Effect of centerline-guided walking on gait characteristics in healthy subjects

One of the challenges in collecting ground reaction force (GRF) and moment data for gait analysis is to obtain “good hits” when the subject walks past the forceplates. We examined whether centerline-guided walking would significantly increase the chance of good hits and alter gait characteristics. Thirty-five healthy individuals (age: 37±13 yrs) walked on a walkway with five embedded forceplates at comfortable self-selected speeds under two conditions: (1) free walking and (2) walking along a centerline and avoiding stepping on it. Gait kinematics and GRF were collected using an 8-camera optoelectronic system and five forceplates, respectively. Surface electromyographic (EMG) activity of the rectus femoris, hamstring, gastrocnemius (GAS), and tibialis anterior (TA) were monitored bilaterally. The probability of good hits significantly increased with the centerline-guided walking (p=0.008). Repeated measures MANOVA and follow-up univariate tests revealed no significant differences between the two conditions in any of the spatiotemporal parameters except for a significant increase in step width with centerline walking (p<0.001). Centerline guiding significantly increased peak mediolateral GRF (p<0.001) and hip adduction/abduction and ankle internal/external rotation ranges of motion (p<0.01). In addition, the average EMG activity in GAS and TA during the stance phase significantly increased with the centerline walking (p<0.001). In general, the centerline walking tended to impact women more than men. Centerline-guided walking increases the chance of good hits but biomechanical characteristics of gait in the frontal and transverse planes and EMG activity should be interpreted with caution, especially in women.     

A probabilistic method to estimate gait kinetics in the absence of ground reaction force measurements

Human joint torques during gait are usually computed using inverse dynamics. This method requires a skeletal model, kinematics and measured ground reaction forces and moments (GRFM). Measuring GRFM is however only possible in a controlled environment. This paper introduces a probabilistic method based on probabilistic principal component analysis to estimate the joint torques for healthy gait without measured GRFM. A gait dataset of 23 subjects was obtained containing kinematics, measured GRFM and joint torques from inverse dynamics in order to obtain a probabilistic model. This model was then used to estimate the joint torques of other subjects without measured GRFM. Only kinematics, a skeletal model and timing of gait events are needed. Estimation only takes 0.28 ms per time instant. Using cross-validation, the resulting root mean square estimation errors for the lower-limb joint torques are found to be approximately 0.1 Nm/kg, which is 6–18% of the range of the ground truth joint torques. Estimated joint torque and GRFM errors are up to two times smaller than model-based state-of-the-art methods. Model-free artificial neural networks can achieve lower errors than our method, but are less repeatable, do not contain uncertainty information on the estimates and are difficult to use in situations which are not in the learning set. In contrast, our method performs well in a new situation where the walking speed is higher than in the learning dataset. The method can for example be used to estimate the kinetics during overground walking without force plates, during treadmill walking without (separate) force plates and during ambulatory measurements.     

Algorithms to determine event timing during normal walking using kinematic data

Algorithms to predict heelstrike and toeoff times during normal walking using only kinematic data are presented. The accuracy of these methods was compared with the results obtained using synchronized force platform recordings of two subjects walking at a variety of speeds for a total of 12 trials. Using a 60Hz data collection system, the absolute value errors (AVE) in predicting heelstrike averaged 4.7ms, while the AVE in predicting toeoff times averaged 5.6ms. True average errors (negative for an early prediction) were +1.2ms for both heelstrike and toeoff, indicating that no systematic errors occurred. It was concluded that the proposed algorithms provide an easy and reliable method of determining event times during walking when kinematic data are collected, with a considerable improvement in resolution over visual inspection of video records, and could be utilized in conjunction with any 2-D or 3-D kinematic data collection system.     

Validation of gait event detection by centre of pressure during target stepping in healthy and paretic gait

BackgroundTarget-stepping paradigms are increasingly used to assess and train gait adaptability. Accurate gait-event detection (GED) is key to locating targets relative to the ongoing step cycle as well as measuring foot-placement error. In the current literature GED is either based on kinematics or centre of pressure (CoP), and both have been previously validated with young healthy individuals. However, CoP based GED has not been validated for stroke survivors who demonstrate altered CoP pattern.MethodsYoung healthy adults and individuals affected by stroke stepped to targets on a treadmill, while gait events were measured using three detection methods; verticies of CoP cyclograms, and two kinematic criteria, (1) vertical velocity and position and of the heel marker, (2) anterior velocity and position of the heel and toe marker, were used. The percentage of unmatched gait events was used to determine the success of the GED method. The difference between CoP and kinematic GED methods were tested with two one sample (two-tailed) t-tests against a reference value of zero. Differences between group and paretic and non-paretic leg were tested with a repeated measures ANOVA.ResultsThe kinematic method based on vertical velocity only detected about 80% of foot contact events on the paretic side in stroke survivors while the method on anterior velocity was more successful in both young healthy adults as stroke survivors (3% young healthy and 7% stroke survivors unmatched). Both kinematic methods detected gait events significantly earlier than CoP GED (p < 0.001) except for foot contact in stroke survivors based on the vertical velocity.ConclusionsCoP GED may be more appropriate for gait analyses of SS than kinematic methods; even when walking and varying steps.     

Speed,age, sex,and body mass index provide a rigorous basis for comparing the kinematic and kinetic profiles of the lower extremity during walking

The increased use of gait analysis has raised the need for a better understanding of how walking speed and demographic variations influence asymptomatic gait. Previous analyses mainly reported relationships between subsets of gait features and demographic measures, rendering it difficult to assess whether gait features are affected by walking speed or other demographic measures. The purpose of this study was to conduct a comprehensive analysis of the kinematic and kinetic profiles during ambulation that tests for the effect of walking speed in parallel to the effects of age, sex, and body mass index. This was accomplished by recruiting a population of 121 asymptomatic subjects and analyzing characteristic 3-dimensional kinematic and kinetic features at the ankle, knee, hip, and pelvis during walking trials at slow, normal, and fast speeds. Mixed effects linear regression models were used to identify how each of 78 discrete gait features is affected by variations in walking speed, age, sex, and body mass index. As expected, nearly every feature was associated with variations in walking speed. Several features were also affected by variations in demographic measures, including age affecting sagittal-plane knee kinematics, body mass index affecting sagittal-plane pelvis and hip kinematics, body mass index affecting frontal-plane knee kinematics and kinetics, and sex affecting frontal-plane kinematics at the pelvis, hip, and knee. These results could aid in the design of future studies, as well as clarify how walking speed, age, sex, and body mass index may act as potential confounders in studies with small populations or in populations with insufficient demographic variations for thorough statistical analyses.     

Repeatability of 3D gait kinematics obtained from an electromagnetic tracking system during treadmill locomotion

The purpose of this paper was to describe a technique that enables three-dimensional (3D) gait kinematics to be obtained using an electromagnetic tracking system, and to report the intra-trial, intra-day/inter-tester and inter-day/intra-tester repeatability of kinematic gait data obtained using this technique. Ten able-bodied adults underwent four gait assessments; the same two testers tested each subject independently on two different days. Gait assessments were conducted on a custom-built long-bed treadmill with no metal components between the rollers. Each gait assessment involved familiarisation to treadmill walking, subject anatomical and functional calibration, and a period of steady-state treadmill walking at a self-selected speed. Following data collection, 3D joint kinematics were calculated using the joint coordinate system approach. 3D joint angle waveforms for 10 left and right strides were extracted and temporally normalised for each trial. Intra-trial, intra-day/inter-tester and inter-day/intra-tester repeatability of the temporally normalised kinematic waveforms were quantified using the coefficient of multiple determination (CMD). CMDs for joint kinematics averaged 0.942 intra-trial, 0.849 intra-day/inter-tester and 0.773 inter-day/intra-tester. In general, sagittal plane kinematics were more repeatable than frontal or transverse plane kinematics, and kinematics at the hip were more repeatable than at the knee or ankle. The level of repeatability of kinematic gait data obtained during treadmill walking using this protocol was equal or superior to that reported previously for overground walking using image-based protocols.     

Estimation of unmeasured ground reaction force data based on the oscillatory characteristics of the center of mass during human walking

To enhance the wearability of portable motion-monitoring devices, the size and number of sensors are minimized, but at the expense of quality and quantity of data collected. For example, owing to the size and weight of low-frequency force transducers, most currently available wearable gait measurement systems provide only limited, if any, elements of ground reaction force (GRF) data. To obtain the most GRF information possible with a minimal use of sensors, we propose a GRF estimation method based on biomechanical knowledge of human walking. This includes the dynamics of the center of mass (CoM) during steady human gait resembling the oscillatory behaviors of a mass-spring system. Available measurement data were incorporated into a spring-loaded inverted pendulum with translating pivot. The spring stiffness and simulation parameters were tuned to match, as accurately as possible, the available data and oscillatory characteristics of walking. Our results showed that the model simulation estimated reasonably well the unmeasured GRF. Using the vertical GRF and CoP profile for gait speeds ranging from 0.93 to 1.89 m/s, the anterior-posterior (A-P) GRF was estimated and resulted in an average correlation coefficient of R = 0.982 ± 0.009. Even when the ground contact timing and gait speed information were alone available, our method estimated GRFs resulting in R = 0.969 ± 0.022 for the A-P and R = 0.891 ± 0.101 for the vertical GRFs. This research demonstrates that the biomechanical knowledge of human walking, such as inherited oscillatory characteristics of the CoM, can be used to gain unmeasured information regarding human gait dynamics.     

Ground reaction force estimation using an insole-type pressure mat and joint kinematics during walking

Kinetic analysis of walking requires joint kinematics and ground reaction force (GRF) measurement, which are typically obtained from a force plate. GRF is difficult to measure in certain cases such as slope walking, stair climbing, and track running. Nevertheless, estimating GRF continues to be of great interest for simulating human walking. The purpose of the study was to develop reaction force models placed on the sole of the foot to estimate full GRF when only joint kinematics are provided (Type-I), and to estimate ground contact shear forces when both joint kinematics and foot pressure are provided (Type-II and Type-II-val). The GRF estimation models were attached to a commercial full body skeletal model using the AnyBody Modeling System, which has an inverse dynamics-based optimization solver. The anterior–posterior shear force and medial–lateral shear force could be estimated with approximate accuracies of 6% BW and 2% BW in all three methods, respectively. Vertical force could be estimated in the Type-I model with an accuracy of 13.75% BW. The accuracy of the force estimation was the highest during the mid-single-stance period with an average RMS for errors of 3.10% BW, 1.48% BW, and 7.48% BW for anterior–posterior force, medial–lateral force, and vertical force, respectively. The proposed GRF estimation models could predict full and partial GRF with high accuracy. The design of the contact elements of the proposed model should make it applicable to various activities where installation of a force measurement system is difficult, including track running and treadmill walking.     

Control of ground reaction forces by hindlimb muscles during cat locomotion

It has been proposed that biarticular muscles are primarily responsible for the control of the direction of external forces, as their activation is closely related and highly sensitive to the direction of external forces. This functional role for biarticular muscles has been supported qualitatively by experimental evidence, but has never been tested quantitatively for lack of a mathematical/mechanical formulation of this theory and the difficulty of measuring individual muscle forces during voluntary movements. The purposes of this study were: (1) to define rules for muscular coordination based on the control of external forces; (2) to develop a model of the cat hindlimb that allows for the calculation of the magnitude and direction of the ground reaction forces (GRFs) produced by individual hindlimb muscles; and (3) to test if the coordination of mono- and biarticular cat hindlimb muscles is related to the control of the resultant GRF. We measured the GRF, hindlimb kinematics, selected muscle forces and activations during cat locomotion. Then, the measured muscle forces were used as input to the hindlimb model to compute the muscle-induced GRF. We assume that if activation (and possibly force) increased as the muscle-induced component of GRF approximated the resultant GRF, then that muscle was used by the central nervous system (CNS) to help control the direction of the external GRF. During cat walking, medial gastrocnemius (MG) and plantaris (PL) forces increased with increasing proximity to the GRF, while soleus (SOL) forces and vastus lateralis (VL) activations did not. SOL and VL activation were most strongly related to the vertical and parallel (braking/accelerating) component of the GRF, respectively. We concluded from these results that MG and PL are primarily responsible for the control of the direction of the GRF, while SOL primarily functions as an anti-gravity muscle, and VL as an acceleration/deceleration muscle.     

The effect of a novel gait retraining device on lower limb kinematics and muscle activation in healthy adults

The Re-Link Trainer (RLT) is a modified walking frame with a linkage system designed to apply a non-individualized kinematic constraint to normalize gait trajectory of the left limb. The premise behind the RLT is that a user’s lower limb is constrained into a physiologically normal gait pattern, ideally generating symmetry across gait cycle parameters and kinematics. This pilot study investigated adaptations in the natural gait pattern of healthy adults when using the RLT compared to normal overground walking. Bilateral lower limb kinematic and electromyography data were collected while participants walked overground at a self-selected speed, followed by walking in the RLT. A series of 2-way analyses of variance examined between-limb and between-condition differences. Peak hip extension and knee flexion were reduced bilaterally when walking in the RLT. Left peak hip extension occurred earlier in the gait cycle when using the RLT, but later for the right limb. Peak hip flexion was significantly increased and occurred earlier for the constrained limb, while peak plantarflexion was significantly reduced. Peak knee flexion and plantarflexion in the right limb occurred later when using the RLT. Significant bilateral reductions in peak electromyography amplitude were evident when walking in the RLT, along with a significant shift in when peak muscle activity was occurring. These findings suggest that the RLT does impose a significant constraint, but generates asymmetries in lower limb kinematics and muscle activity patterns. The large interindividual variation suggests users may utilize differing motor strategies to adapt their gait pattern to the imposed constraint.     

A mobile gait monitoring system for abnormal gait diagnosis and rehabilitation: a pilot study for Parkinson disease patients

Conventional gait rehabilitation treatment does not provide quantitative information on abnormal gait kinematics, and the match of the intervention strategy to the underlying clinical presentation may be limited by clinical expertise and experience. Also the effect of rehabilitation treatment may be reduced as the rehabilitation treatment is achieved only in a clinical setting. In this paper, a mobile gait monitoring system (MGMS) is proposed for the diagnosis of abnormal gait and rehabilitation. The proposed MGMS consists of Smart Shoes and a microsignal processor with a touch screen display. It monitors patients' gait by observing the ground reaction force (GRF) and the center of GRF, and analyzes the gait abnormality. Since visual feedback about patients' GRFs and normal GRF patterns are provided by the MGMS, patients can practice the rehabilitation treatment by trying to follow the normal GRF patterns without restriction of time and place. The gait abnormality proposed in this paper is defined by the deviation between the patient's GRFs and normal GRF patterns, which are constructed as GRF bands. The effectiveness of the proposed gait analysis methods with the MGMS has been verified by preliminary trials with patients suffering from gait disorders.     

Quadrupedal locomotion in squirrel monkeys (Cebidae: Saimiri sciureus): a cineradiographic study of limb kinematics and related substrate reaction forces

Quadrupedal locomotion of squirrel monkeys on small-diameter support was analyzed kinematically and kinetically to specify the timing between limb movements and substrate reaction forces. Limb kinematics was studied cineradiographically, and substrate reaction forces were synchronously recorded. Squirrel monkeys resemble most other quadrupedal primates in that they utilize a diagonal sequence/diagonal couplets gait when walking on small branches. This gait pattern and the ratio between limb length and trunk length influence limb kinematics. Proximal pivots of forelimbs and hindlimbs are on the same horizontal plane, thus giving both limbs the same functional length. However, the hindlimbs are anatomically longer than the forelimbs. Therefore, hindlimb joints must be more strongly flexed during the step cycle compared to the forelimb joints. Because the timing of ipsilateral limb movements prevents an increasing amount of forelimb retraction, the forelimb must be more protracted during the initial stance phase. At this posture, gravity acts with long moment arms at proximal forelimb joints. Squirrel monkeys support most of their weight on their hindlimbs. The timing of limb movements and substrate reaction forces shows that the shift of support to the hindlimbs is mainly done to reduce the compressive load on the forelimb. The hypothesis of the posterior weight shift as a dynamic strategy to reduce load on forelimbs, proposed by Reynolds ([1985]) Am. J. Phys. Anthropol. 67:335-349; [1985] Am. J. Phys. Anthropol. 67:351-362), is supported by the high correlation of ratios between forelimb and hindlimb peak vertical forces and the range of motion of shoulder joint and scapula in primates.     

Resonance-based oscillations could describe human gait mechanics under various loading conditions

The oscillatory behavior of the center of mass (CoM) and the corresponding ground reaction force (GRF) of human gait for various gait speeds can be accurately described in terms of resonance using a spring–mass bipedal model. Resonance is a mechanical phenomenon that reflects the maximum responsiveness and energetic efficiency of a system. To use resonance to describe human gait, we need to investigate whether resonant mechanics is a common property under multiple walking conditions. Body mass and leg stiffness are determinants of resonance; thus, in this study, we investigated the following questions: (1) whether the estimated leg stiffness increased with inertia, (2) whether a resonance-based CoM oscillation could be sustained during a change in the stiffness, and (3) whether these relationships were consistently observed for different walking speeds. Seven healthy young subjects participated in over-ground walking trials at three different gait speeds with and without a 25-kg backpack. We measured the GRFs and the joint kinematics using three force platforms and a motion capture system. The leg stiffness was incorporated using a stiffness parameter in a compliant bipedal model that best fitted the empirical GRF data. The results showed that the leg stiffness increased with the load such that the resonance-based oscillatory behavior of the CoM was maintained for a given gait speed. The results imply that the resonance-based oscillation of the CoM is a consistent gait property and that resonant mechanics may be useful for modeling human gait.     

Using computed muscle control to generate forward dynamic simulations of human walking from experimental data

The objective of this study was to develop an efficient methodology for generating muscle-actuated simulations of human walking that closely reproduce experimental measures of kinematics and ground reaction forces. We first introduce a residual elimination algorithm (REA) to compute pelvis and low back kinematic trajectories that ensure consistency between whole-body dynamics and measured ground reactions. We then use a computed muscle control (CMC) algorithm to vary muscle excitations to track experimental joint kinematics within a forward dynamic simulation. CMC explicitly accounts for delays in muscle force production resulting from activation and contraction dynamics while using a general static optimization framework to resolve muscle redundancy. CMC was used to compute muscle excitation patterns that drove a 21-degrees-of-freedom, 92 muscle model to track experimental gait data of 10 healthy young adults. Simulated joint kinematics closely tracked experimental quantities (mean root-mean-squared errors generally less than 1 degrees), and the time histories of muscle activations were similar to electromyographic recordings. A simulation of a half-cycle of gait could be generated using approximately 30 min of computer processing time. The speed and accuracy of REA and CMC make it practical to generate subject-specific simulations of gait.     

Sampling frequencies and measurement error for linear and temporal gait parameters in primate locomotion

Quantitative analyses of animal motion are increasingly easy to conduct using simple video equipment and relatively inexpensive software packages. With careful use, such analytical tools have the potential to quantify differences in movement between individuals or species and to allow insights into the behavioral consequences of morphological differences between taxa. However, as with any other type of measurement, there are errors associated with kinematic measurements. Because normative kinematic data on human and nonhuman primate locomotion are used to model aspects of gait of fossil hominins, errors in the extant data influence the accuracy of fossil gait reconstructions. The principal goal of this paper is to illustrate the effect of camera speeds (frame rates) on kinematic measurement errors, and to demonstrate how these errors vary with subject size, movement velocity, and sample size. Kinematic data for human walking and running (240 Hz), as well as data for primate quadrupedal walking and running (180 Hz) were used as inputs for a simulation of the measurement errors associated with various linear and temporal kinematic variables. Measurement errors were shown to increase as camera speed, subject body size, and interval duration all decrease, and as movement velocity increases. These results have implications for the methods used to calculate subject velocity and suggest that using a moving marker to measure the linear displacements of the body is preferable to the use of a stationary marker. Finally, while slower camera speeds will always result in higher measurement errors than do faster camera speeds, this effect can be moderated to some extent by collecting sufficiently large samples of data.     

Rotational and translational movement features of the pelvis and thorax during adult human locomotion

The kinematics of the pelvis and thorax are important in gait studies since their movement patterns are closely related to gait efficiency and 'smoothness' of locomotion. The purpose of this study was to identify features of normal gait patterns for later comparisons with pathological and developmental gait patterns. A two camera SELSPOT system interfaced with an HP1000 minicomputer was used to obtain three-dimensional kinematic/temporal data for the pelvis and thorax. Data from treadmill walking of eight adults were used for within subject (at different speeds) analyses. The analyses revealed a very complex pattern with a set of breakpoints which was consistent over all subjects. Some features were invariant over a range of walking speeds although the total range of motion changed considerably.     

Do highly trained monkeys walk like humans? A kinematic study of bipedal locomotion in bipedally trained Japanese macaques

In this study, we examined the kinematics of bipedal walking in macaque monkeys that have been highly trained to stand and walk bipedally, and compared them to the kinematics of bipedal walking in ordinary macaques. The results revealed that the trained macaques walked with longer and less frequent strides than ordinary subjects. In addition, they appear to have used inverted pendulum mechanics during bipedal walking, which resulted in an efficient exchange of potential and kinetic energy. These gait characteristics resulted from the relatively more extended hindlimb joints of the trained macaques. By contrast, the body of the ordinary macaques translated downward during the single-limb stance phase due to more flexed hindlimb joints. This resulted in almost in-phase fluctuations of potential and kinetic energy, which indicated that energy transformation was less efficient in the ordinary macaques. The findings provide two insights into the early stage of the evolution of human bipedalism. First, the finding that training considerably improved bipedal walking a posteriori may explain why the very first bipeds that might not yet have been morphologically adapted to bipedal walking continued to walk bipedally. The evolutionary transition from quadrupedalism to bipedalism might not be as difficult as has been envisioned. In addition, the finding that macaques, which are phylogenetically distant from humans and in which bipedal walking is unlike human walking, could develop humanlike gait characteristics with training, provides strong support for the commonly held but unproven idea that the characteristics of the human gait are advantageous to human bipedalism.