Gait variability analysis through phase portrait estimated from the Hilbert transform

Abstract

Gait variability has been used to evaluate the ability to control gait. Several studies approached this topic by analysing the influence of different conditions on gait variability, such as different walk speeds, inclined surfaces, load carriage, or comparing characteristics of subject groups, such as age, sedentarism and impairment level. The aim of this study was to develop and assess a new method, based on the property of the Hilbert transform of easily creating a phase portrait from a single time series, capable of estimating variability within gait cycles. The obtained results were based on a comparison of the proposed method with a traditional one whilst analysing a data set related to gait evaluation on inclined surfaces. Furthermore, the influence of noise over the estimated gait variability was assessed. The results showed that the proposed method is less sensitive to the presence of noise, with the advantage of not relying on signal interpolation, being thus an alternative to the analysis of gait variability.     

A machine learning approach for automated recognition of movement patterns using basic, kinetic and kinematic gait data

This paper investigated application of a machine learning approach (Support vector machine, SVM) for the automatic recognition of gait changes due to ageing using three types of gait measures: basic temporal/spatial, kinetic and kinematic. The gaits of 12 young and 12 elderly participants were recorded and analysed using a synchronized PEAK motion analysis system and a force platform during normal walking. Altogether, 24 gait features describing the three types of gait characteristics were extracted for developing gait recognition models and later testing of generalization performance. Test results indicated an overall accuracy of 91.7% by the SVM in its capacity to distinguish the two gait patterns. The classification ability of the SVM was found to be unaffected across six kernel functions (linear, polynomial, radial basis, exponential radial basis, multi-layer perceptron and spline). Gait recognition rate improved when features were selected from different gait data type. A feature selection algorithm demonstrated that as little as three gait features, one selected from each data type, could effectively distinguish the age groups with 100% accuracy. These results demonstrate considerable potential in applying SVMs in gait classification for many applications.     

Gait variability magnitude but not structure is altered in essential tremor

Essential tremor (ET) is a common tremor disorder affecting postural/action tremor of the upper extremities and midline. Recent research revealed a cerebellar-like deficit during tandem gait in persons with ET, though spatiotemporal variability during normal gait in ET has been relatively ignored. The first purpose of this study was to investigate gait variability magnitude and structure in ET as compared to healthy older adults (HOA). To address this issue, 11 ET and 11 age-matched HOAs walked on a treadmill for 5 min at preferred walking speeds. HOAs walked for an additional minute while speed-matched to an ET participant. The second purpose was to describe the clinical correlates of gait variability in this population. To address this aim, 31 persons with ET walked on a treadmill for 5 min and completed the Fahn–Tolosa–Marin Tremor Rating Scale. Gait variability magnitude was derived by calculating coefficients of variation in stride length, stride time, step length, step time, and step width. Gait variability structure was derived using a detrended fluctuation analysis technique. At preferred walking speeds, ET participants walked significantly slower with significantly increased variability magnitude in all five spatiotemporal gait parameters. At speed-matched walking, ET participants exhibited significantly higher step width variability. Gait variability structure was not different between groups. We also observed that gait variability magnitude was predicted by severity of upper extremity and midline tremors. This study revealed that self-selected gait in ET is characterized by high variability that is associated with tremor severity in the upper extremity and midline.     

Computational evaluation of load carriage effects on gait balance stability

Evaluating the effects of load carriage on gait balance stability is important in various applications. However, their quantification has not been rigorously addressed in the current literature, partially due to the lack of relevant computational indices. The novel Dynamic Gait Measure (DGM) characterizes gait balance stability by quantifying the relative effects of inertia in terms of zero-moment point, ground projection of center of mass, and time-varying foot support region. In this study, the DGM is formulated in terms of the gait parameters that explicitly reflect the gait strategy of a given walking pattern and is used for computational evaluation of the distinct balance stability of loaded walking. The observed gait adaptations caused by load carriage (decreased single support duration, inertia effects, and step length) result in decreased DGM values (p < 0.0001), which indicate that loaded walking motions are more statically stable compared with the unloaded normal walking. Comparison of the DGM with other common gait stability indices (the maximum Floquet multiplier and the margin of stability) validates the unique characterization capability of the DGM, which is consistently informative of the presence of the added load.     

Gait Variability before Surgery and at Discharge in Patients Who Undergo Total Knee Arthroplasty: A Cohort Study

This study aimed to determine gait ability at hospital discharge in patients undergoing total knee arthroplasty (TKA) as an indicator of the risk of falling. Fifty-seven patients undergoing primary TKA for knee osteoarthritis participated in this study. Gait variability measured with accelerometers and physical function including knee range of motion (ROM), quadriceps strength, walking speed, and the Timed Up and Go (TUG) test were evaluated preoperatively and at discharge from the hospital (1 month before and 5 days after surgery). All patients were discharged directly home at 5 days after surgery. Knee flexion of ROM, quadriceps strength, walking speed, and the TUG test results were significantly worse at hospital discharge than preoperatively (p < 0.001). However, gait variability was not significantly different before and after TKA. This result indicated that patients following TKA surgery could walk at hospital discharge as stably as preoperatively regardless of the decrease in physical function, including knee ROM, quadriceps strength, and gait speed after surgery.     

Effect of boot shaft stiffness on stability joint energy and muscular co-contraction during walking on uneven surface

Increased boot shaft stiffness may have a noticeable impact on the range of motion of the ankle joint. Therefore, the ability of the ankle joint to generate power for propulsion might be impaired. This might result in compensatory changes at the knee and hip joint. Besides, adaptability of the subtalar joint to uneven surface might be reduced, which could in turn affect stability. The aim of the study was therefore to investigate the influence of boot shaft stiffness on biomechanical gait parameters.Fifteen healthy young adults walked over coarse gravel wearing two different hiking boots that differed by 50% in passive shaft stiffness. Leg kinematics, kinetics and electromyography were measured. Gait velocity and indicators for stability were not different when walking with the hard and soft boot shaft over the gravel surface. However, the hard boot shaft decreased the ankle range of motion as well as the eccentric energy absorbed at the ankle joint. As a consequence, compensatory changes at the knee joint were observed. Co-contraction was increased, and greater eccentric energy was absorbed. Therefore, the efficiency of gait with hard boots might be decreased and joint loading at the knee might be increased, which might cause early fatigue of knee muscles during walking or hiking. The results of this study suggest that stiffness and blocking of joint motion at the ankle should not be equated with safety. A trade-off between lateral stiffness and free natural motion of the ankle joint complex might be preferable.     

Effect of severity of knee osteoarthritis on the variability of gait parameters

Gait analysis has provided important information concerning gait patterns and variability of gait in patients with knee osteoarthritis (OA) of varying severity. The objective of this study was to clarify how the variability of gait parameters is influenced by the severity of knee OA. Gait analysis was performed at three different controlled walking speeds in three groups of subjects with varying degrees of knee OA (20 healthy subjects with no OA and 90 patients with moderate or severe OA). The variability of gait parameters was characterized by the coefficient of variance (CV) of spatial-temporal parameters, as well as by the mean coefficient variance (MeanCV) of angular parameters. Based on our results, we conclude that the complexity of gait decreases if the walking speed differs from the self-selected speed. In patients with knee OA, the decreased variability of angular parameters on the affected side represents decreased joint flexibility. This leads to decreased consistency in movements of the lower limbs from stride-to-stride, as shown by increased variability of spatial-temporal parameters. Decreased joint flexibility and consistency of movement can be associated with decreased complexity of movement. Other joints of the kinetic chain, such as joints of the non-affected side and the pelvis, play an important role in compensation and adaptation of step-by step motion and in the ability of secure gait. Results suggest that the variability of gait associated with knee osteoarthritis is gender-dependent. During rehabilitation, particular attention must be paid to improving gait stability and proprioception and gender differences should be taken into account.     

Effect of walking speed and severity of hip osteoarthritis on gait variability

Gait analysis in orthopaedic and neurological examinations is important; however, few studies assess gait variability at different walking speeds in patients with varying degrees of hip osteoarthritis. We aimed to clarify (1) how different controlled speeds and (2) various severities of hip osteoarthritis influence gait variability. Gait variability was described by the standard deviation (SD) of the spatial–temporal and mean standard deviation (MeanSD) of angular parameters. The spatial positions of the anatomical points for calculating gait parameters were determined in 20 healthy elderly controls and 20 patients with moderate and 20 patients with severe hip osteoarthritis with a zebris CMS-HS ultrasound-based motion analysis system at three walking speeds. The SD of the spatial–temporal and MeanSD of angular parameters of gait, which together describe gait variability, significantly depended on speed and osteoarthritis severity. The lowest variability in the gait was found near the self-selected walking speeds. Hip joint degeneration significantly worsened variability on the affected side, with non-affected joints and the pelvis compensating by increasing flexibility and adapting to step-by-step motions. Particular attention must be paid to improving gait stability and the reliability of limb movements in the presence of and increasing severity of osteoarthritis.     

Neural network estimation of balance control during locomotion

Gait patterns of the elderly are often adjusted to accommodate for reduced function in the balance control system and a general reduction in skeletal muscle strength. Recent studies have demonstrated that measures related to motion of whole body center of mass (COM) can distinguish elderly individuals with balance impairment from healthy peers. Accurate COM estimation requires a multiple-segment anthropometric model, which may restrict its broad application in assessment of dynamic instability. Although temporal-distance measures and electromyography have been used in evaluation of overall gait function and determination of gait dysfunction, no studies have examined the use of gait measurements in predicting COM motion during gait. The purpose of this study was to demonstrate the effectiveness of an artificial neural network (ANN) model in mapping gait measurements onto COM motion in the frontal plane. Data from 40 subjects of varied age and balance impairment were entered into a 3-layer feed-forward model with back-propagated error correction. Bootstrap re-sampling was used to enhance the generalization accuracy of the model, using 20 re-sampling trials. The ANN model required minimal processing time (5 epochs, with 20 hidden units) and accurately mapped COM motion (R-values up to 0.89). As training proportion and number of hidden units increased, so did model accuracy. Overall, this model appears to be effective as a mapping tool for estimating balance control during locomotion. With easily obtained gait measures as input and a simple, computationally efficient architecture, the model may prove useful in clinical scenarios where electromyography equipment exists.     

Diurnal gait fluctuations in single- and dual- task conditions

ABSTRACT

Gait is one of the most basic movements, and walking activity accomplished in dual task conditions realistically represents daily life mobility. Much is known about diurnal variations of gait components such as muscle power, postural control, and attention. However, paradoxically only little is known about gait itself. The aim of this study was to analyze whether gait parameters show time-of-day fluctuation in simple and dual task conditions. Sixteen young subjects performed sessions at five specific hours (06:00, 10:00, 14:00, 18:00 and 22:00 h), performing a single (walking or counting) and a dual (walking and counting) task. When performing gait in dual task conditions, an additional cognitive task had to be carried out. More precisely, the participants had to count backwards from a two-digit random number by increments of three while walking. Spatio-temporal gait parameters and counting performance data were recorded for analysis. Walking speed significantly decreased, while stride length variability increased when the task condition switched from single to dual. In the single-task condition, diurnal variations were observed in both walking speed and counting speed. Walking speed was higher in the afternoon and in the evening (14:00 and 22:00 h) and lower in the morning (10:00 h). Counting speed was maximum at 10:00 and 14:00 h and minimum at 18:00 h. Nevertheless, no significant diurnal fluctuation was substanytiated in the dual task condition. These results confirm the existing literature about changes in gait between single and dual task conditions. A diurnal pattern of single-task gait could also be highlighted. Moreover, this study suggests that diurnal variations faded in complex dual task gait, when the cognitive load nearly reached its maximum. These findings might be used to reduce the risk for falls, especially of the elderly.     

Men and women adopt similar walking mechanics and muscle activation patterns during load carriage

Although numerous studies have investigated the effects of load carriage on gait mechanics, most have been conducted on active military men. It remains unknown whether men and women adapt differently to carrying load. The purpose of this study was to compare the effects of load carriage on gait mechanics, muscle activation patterns, and metabolic cost between men and women walking at their preferred, unloaded walking speed. We measured whole body motion, ground reaction forces, muscle activity, and metabolic cost from 17 men and 12 women. Subjects completed four walking trials on an instrumented treadmill, each five minutes in duration, while carrying no load or an additional 10%, 20%, or 30% of body weight. Women were shorter (p<0.01), had lower body mass (p=0.01), and had lower fat-free mass (p=0.02) compared to men. No significant differences between men and women were observed for any measured gait parameter or muscle activation pattern. As load increased, so did net metabolic cost, the duration of stance phase, peak stance phase hip, knee, and ankle flexion angles, and all peak joint extension moments. The increase in the peak vertical ground reaction force was less than the carried load (e.g. ground force increased approximately 6% with each 10% increase in load). Integrated muscle activity of the soleus, medial gastrocnemius, lateral hamstrings, vastus medialis, vastus lateralis, and rectus femoris increased with load. We conclude that, despite differences in anthropometry, men and women adopt similar gait adaptations when carrying load, adjusted as a percentage of body weight.     

Effect of stable and unstable load carriage on walking gait variability,dynamic stability and muscle activity of older adults

Load carriage perturbs the neuromuscular system, which can be impaired due to ageing. The ability to counteract perturbations is an indicator of neuromuscular function but if the response is insufficient the risk of falls will increase. However, it is unknown how load carriage affects older adults. Fourteen older adults (65 ± 6 years) attended a single visit during which they performed 4 min of walking in 3 conditions, unloaded, stable backpack load and unstable backpack load. During each walking trial, 3-dimensional kinematics of the lower limb and trunk movements and electromyographic activity of 6 lower limb muscles were recorded. The local dynamic stability (local divergence exponents), joint angle variability and spatio-temporal variability were determined along with muscle activation magnitudes. Medio-lateral dynamic stability was lower (p = 0.018) and step width (p = 0.019) and step width variability (p = 0.015) were greater in unstable load walking and step width variability was greater in stable load walking (p = 0.009) compared to unloaded walking. However, there was no effect on joint angle variability. Unstable load carriage increased activity of the Rectus Femoris (p = 0.001) and Soleus (p = 0.043) and stable load carriage increased Rectus Femoris activity (p = 0.006). These results suggest that loaded walking alters the gait of older adults and that unstable load carriage reduces dynamic stability compared to unloaded walking. This can potentially increase the risk of falls, but also offers the potential to use unstable loads as part of fall prevention programmes.     

Dynamic analysis of load carriage biomechanics during level walking

This paper describes an investigation into the biomechanical effects of load carriage dynamics on human locomotion performance. A whole body, inverse dynamics gait model has been developed which uses only kinematic input data to define the gait cycle. To provide input data, three-dimensional gait measurements have been conducted to capture whole body motion while carrying a backpack. A nonlinear suspension model is employed to describe the backpack dynamics. The model parameters for a particular backpack system can be identified using a dynamic load carriage test-rig. Biomechanical assessments have been conducted based on combined gait and pack simulations. It was found that the backpack suspension stiffness and damping have little effect on human locomotion energetics. However, decreasing suspension stiffness offers important biomechanical advantages. The peak values of vertical pack force, acting on the trunk, and lower limb joint loads are all moderated. This would reduce shoulder strap pressures and the risk of injury when heavy loads are carried.     

An application of principal component analysis for lower body kinematics between loaded and unloaded walking

Load carriage is a very common daily activity at home and in the workplace. Generally, the load is in the form of an external load carried by an individual, it could also be the excessive body mass carried by an overweight individual. To quantify the effects of carrying extra weight, whether in the form of an external load or excess body mass, motion capture data were generated for a diverse subject set. This consisted of twenty-three subjects generating one hundred fifteen trials for each loading condition. This study applied principal component analysis (PCA) to motion capture data in order to analyze the lower body gait patterns for four loading conditions: normal weight unloaded, normal weight loaded, overweight unloaded and overweight loaded.PCA has been shown to be a powerful tool for analyzing complex gait data. In this analysis, it is shown that in order to quantify the effects of external loads and/or for both normal weight and overweight subjects, the first principal component (PC1) is needed. For the work in this paper, PCs were generated from lower body joint angle data. The PC1 of the hip angle and PC1 of the ankle angle are shown to be an indicator of external load and BMI effects on temporal gait data.     

Effects of general fatigue induced by incremental maximal exercise test on gait stability and variability of healthy young subjects

The purpose of this study was to determine whether general fatigue induced by incremental maximal exercise test (IMET) affects gait stability and variability in healthy subjects. Twenty-two young healthy male subjects walked in a treadmill at preferred walking speed for 4 min prior (PreT) the test, which was followed by three series of 4 min of walking with 4 min of rest among them. Gait variability was assessed using walk ratio (WR), calculated as step length normalized by step frequency, root mean square (RMS_ratio) of trunk acceleration, standard deviation of medial-lateral trunk acceleration between strides (VAR_ML), coefficient of variation of step frequency (SFCV), length (SLCV) and width (SWCV). Gait stability was assessed using margin of stability (MoS) and local dynamic stability (λ_s). VAR_ML, SFCV, SLCV and SWCV increased after the test indicating an increase in gait variability. MoS decreased and λ_s increased after the test, indicating a decrease in gait stability. All variables showed a trend to return to PreT values, but the 20-min post-test interval appears not to be enough for a complete recovery. The results showed that general fatigue induced by IMET alters negatively the gait, and an interval of at least 20 min should be considered for injury prevention in tasks with similar demands.     

Impact of the method of exposure in total hip arthroplasty on the variability of gait in the first 6 months of the postoperative period

Introduction, objectiveGait analysis has provided important information about the variability of gait for patients prior to and after total hip arthroplasty (THA). The objective of this research was to clarify how the method of exposure in total hip arthroplasty affects the variability of gait.Materials and methodGait analysis was performed at 0.8 m/s, 1.0 m/s, and 1.2 m/s on 25 patients with direct-lateral exposure (DL), 22 with antero-lateral exposure (AL) and 25 with posterior exposure (P) during total hip arthroplasty. The control group was represented by 45 healthy subjects of identical age. Gait analysis was performed pre-operatively and 3 and 6 months after the surgery. Gait parameter variability was characterized by the coefficient of variance (CV) of spatial–temporal parameters and by the mean coefficient of variance (MeanCV) of angular parameters.ResultsThe variability of gait tends to reach control values during the first 6 months of the postoperative period in all three patient groups. Six months after THA, in patients operated with DL and AL exposure the variability of gait differs significantly from control values; however, in patients operated with P exposure, the variability of spatial–temporal and angular parameters – except the rotation of pelvis – was similar to that of controls.Discussion, conclusionThe type of surgical technique significantly influences the variability of gait. Difference in the variability of angular parameters predicts gait instability and increased risk of falling after THA without the joint capsule preserved. Joint capsule preservation ensures a recovery of gait variability. It should be taken into account when compiling rehabilitation protocols. Differences related to the method of exposure should be considered when abandoning therapeutic aids.     

Quantifying lumbar–pelvis coordination during gait using a modified vector coding technique

The complexity of human gait patterns has become a topic of major interest in motor control and biomechanics. Range of motion is still the preferred method to quantify movement impairment, however, within these traditional linear measures, the inter-segmental coordination and movement variability is normally ignored. A dynamical systems approach using vector coding and circular statistics provides non-linear techniques to quantify coordination and variability. This study provides comprehensive vector coding and circular statistics calculations. Additionally, pelvis–lumbar coordination and coordination variability data obtained from ten healthy young male participants during five walking trials using an optoelectronic system is provided. This novel data can form the baseline information for future studies in this area of research. Finally, a new illustration to present coordination and coordination variability information of gait kinematics, combining the output from the modified vector coding technique with traditional time-series segmental angle data is presented. This technique, when applied to single patients can be beneficial to assess the effect of an intervention on the patient-specific inter-segmental coordination pattern with implications to the clinical setting.     

Effect of unilateral load carriage on postures and gait symmetry in ground reaction force during walking

Unilateral load carriage is more hazardous to the musculoskeletal system than bilateral load. The purpose of this study was to examine the effect of such asymmetric carriage on postures and gait symmetry in ground reaction force (GRF) during walking. Kinematics and GRF of 19 adults were recorded while they walked under five load conditions: no load, dumbbell (10 and 20% body weight) held in right and left hand, respectively. After loading, the trunk bent towards the loaded or unloaded side in right- and left-hand trials and under different load weight conditions. The amplitude of trunk bend increased with load, accompanied by decreased stride width, progressively inclined legs towards unloaded side and higher level of asymmetry in medial/lateral GRF (GRFm/l) and free vertical moment GRF (GRFm). The findings indicate the postural adjustment is likely related to the characteristics of load and the task experience and handedness of subject and the unilateral load increases the gait asymmetry in GRFm/l and GRFm.