait variability were computed. The findings demonstrate that in an outdoor environment, the surfaces significantly impacted only gait variability, not complexity, and that the tasks affected both gait variability and complexity in young healthy adults.

People with stroke (PwS) face increased fall risk on uneven surfaces; however, gait stability under such conditions remains unexplored. This study used machine learning (ML) to identify acceleration features distinguishing PwS from healthy controls (HC) during uneven-surface walking and to predict them from even-surface gait parameters. Trunk acceleration data from 71 PwS and 39 HC were analyzed using classification and regression models. The ML classifiers achieved an accuracy of over 95%. The key discriminative features included the vertical root mean square (RMS_VT), anterior-posterior sample entropy (SampEn_AP), and harmonic ratio (HR_AP). In PwS, even-surface gait speed < 0.8 m/s predicted reduced speed and higher RMS_VT on uneven surfaces. SampEn_AP and HR_AP were influenced by ankle kinematics and their even-surface values, respectively, showing nonlinear associations. These findings support the use of wearable sensor data and interpretable ML to assess gait stability and adaptability, facilitating development of digital biomarkers for personalized stroke rehabilitation aimed at improving outdoor mobility.

Background: The subjective evaluation of pathological gait exhibits a low inter-rater reliability. Therefore, we developed a three-dimensional acceleration of the trunk during walking to assess the pathological gait quantitatively. Methods: We evaluated 97 patients who underwent the cerebrospinal tap test and were diagnosed with idiopathic normal pressure hydrocephalus (iNPH) and 68 healthy elderlies. The gait features of all patients were evaluated and classified as one of the following: freezing of gait, wide-based gait, short-stepped gait, shuffling gait, instability, gait festination, difficulty in changing direction, and balance disorder in standing up. All gait features of 68 healthy elderlies were treated as normal. Trunk acceleration was recorded automatically by a smartphone placed on the umbilicus during a 15-foot walking test. Two novel indices were created. The first index was a trunk acceleration index, which was defined as (forward acceleration fluctuation) + (vertical acceleration fluctuation) – (lateral acceleration fluctuation) based on the multivariate logistics regression model, and the second index was created by multiplying the forward acceleration with the vertical acceleration. Additionally, 95% confidence ellipsoid volume of the three-dimensional accelerations was assessed. Results: Forward and vertical acceleration fluctuations were significantly associated with the probability of an iNPH-specific pathological gait. The trunk acceleration index demonstrated the strongest association with the probability of an iNPH-specific pathological gait. The areas under the receiver-operating characteristic curves for detecting 100% probability of an iNPH-specific pathological gait were 86.9% for forward acceleration fluctuation, 88.0% for vertical acceleration fluctuation, 82.8% for lateral acceleration fluctuation, 89.0% for trunk acceleration index, 88.8% for forward × vertical acceleration fluctuation, and 87.8% for 95% confidence ellipsoid volume of the three-dimensional accelerations. Conclusions: The probability of a pathological gait specific to iNPH is high at the trunk acceleration fluctuation, reduced in the forward and vertical directions, and increased in the lateral direction.

Background Root mean square (RMS) of trunk acceleration is seen frequently in gait analysis research. However, many studies have reported that the RMS value was related to walking speed. Therefore, the relationship between the RMS value and walking speed should be considered when the RMS value is used to assess gait abnormality. We hypothesized that the RMS values in three sensing axes exhibit common proportions for healthy people if they walk at their own preferred speed and that the RMS proportions in abnormal gait deviate from the common proportions. In this study, we proposed the RMS ratio (RMSR) as a gait abnormality measure and verified its ability to discriminate abnormal gait. Methods Forty-seven healthy male subjects (24–49 years) were recruited to examine the relationship between walking speed and the RMSR. To verify its ability to discriminate abnormal gait, twenty age-matched male hemiplegic patients (30–48 years) participated as typical subjects with gait abnormality. A tri-axial accelerometer was attached to their lower back, and they walked along a corridor at their own preferred speed. We defined the RMSR as the ratio between RMS in each direction and the RMS vector magnitude. Results In the healthy subjects, the RMS in all directions related to preferred walking speed. In contrast, RMSR in the mediolateral (ML) direction did not correlate with preferred walking speed ( rs = -0.10 , p = 0.54 ) and represented the similar value among the healthy subjects. Moreover, the RMSR in the ML direction for the hemiplegic patients was significantly higher than that for the healthy subjects ( p < 0.01 ). Conclusions These results suggest that the RMSR in the ML direction exhibits a common value when healthy subjects walk at their own preferred speed, even if their preferred walking speed were different. For subjects with gait abnormality, the RMSR in the ML direction deviates from the common value of healthy subjects. The RMSR in the ML direction may potentially be a quantitative measure of gait abnormality.

The aim of this study was to determine the test-retest reliability of an automated infrared-assisted, trunk accelerometer-based gait analysis system for measuring gait parameters of healthy subjects in a hospital. Thirty-five participants (28 of them females; age range, 23–79 years) performed a 5-m walk twice using an accelerometer-based gait analysis system with infrared assist. Measurements of spatiotemporal gait parameters (walking speed, step length, and cadence) and trunk control (gait symmetry, gait regularity, acceleration root mean square (RMS), and acceleration root mean square ratio (RMSR)) were recorded in two separate walking tests conducted 1 week apart. Relative and absolute test-retest reliability was determined by calculating the intra-class correlation coefficient (ICC3,1) and smallest detectable difference (SDD), respectively. The test-retest reliability was excellent for walking speed (ICC = 0.87, 95% confidence interval = 0.74–0.93, SDD = 13.4%), step length (ICC = 0.81, 95% confidence interval = 0.63–0.91, SDD = 12.2%), cadence (ICC = 0.81, 95% confidence interval = 0.63–0.91, SDD = 10.8%), and trunk control (step and stride regularity in anterior-posterior direction, acceleration RMS and acceleration RMSR in medial-lateral direction, and acceleration RMS and stride regularity in vertical direction). An automated infrared-assisted, trunk accelerometer-based gait analysis system is a reliable tool for measuring gait parameters in the hospital environment.

Measurements using an accelerometer reflect the impact applied to the trunk. Measurement of trunk acceleration has the possibility of reflecting the typical characteristics of trunk motion during cutting. However, analysis of trunk acceleration data during cutting manoeuvres has not been previously conducted. This study aimed to analyse trunk acceleration during cutting manoeuvres to examine any gender differences or a relationship with posture. All participants (eight male and eight female college soccer athletes) performed a shuttle run cutting task, and trunk accelerations (medio-lateral, vertical, and antero-posterior) were calculated. The peak acceleration (G) and total magnitude during the 200 ms after foot contact were measured, and the forward trunk inclination and femoral angle were calculated from the video images taken using a sagittal plane camera. Peak vertical acceleration (mean, s) was significantly greater among female athletes than among male athletes (−2.18, s = 0.84 G; −1.15, s = 0.45 G, respectively; p < 0.01). Medio-lateral and antero-posterior peak acceleration and the total magnitude in all directions were not significantly different between genders. Moderate negative correlations were found between vertical peak acceleration and trunk forward inclination and femoral inclination (r = −0.57, p < 0.05; r = −0.69, p < 0.01, respectively). The difference in vertical acceleration between genders has the possibility to reflect a stiff cutting movement among female athletes. The acceleration of the upper trunk may be an index for evaluating cutting movements.

Duathlon consists of two durations of running separated by cycling in a format similar to triathlon. The addition of cycling and the associated loadings on the neuromuscular system can modify spatiotemporal variables in running including trunk motion, which can impact running economy. Changes to trunk motion can be inferred by measuring accelerations of the centre of mass (CoM). However, there is scarce research into trunk dynamics in duathlon. Therefore, the aim of this study was to use an inertial sensor (an accelerometer) to compare acceleration magnitudes of the trunk in the vertical, mediolateral, and anteroposterior directions during a simulated field-based duathlon. Specifically, running performance and magnitudes of trunk acceleration were compared pre and post a cycling load. Ten well-trained duathletes (seven males, three females (mean ± SD; age: 31.1 ± 3.4 years; body mass: 70.9 ± 6.9 kg; body height: 177 ± 5.82 cm; 9.45 ± 1.7 weekly training hours per week; 9.15 ± 5.2 years training experience)) completed a 5 km run performed at a self-selected pace (described as moderate intensity) prior to 20 km of continuous cycling at four varied cadence conditions. This was immediately followed by a 2.5 km run. Mean completion times for the final 2.5 km in running pre-cycling (4.03:05 ± 0.018) compared to the 2.5 km in running post-cycling (4.08:16 ± 0.024) were significantly different. Regarding trunk acceleration, the largest difference was seen in the vertical direction (y axis) as greater magnitudes of acceleration occurred during the initial 1 km of running post-cycling combined with overall significant alterations in acceleration between running pre- and post-cycling (p = 0.0093). The influence of prior cycling on trunk acceleration activity in running likely indicates that greater vertical and mediolateral trunk motion contributes to decremental running performance. In future, further advanced simulation and analysis could be performed in ecologically valid contexts whereby multiple accelerometers might be used to model a more complete set of dynamics.

Obstacles often appear unexpectedly in our pathway and these require us to make adjustments to avoid collision. Previous research has demonstrated that healthy adults will make anticipatory adjustments to gait where they have been told there is the possibility of an obstacle appearing. One population that may find this type of anticipatory movement difficult is individuals with Developmental Coordination Disorder (DCD). The current study considered how individuals with and without DCD adjust to the possibility of an obstacle appearing which would require circumvention. Fortyfour individuals with DCD and 44 age-matched controls (aged from 7 to 34 years of age) walked down an 11 m walkway under three conditions. Initially they were told this was a clear pathway and nothing in the environment would change (1, no possibility of an obstacle, no obstacle). They then performed a series of trials in which a gate may (2, possibility of an obstacle, obstacle) or may not (3, possibility of an obstacle, no obstacle) partially obstruct their pathway. We found that all participants increased medio-lateral trunk acceleration when there was the possibility of an obstacle but before the obstacle appeared, in addition the typical adults and older children also increased step width. When describing circumvention we found that the younger children showed an increase in trunk velocity and acceleration in all three directions compared to older children and adults. We also found that the individuals with DCD adjusted their path sooner and deviated more than their peers. The degree of adjustment to step width in anticipation of an obstacle was related to later medio-lateral velocity and timing of the deviation. Therefore, the lack of ‘readying’ the system where there is the possibility of an obstacle appearing seen in the individuals with DCD and the younger typical children may explain the increased medio-lateral velocity seen during circumvention.