Consecutive Strides Research Articles

Predictors of Gait Variability in Older Inpatients: An Exploratory Study Among Orthopedic Patients.

Aim Older inpatients have reduced physical function and walking ability with a higher risk of falls after being discharged home. Gait variability can assess ambulation and is strongly related to the risk of falls. However, the clinical factors affecting gait variability in inpatients have not been identified. The purpose of this study was to investigate the predictive factors affecting gait variability in older inpatients. Methods A total of 42 older orthopedic inpatients with fractures of the hip, spine, and other segments and 18 healthy volunteers as the control group were enrolled in this study. Inpatients wore tri-axial accelerometers for a 10m walk before discharge. Gait variability was assessed by the coefficient of variation (CV) based on five consecutive stride times. Clinical assessment of muscle strength, joint mobility, balance, pain, and activities of daily living were also evaluated. Results The CV in inpatients was higher than that in healthy elderly. Quadriceps muscle strength, ankle dorsiflexion range of motion, and balance described the CV. When model 2 (adjusted R2 = 0.473) was compared with model 1 (adjusted R2 = 0.293), the quadriceps muscle strength and ankle dorsiflexion range of motion had a major effect on CV, while balance had not a greater influence than these two factors when compared with model 3 (adjusted R2 = 0.537). Conclusions Poor knee extension strength, balance, and restriction of ankle dorsiflexion mobility have influenced gait variability in older inpatients.

Modeling Neuromotor Adaptation to Pulsed Torque Assistance During Walking.

Multiple mechanisms of motor learning contribute to the response of individuals to robot-aided gait training, including error-based learning and use-dependent learning. Previous models described either of these mechanisms, but not both, and their relevance to gait training is unknown. In this paper, we establish the validity of existing models to describe the response of healthy individuals to robot-aided training of propulsion via a robotic exoskeleton, and propose a new model that accounts for both use-dependent and error-based learning. We formulated five state-space models to describe the stride-by-stride evolution of metrics of propulsion mechanics during and after robot-assisted training, applied by a hip/knee robotic exoskeleton for 200 consecutive strides. The five models included a single-state, a two-state, a two-state fast and slow, a use-dependent learning (UDL), and a newly-developed modified UDL model, requiring 4, 9, 5, 3, and 4 parameters, respectively. The coefficient of determination (R 2) and Akaike information criterion (AIC) values were calculated to quantify the goodness of fit of each model. Model fit was conducted both at the group and at the individual participant level. At the group level, the modified UDL model shows the best goodness-of-fit compared to other models in AIC values in 15/16 conditions. At the participant level, both the modified UDL model and the two-state model have significantly better goodness-of-fit compared to the other models. In summary, the modified UDL model is a simple 4-parameter model that achieves similar goodness-of-fit compared to a two-state model requiring 9 parameters. As such, the modified UDL model is a promising model to describe the effects of robot-aided gait training on propulsion mechanics.

QUANTIFYING VARIABILITY IN DAILY ACCELERATIONS RECORDED BY INERTIAL SENSORS IN HEALTHY INDIVIDUALS: IMPLICATIONS FOR GAIT MEASUREMENT IN FREE-LIVING ENVIRONMENTS

Gait measurements can vary due to various intrinsic and extrinsic factors, and this variability becomes more pronounced using inertial sensors in a free-living environment. Therefore, identifying and quantifying the sources of variability is essential to ensure measurement reliability and maintain data quality.This study aimed to determine the variability of daily accelerations recorded by an inertial sensor in a group of healthy individuals. Ten participants, four males and six females, with a mean age of 50 years (range: 29–61) and BMI of 26.9 kg/m2 (range: 21.4–36.8), were included. A single accelerometer continuously recorded lower limb accelerations over two weeks. We extracted and analyzed the accelerations of three consecutive strides within walking bouts if the time difference between the bouts was more than two hours. Multivariate mixed-effects modeling was performed on both the discretized acceleration waveforms at 101 points (0–100) and the harmonics of the signals in the frequency domain to determine the variance components for different subjects, days, bouts, and steps as the random effect variables. Intraclass correlation coefficients (ICCs) were calculated for between-day, between-bout, and between-step comparisons.The results showed that the ICCs for the between-day, between-bout, and between-step comparisons were 0.73, 0.82, 0.99 for the vertical axis; 0.64, 0.75, 0.99 for the anteroposterior axis; and 0.55, 0.96, 0.97 for the mediolateral axis. For the signal harmonics, the respective ICCs were 0.98, 0.98, 0.99 for the vertical axis; 0.54, 0.93, 0.98 for the anteroposterior axis; and 0.69, 0.78, 0.95 for the mediolateral axis.Overall, this study demonstrated that accelerations recorded continuously for multiple days in a free-living environment exhibit high variability, mainly between days, and some variability arising from differences between walking bouts during different times within days. However, reliable and repeatable gait measurements can be obtained by identifying and quantifying the sources of variability.

Biomechanical feedback and feedforward responses during perturbed running in asymptomatic individuals.

Assessment of biomechanical features whilst running on an uneven terrain plays an important role in identifying running-related injury mechanisms. However, feedback and feedforward motor responses and adaptations, an important component of gait retraining and injury rehabilitation programs, have been less investigated during running. Therefore, the current study assessed the whole-session responses and within-session adaptation mechanisms during perturbed running. Twenty three individuals performed an eight-minute perturbed treadmill running protocol with one-sided decelerative belt perturbations. Joint angle curves and muscle activity amplitudes were analysed throughout the running cycle, in both the perturbed and contralateral leg. For the whole-session responses, the average of 10 consecutive strides during the baseline trial and all perturbed strides from the perturbed running trial were compared. To assess within-session adaptation, the first perturbation was compared to the average of the last three perturbations. Data were analysed with one-dimensional statistical parametric mapping of Paired t-tests to assess responses and adaptations to the perturbations (P < 0.025). Regarding whole-session responses (baseline vs. perturbations), statistically significant feedback (after perturbation) responses were detected in most measured joint angles and muscle activity of both perturbed and contralateral legs. Feedforward (before perturbation) responses for whole-session comparison were detected for most joint angles in the contralateral leg and only hip flexion in the perturbed leg. Feedforward muscle activities of whole-session responses were different in the biceps femoris, semitendinosus, and erector spinae of the perturbed leg, and the soleus of the contralateral leg. Regarding within-session (first vs. last three perturbations) adaptation, feedback adaptations included statistically significant changes in ankle, knee, and hip movements, and muscle activities in the perturbed leg, while the contralateral leg showed less adaptation. No significant feedforward within-session adaptations were observed in the perturbed leg, but the contralateral leg showed changes in ankle dorsiflexion, soleus activity, and erector spinae activity. Findings suggest that participants compensated perturbations during running by modifying muscle activities and movement patterns, primarily through feedback mechanisms in the perturbed leg, with limited feedforward adaptations. The current protocol may present a viable approach for testing and training postural control during running.

Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running

Introduction: The seemingly periodic human gait exhibits stride-to-stride variations as it adapts to the changing task constraints. The optimal movement variability hypothesis (OMVH) states that healthy stride-to-stride variations exhibit “fractality”—a specific temporal structure in consecutive strides that are ordered, stable but also variable, and adaptable. Previous research has primarily focused on a single fractality measure, “monofractality.” However, this measure can vary across time; strideto-stride variations can show “multifractality.” Greater multifractality in stride-tostride variations would highlight the ability to tune and adjust movements more.Methods: We investigated monofractality and multifractality in a cohort of eight healthy adults during self-paced walking and running trials, both on a treadmill and overground. Footfall data were collected through force-sensitive sensors positioned on their heels and feet. We examined the effects of self-paced walking vs. running and treadmill vs. overground locomotion on the measure of monofractality, α-DFA, in addition to the multifractal spectrum width, W, and the asymmetry in the multifractal spectrum, WAsym, of stride interval time series.Results: While the α-DFA was larger than 0.50 for almost all conditions, α-DFA was higher in running and locomoting overground than walking and locomoting on a treadmill. Similarly, W was greater while locomoting overground than on a treadmill, but an opposite trend indicated that W was greater in walking than running. Larger WAsym values in the negative direction suggest that walking exhibits more variation in the persistence of shorter stride intervals than running. However, the ability to tune and adjust movements does not differ between treadmill and overground, although both exhibit more variation in the persistence of shorter stride intervals.Discussion: Hence, greater heterogeneity in shorter than longer stride intervals contributed to greater multifractality in walking compared to running, indicated by larger negative WAsym values. Our results highlight the need to incorporate multifractal methods to test the predictions of the OMVH.

On the variability and dependence of human leg stiffness across strides during running and some consequences for the analysis of locomotion data.

Typically, animal locomotion studies involve consecutive strides, which are frequently assumed to be independent with parameters that do not vary across strides. This assumption is often not tested. However, failing in particular to account for dependence across strides may cause an incorrect estimate of the uncertainty of the measurements and thereby lead to either missing (overestimating variance) or over-evaluating (underestimating variance) biological signals. In turn, this impacts replicability of the results because variability is accounted for differently across experiments. In this paper, we analyse the changes of a couple of measures of human leg stiffness across strides during running experiments, using a publicly available dataset. A major finding of this analysis is that the time series of these measurements of stiffness show autocorrelation even at large lags and so there is dependence between individual strides, even when separated by many intervening strides. Our results question the practice in biomechanics research of using each stride as an independent observation or of sub-selecting strides at small lags. Following the outcome of our analysis, we strongly recommend caution in doing so without first confirming the independence of the measurements across strides and without confirming that sub-selection does not produce spurious results.

Comparison of EMG activity in shank muscles between individuals with and without chronic ankle instability when running on a treadmill

Changes in movement capabilities after an injury to the ankle may impose adaptations in the peripheral and central nervous system. The purpose of our study was to compare the electromyogram (EMG) profile of ankle stabilizer muscles and stride-time variation during treadmill running in individuals with and without chronic ankle instability (CAI). Recreationally active individuals with (n=12) and without (n=15) CAI ran on a treadmill at two speeds. EMG activity of four shank muscles as well as tibial acceleration data were recorded during the running trials. EMG amplitude, timing of EMG peaks, and variation in stride-time were analyzed from 30 consecutive stride cycles. EMG data were time-normalized to stride duration and amplitude was normalized relative to the appropriate maximal voluntary contraction (MVC) task. Individuals with CAI had similar EMG amplitudes and peak timing, but an altered order of peak EMG activity in ankle stabilizer muscles, a significantly greater EMG amplitude for PL with an increase in speed, and a greater stride-time variability during treadmill running compared with individuals who had no history of ankle sprains. The results of our study indicate that individuals with CAI exhibit altered activation strategies for ankle stabilizer muscles when running on a treadmill.

Effect of speed and leading or trailing limbs on surface muscle activities during canter in Thoroughbred horses.

Given that Thoroughbred horses' canter is an asymmetric gait, not only speed but also leading or trailing limbs could affect muscle activities. However, the muscle activity during a canter remains poorly understood. Hence, we aimed to investigate speed and lead-side (leading or trailing) effects on surface electromyography (sEMG) during a canter. The sEMG data were recorded from left Musculus brachiocephalicus (Br), M. infraspinatus (Inf), long head of M. triceps brachii (TB), M. gluteus medius (GM), M. semitendinosus (ST), and M. flexor digitorum longus of seven Thoroughbreds with hoof-strain gauges at the left hooves. Horses cantered on a flat treadmill at 7, 10, and 13 m/s for 25 s each without lead change. Subsequently, the horses trotted for 3 min and cantered at the same speed and duration in the opposite lead side ("leading" at the left lead and "trailing" at the right lead). The order of the lead side and speed was randomized. The mean of 10 consecutive stride durations, duty factors, integrated-EMG values (iEMG) for a stride, and muscle onset and offset timing were compared using a generalized mixed model (P < 0.05). Stride durations and duty factors significantly decreased with speed regardless of the lead side. In all muscles, iEMG at 13 m/s significantly increased compared with 7 m/s (ranging from +15% to +134%). The lead-side effect was noted in the iEMG of Br (leading > trailing, +47%), Inf (leading > trailing, +19%), GM (leading < trailing, +20%), and ST (leading < trailing, +19%). In TB, GM, and ST, muscle onset in trailing was earlier than the leading, while offset in the leading was earlier in Br. In conclusion, different muscles have different responses to speed and lead side; thus, both the lead side and running speed should be considered during training and/or rehabilitation including canter or gallop.

Long-term levodopa ameliorates sequence effect in simple, but not complex walking in early Parkinson's disease patients

BackgroundThe sequence effect (SE) is characterized by the progressive decrement of movements and is often observed in Parkinson's disease (PD) patients. While acute effect of levodopa does not ameliorate the SE, the effect of long-term levodopa treatment for the SE remains unknown. ObjectiveWe aimed to elucidate the SEs during various gait conditions and their response to long-term levodopa treatment in drug-naïve PD patients. MethodsNineteen drug-naïve PD patients and 21 healthy controls were enrolled. Gait parameters were measured via wearable inertial sensors in the following conditions:1) straight walking, 2) circular walking: walking a circle of 1 m diameter in a clock-wise direction for 3 laps, 3) straight or circular walking under cognitive-motor dual-task (serial 7s subtractions). PD patients were evaluated at baseline, within 1 h after intravenous administration of levodopa, and after one, three, and six months treatment with levodopa. The SE was measured by a linear regression slope by plotting consecutive stride lengths over steps. Patients were also separately analyzed depending on laterality of symptoms. ResultsLong-term levodopa treatment ameliorated the SE only during single-task straight walking. The SE during circular walking was exacerbated after long-term levodopa treatment for right-side dominant patients. During dual-task straight walking, the SE at baseline was greater in right-side dominant PD patients. ConclusionsThe SE only during single-task straight walking can be ameliorated by long-term levodopa treatment. However, the SE may be exaggerated by cognitive motor interference or by asymmetrical stride length with/without long-term levodopa treatment, depending on the laterality of symptoms.

Exploring surface electromyography (EMG) as a feedback variable for the human-in-the-loop optimization of lower limb wearable robotics.

Human-in-the-loop (HITL) optimization with metabolic cost feedback has been proposed to reduce walking effort with wearable robotics. This study investigates if lower limb surface electromyography (EMG) could be an alternative feedback variable to overcome time-intensive metabolic cost based exploration. For application, it should be possible to distinguish conditions with different walking efforts based on the EMG. To obtain such EMG data, a laboratory experiment was designed to elicit changes in the effort by loading and unloading pairs of weights (in total 2, 4, and 8 kg) in three randomized weight sessions for 13 subjects during treadmill walking. EMG of seven lower limb muscles was recorded for both limbs. Mean absolute values of each stride prior to and following weight loading and unloading were used to determine the detection rate (100% if every loading and unloading is detected accordingly) for changing between loaded and unloaded conditions. We assessed the use of multiple consecutive strides and the combination of muscles to improve the detection rate and estimated the related acquisition times of diminishing returns. To conclude on possible limitations of EMG for HITL optimization, EMG drift was evaluated during the Warmup and the experiment. Detection rates highly increased for the combination of multiple consecutive strides and the combination of multiple muscles. EMG drift was largest during Warmup and at the beginning of each weight session. The results suggest using EMG feedback of multiple involved muscles and from at least 10 consecutive strides (5.5 s) to benefit from the increases in detection rate in HITL optimization. In combination with up to 20 excluded acclimatization strides, after changing the assistance condition, we advise exploring about 16.5 s of walking to obtain reliable EMG-based feedback. To minimize the negative impact of EMG drift on the detection rate, at least 6 min of Warmup should be performed and breaks during the optimization should be avoided. Future studies should investigate additional feedback variables based on EMG, methods to reduce their variability and drift, and should apply the outcomes in HITL optimization with lower limb wearable robots.

Reliability of a novel method to assess correlation structure among consecutive stride intervals using a low-back accelerometer: A test-retest study

Reliability of a novel method to assess correlation structure among consecutive stride intervals using a low-back accelerometer: A test-retest study

Fetlock Joint Angle Pattern and Range of Motion Quantification Using Two Synchronized Wearable Inertial Sensors per Limb in Sound Horses and Horses with Single Limb Naturally Occurring Lameness.

Simple SummaryThe incidence of disease affecting fetlock joint and associated structures is high in the equine athlete due to the large loads acting on the joint during athletic activity. Therefore, study of the movement of this joint (flexion and extension) is a significant matter of interest. To date, fetlock joint angle pattern and range of motion in horses have been quantified using optical motion capture (OMC). These systems use a number of cameras to film the subject and reconstruct the movement trajectories into a computer model. They are very accurate and precise but require expensive equipment and a laboratory setting. The use of inertial measurement unit (IMU) systems in the field of motion analysis is now widespread. IMU systems use a number of sensors in order to derive the position of the body in the space; they have the advantage of being able to collect kinematic spatio-temporal data when the animal is moving overground with fewer constraints than in a gait lab. To the authors’ best knowledge there are no studies using IMUs sensors in order to record relative fetlock joint angles in horses moving overground. In this study, we wanted first to validate the use of IMUs for kinematic detection of fetlock joint movement on the sagittal axis comparing it to the OMC. Then, we intended to discuss fetlock joint range of motion variability quantified by the IMU system under investigation in lame and sound horses. The IMU system was able to record fetlock joint range of motion just as does the bi-dimensional OMC at walk and trot, in both sound and lame horses. IMU system quantification of fetlock joint range of motion confirmed that the variability was mainly due to lameness in our population of horses. Quantifying joint angle patterns with an IMU system instead of using OMC has the advantage of furnishing real-time bio-feedback of kinematic data. The system can handle various equine gaits and clinical and training conditions outside of expensive laboratory circumstances.Fetlock joint angle (FJA) pattern is a sensitive indicator of lameness. The first aim of this study is to describe a network of inertial measurement units system (IMUs) for quantifying FJA simultaneously in all limbs. The second aim is to evaluate the accuracy of IMUs for quantifying the sagittal plane FJA overground in comparison to bi-dimensional (2-D) optical motion capture (OMC). 14 horses (7 free from lameness and 7 lame) were enrolled and analyzed with both systems at walk and trot on a firm surface. All enrolled horses were instrumented with 8 IMUs (a pair for each limb) positioned at the dorsal aspect of the metacarpal/metatarsal bone and pastern and acquiring data at 200 Hz. Passive markers were glued on the center of rotation of carpus/tarsus, fetlock, and distal interphalangeal joint, and video footages were captured at 60 Hz and digitalized for OMC acquisition. The IMU system accuracy was reported as Root Mean Square Error (RMSE) and Pearson Correlation Coefficient (PCC). The Granger Causality Test (GCT) and the Bland–Altman analysis were computed between the IMUs and OMC patterns to determine the agreement between the two systems. The proposed IMU system was able to provide FJAs in all limbs using a patented method for sensor calibration and related algorithms. Fetlock joint range of motion (FJROM) variability of three consecutive strides was analyzed in the population through 3-way ANOVA. FJA patterns quantified by IMUs demonstrated high accuracy at the walk (RMSE 8.23° ± 3.74°; PCC 0.95 ± 0.03) and trot (RMSE 9.44° ± 3.96°; PCC 0.96 ± 0.02) on both sound (RMSE 7.91° ± 3.19°; PCC 0.97 ± 0.03) and lame horses (RMSE 9.78° ± 4.33°; PCC 0.95 ± 0.03). The two systems’ measurements agreed (mean bias around 0) and produced patterns that were in temporal agreement in 97.33% of the cases (p < 0.01). The main source of variability between left and right FJROM in the population was the presence of lameness (p < 0.0001) and accounted for 28.46% of this total variation. IMUs system accurately quantified sagittal plane FJA at walk and trot in both sound and lame horses.

Comparison of Heel Movement Between two Different Glue-on Type Shoes and Nailed Shoes in Thoroughbreds

Gluing an aluminum shoe onto equine hooves has been known to restrict heel movement and might cause interference with shock absorption and blood flow to the hoof. To investigate the effects of new glue-on type shoes on heel movement, 2 experiments that compared forelimb heel movement between conventional nailed shoes and flexible polyurethane glue-on shoes or Hanton-type shoes, which had 2 side clips for adhesive, were conducted on separate days. A displacement sensor was fixed on the heel to measure the forelimb's mediolateral heel movement. Exercise consisted of walking at 1.7 m/s, trotting at 4 m/s, cantering at 8 and 12 m/s for 30 seconds on a treadmill without a slope. The average heel expansion, contraction, and total heel movement (sum of the absolute expansion and contraction values) of 10 consecutive strides between the nailed shoes and glue-on shoes were compared using the paired t-tests. No significant differences in heel movement were observed between polyurethane glued shoes and nailed shoes regardless of gait. During trotting, Hanton shoes promoted significantly smaller heel expansion (14% decrease, P < 0.01) and larger heel contraction (11% increase, P = 0.03) compared to conventional nailed shoes, although no difference in total heel movement was observed. Furthermore, neither heel expansion nor contraction nor total movement in other gaits showed significant differences between Hanton shoes and conventional nailed shoes. The aforementioned results suggested that the new glue-on type shoes promoted similar heel movement compared to conventional nailed shoes.

Strides to Achieve a Stable Symmetry Index During Running.

The quality of running mechanics is often characterized by limb pattern symmetry and used to support clinical decisions throughout the rehabilitation of lower-extremity injuries. It is valuable to ensure that gait analyses provide stable measures while not asking an individual to complete an excessive number of running strides. The present study aimed to determine the minimum number of strides required to establish a stable mean symmetry index (SMSI) of discrete-level measures of spatiotemporal parameters, joint kinematics, and joint kinetics. Further, the study aimed to determine if differences occurred between random and consecutive strides for directional and absolute symmetry indices. Descriptive laboratory study. A sequential average was used to determine how many strides were required to achieve a SMSI within a 60-second trial. Multiple 2-factor repeated-measure analysis of variances were used to determine if differences between bins of strides and symmetry calculations were significantly different. A median SMSI was achieved in 15 strides for all biomechanical variables. There were no significant differences (P > .05) found between consecutive and random bins of 15 strides within a 60-second trial. Although there were significant differences between symmetry calculation values for most variables (P < .05), there appeared to be no systematic difference between the numbers of strides required for stable symmetry for either index. As 15 strides were sufficient to achieve a SMSI during running, a continued emphasis should be placed on the number of strides collected when examining interlimb symmetry.

Gait-based Frailty Assessment using Image Representation of IMU Signals and Deep CNN.

Frailty is a common and critical condition in elderly adults, which may lead to further deterioration of health. However, difficulties and complexities exist in traditional frailty assessments based on activity-related questionnaires. These can be overcome by monitoring the effects of frailty on the gait. In this paper, it is shown that by encoding gait signals as images, deep learning-based models can be utilized for the classification of gait type. Two deep learning models (a) SS-CNN, based on single stride input images, and (b) MS-CNN, based on 3 consecutive strides were proposed. It was shown that MS-CNN performs best with an accuracy of 85.1%, while SS-CNN achieved an accuracy of 77.3%. This is because MS-CNN can observe more features corresponding to stride-to-stride variations which is one of the key symptoms of frailty. Gait signals were encoded as images using STFT, CWT, and GAF. While the MS-CNN model using GAF images achieved the best overall accuracy and precision, CWT has a slightly better recall. This study demonstrates how image encoded gait data can be used to exploit the full potential of deep learning CNN models for the assessment of frailty.

Running gait biomechanics in females with chronic ankle instability and ankle sprain copers

ABSTRACT Limited evidence exists comparing running biomechanics between individuals with chronic ankle instability (CAI) and those who fully recover (copers). The purpose of this study was to simultaneously analyse running gait kinematics, kinetics, and surface electromyography (sEMG) between ankle sprain copers and individuals with CAI. Twenty-six (13 CAI, 13 Coper) recreationally active females participated and ran shod on an instrumented treadmill at 2.68 m/s. We assessed lower extremity kinematics and kinetics and sEMG amplitude for the fibularis longus, tibialis anterior, medial gastrocnemius, and gluteus medius muscles. Ten consecutive strides from the beginning of the trial were analysed using statistical parametric mapping (SPM) independent t-test. The CAI group had significantly more ankle inversion during 0–6%, 42–53%, and 96–100% of the running stride cycle compared to the coper group. At initial contact (0%), the CAI group was in an inverted ankle position (5.9°±6.8°) and the coper group was in an everted ankle position (−3.2°±5.5°; p = 0.01, d = 1.5). There were no significant differences identified for any other outcome measures. Increased ankle inversion during the swing phase leading into the loading phase is concerning because the ankle is in an open packed position and inversion is a primary mechanism of injury for sustaining a lateral ankle sprain.

Test–Retest Reliability and the Effects of Walking Speed on Stride Time Variability During Continuous, Overground Walking in Healthy Young Adults

Studies have investigated the reliability and effect of walking speed on stride time variability during walking trials performed on a treadmill. The objective of this study was to investigate the reliability of stride time variability and the effect of walking speed on stride time variability, during continuous, overground walking in healthy young adults. Participants completed: (1)2 walking trials at their preferred walking speed on 1day and another trial 2 to 4 days later and (2)1 trial at their preferred walking speed, 1 trial approximately 20% to 25% faster than their preferred walking speed, and 1 trial approximately 20% to 25% slower than their preferred walking speed on a separate day. Data from a waist-mounted accelerometer were used to determine the consecutive stride times for each trial. The reliability of stride time variability outcomes was generally poor (intraclass correlations: .167-.487). Although some significant differences in stride time variability were found between the preferred walking speed, fast, and slow trials, individual between-trial differences were generally below the estimated minimum difference considered to be a real difference. The development of a protocol to improve the reliability of stride time variability outcomes during continuous, overground walking would be beneficial to improve their application in research and clinical settings.

Initiation gait variability is higher in the morning in elderly inpatients.

Although elderly inpatients are known to experience decreased physical activity in the morning, falls occur frequently during this time. Gait variability is an evaluation of gait instability and a risk factor for falls. Gait initiation requires complex processes, and it is important to evaluate gait variability not only during steady-state gait but also during gait initiation. However, the effect of the diurnal pattern on variability in gait characteristics is still unknown. The aim of this study was to investigate the effect of the diurnal pattern on initiation and steady-state gait variability in elderly inpatients. Thirty-seven elderly inpatients (28 women; mean age, 79.7 ± 9.5 years) who could walk without support were sampled in this study. The quantitative measure of gait variability was evaluated using the coefficient of variation (CV) based on four consecutive stride durations determined using triaxial accelerometers. Gait characteristics were evaluated during initiation and steady-state gait and defined as initiation CV and steady-state CV, respectively. This measurement was performed at two time points, morning and daytime. There was no significant difference between initiation and steady-state gait characteristics in the daytime condition. However, in the morning condition, the initiation CV was higher than the steady-state CV. Furthermore, the initiation CV was higher in the morning than during daytime (p < 0.01). Our study revealed that the variability of initiation gait is higher in the morning. It may be important to assess the risk of falls, including initiation gait, in the morning.

VALIDITY AND RELIABILITY OF VIDEO-BASED ANALYSIS OF UPPER TRUNK ROTATION DURING RUNNING.

Two-dimensional (2D) video analysis is a practical tool for assessing biomechanical factors that may contribute to running-related injury. Asymmetrical or altered coordination of transverse plane trunk movement has been associated with low back pain, increased vertical and horizontal ground reaction forces, and altered hip abduction torque and strength. However, the reliability and validity of 2D transverse plane upper trunk rotation (UTR) has not been assessed. Validity and reliability study. To determine the validity and reliability of 2D video-based, transverse plane UTR measurement during running. Sixteen runners ran at self-selected speed on a treadmill while three-dimensional (3D) and 2D motion capture occurred synchronously. Two raters measured peak UTR for five consecutive strides on two occasions. Interrater and intrarater reliability and the minimum detectable change was calculated for right and left peak 2D UTR measurement. Concurrent validity and agreement between 2D and 3D measures were determined by calculating Pearson Product Correlation Coefficients (r) and Bland-Altman plots, respectively. Using a single UTR measure per runner, intrarater and interrater reliability (ICC2,1) was excellent (intrarater ICC2,1 range: 0.989-0.999; interrater ICC2,1 range: 0.990-0.995) and the minimum detectable change was 0.39-1.4 degrees. Measurements in 2D and 3D were significantly correlated for peak UTR (all r ≥ 0.986; all p-values < 0.001) and showed good agreement in Bland-Altman plots. Two-dimensional video-based measurement of transverse plane peak UTR is valid and reliable. UTR measurement may provide clinical insight into gait deviations in the transverse plane that alter angular momentum and increase risk for running-related injury. 2B.

Reliable and clinically applicable gait event classification using upper body motion in walking and trotting horses

Objectively assessing horse movement symmetry as an adjunctive to the routine lameness evaluation is on the rise with several commercially available systems on the market. Prerequisites for quantifying such symmetries include knowledge of the gait and gait events, such as hoof to ground contact patterns over consecutive strides. Extracting this information in a robust and reliable way is essential to accurately calculate many kinematic variables commonly used in the field. In this study, optical motion capture was used to measure 222 horses of various breeds, performing a total of 82 664 steps in walk and trot under different conditions, including soft, hard and treadmill surfaces as well as moving on a straight line and in circles. Features were extracted from the pelvis and withers vertical movement and from pelvic rotations. The features were then used in a quadratic discriminant analysis to classify gait and to detect if the left/right hind limb was in contact with the ground on a step by step basis. The predictive model achieved 99.98% accuracy on the test data of 120 horses and 21 845 steps, all measured under clinical conditions. One of the benefits of the proposed method is that it does not require the use of limb kinematics making it especially suited for clinical applications where ease of use and minimal error intervention are a priority. Future research could investigate the extension of this functionality to classify other gaits and validating the use of the algorithm for inertial measurement units.