Self-Selected walking speed increases when individuals are aware of being recorded

BackgroundTypical gait data collections consist of discrete walking trials where participants are aware when data are being recorded. Anecdotally, some investigators have reported that participants often walk differently between trials or before or after data collection compared to when they know they are being recorded. In addition, walking speed, which affects a number of gait variables, is known to be different when individuals complete discrete and continuous walking trials.Research questionThe purpose of this study was to determine whether changes in walking speed occurred as a result of participants being aware, versus unaware that data were being recorded, during both discrete and continuous walking trials.MethodsKinematic data were collected for twenty two individuals walking continuous trials or discrete trials, while they were both aware and unaware of being recorded. Comparisons of walking speeds were made between groups (continuous walking; discrete trials) and awareness of being recorded (aware; unaware) using a two way ANOVA.ResultsThe results indicated that participants walked significantly faster during discrete trials when they were aware that data were being recorded compared to when they were unaware. However, when they walked continuously their walking speed was not affected by their awareness.SignificanceThe results suggest that awareness of data collection, and the type of protocol used during data collection, affect an individual’s walking speed during gait analysis. Therefore, care should be taken when determining gait analysis protocols where variables are sensitive to walking speeds.     

The influence of walking speed on mechanical joint power during gait

To study how walking speeds influence joint power and determine normal mechanical power output by the muscles about the hip, knee and ankle joints, we investigated ten healthy children in our gait laboratory. We found that walking speed does influence the mechanical work at the hip, knee and ankle. The work generated at the knee had the greatest increase with speed. The work at the hip was also sensitive to speed changes but to a lesser degree. Surprisingly, the joint power at the ankle remained constant despite increasing speed. This also supports the theory that the role of the calf muscle in propulsion is related to walking speed.     

Speed related changes in muscle activity from normal to very slow walking speeds

The study of neuromuscular activity at very slow walking speeds may lead to a better understanding of the mechanisms underlying speed regulation during walking, and may aid the interpretation of gait data in patients who walk slowly. Extreme reductions in walking speed will cause changes in locomotor task demands that may eventually result in modifications of the patterning of muscle activity that underlies walking. The aim of the present study was to investigate patterns of lower limb muscle activity during very slow walking (<0.28 m s⁻¹), and to study the neuromuscular gain functions that reflect the phase dependent effects of walking speed on electromyographic (EMG) amplitude. Nine healthy young adults walked at seven different walking speeds (1.39, 0.83, 0.28, 0.22, 0.17, 0.11, and 0.06 m s⁻¹) while EMG was recorded from eight lower extremity muscles. Results showed that the phasing of muscle activity remained relatively stable over walking speeds despite substantial changes in its amplitude. However, between 1.39 and 0.28 m s⁻¹, epochs of Rectus femoris, Biceps femoris and Tibialis anterior activities were found that were typical for specific speed ranges. When walking speed decreased further to almost standing still (0.06 m s⁻¹), negative gain values were found in Peroneus longus during midstance and Rectus femoris in late swing, indicating the emergence of new bursts of activity with decreasing walking speed. It is proposed that these extra activities may be attributed to increased demands on postural stability, and the altered dynamics of the swinging limb at very slow speeds.     

Comparison of measurement protocols to estimate preferred walking speed between sites

BackgroundWalking speed influences a variety of typical outcome measures in gait analysis. Many researchers use a participant’s preferred walking speed (PWS) during gait analysis with a goal of trying to capture how a participant would typically walk. However, the best practices for estimating PWS and the impact of laboratory size and walk distance are still unclear.Research questionIs measured PWS consistent across different distances and between two laboratory sites?MethodsParticipants walked overground at a “comfortable speed” for six different conditions with either dynamic (4, 6, 10, and 400 m) or static (4 and 10 m) starts and stops at two different data collection sites. Repeated measures ANOVA with Bonferroni corrections were used to test for differences between conditions and sites.ResultsParticipants walked significantly faster in the 4, 6, and 10 m dynamic conditions than in the 400 m condition. On average, participants walked slower in the static trials than the dynamic trials of the same distance. There was a significant interaction of lab and condition and so results were examined within each lab. Across both labs, we found that the 4 and 10 m dynamic conditions were not different than the 6 m dynamic condition at both sites, while other tests did not provide consistent results at both sites.SignificanceWe recommend researchers use a 6 m distance with acceleration and deceleration zones to reliably test for PWS across different laboratories. Given some of the differences found between conditions that varied by site, we also emphasize the need to report the test environment and methods used to estimate PWS in all future studies so that the methods can be replicated between studies.     

The effect of walking speed on gait kinematics and kinetics after endoprosthetic knee replacement following bone tumor resection

Gait function is one of the most important components of functional outcome evaluation in patients with a tumor around the knee. In addition to walking at a preferred speed, the patients might be sometimes required to walk fast in daily life (e.g., schooling and working) because the major types of bone tumors often occur in adolescence and young adults. Therefore, recovering the ability to walk fast would increase the quality of life of these patients. To clarify which parts of the lower limb are exerted while walking fast, we investigated the kinematic and kinetic changes during fast walking in patients who underwent endoprosthetic knee replacement after bone tumor resection. Laboratory-based gait analysis was performed on eight patients who had undergone endoprosthetic knee replacement following resection of a tumor around the knee. Patients walked at a preferred and faster speed, and the gait parameters were compared between the two walking speeds for each leg. To increase walking speed, patients tended to rely on the bilateral hip, ankle, and contralateral knee to generate additional power. Kinetic analysis showed that involved-side vertical body support was not significantly increased during late stance to increase walking speed, which was associated with a small increase in ankle plantarflexion moment and concentric power. These results suggest to patients after knee reconstruction how to effectively increase their walking speed or redistribute the mechanical load on the muscles and joints to prevent excessive stress on the lower limbs.     

The effect of walking speed on gait kinematics and kinetics after endoprosthetic knee replacement following bone tumor resection

Gait function is one of the most important components of functional outcome evaluation in patients with a tumor around the knee. In addition to walking at a preferred speed, the patients might be sometimes required to walk fast in daily life (e.g., schooling and working) because the major types of bone tumors often occur in adolescence and young adults. Therefore, recovering the ability to walk fast would increase the quality of life of these patients. To clarify which parts of the lower limb are exerted while walking fast, we investigated the kinematic and kinetic changes during fast walking in patients who underwent endoprosthetic knee replacement after bone tumor resection. Laboratory-based gait analysis was performed on eight patients who had undergone endoprosthetic knee replacement following resection of a tumor around the knee. Patients walked at a preferred and faster speed, and the gait parameters were compared between the two walking speeds for each leg. To increase walking speed, patients tended to rely on the bilateral hip, ankle, and contralateral knee to generate additional power. Kinetic analysis showed that involved-side vertical body support was not significantly increased during late stance to increase walking speed, which was associated with a small increase in ankle plantarflexion moment and concentric power. These results suggest to patients after knee reconstruction how to effectively increase their walking speed or redistribute the mechanical load on the muscles and joints to prevent excessive stress on the lower limbs.     

Outcome-dependent effects of walking speed and age on quantitative and qualitative gait measures

BackgroundWalking speed predicts many clinical outcomes in old age. However, a comprehensive assessment of how walking speed affects accelerometer based quantitative and qualitative gait measures in younger and older adults is lacking.Research questionWhat is the relationship between walking speed and quantitative and qualitative gait outcomes in younger and older adults?MethodsYounger (n = 27, age: 21.6) and older participants (n = 27, age: 69.5) completed 340 steps on a treadmill at speeds of 0.70 to a maximum of 1.75 m·s^-1. We used generalized additive mixed models to determine the relationship between walking speed and quantitative (stride length, stride time, stride frequency and their variability) and qualitative (stride regularity, stability, smoothness, symmetry, synchronization, predictability) gait measures extracted from trunk accelerations.ResultsThe type of relationship between walking speed and the majority of gait measures (quantitative and qualitative) was characterized as logarithmic, with more prominent speed-effects at speeds below 1.20 m·s⁻¹. Changes in quantitative measures included shorter strides, longer stride times, and a lower stride frequency, with more variability at lower speeds independent of age. For qualitative measures, we found a decrease in gait symmetry, stability and regularity in all directions with decreasing speeds, a decrease in gait predictability (Vertical, V, anterior-posterior, AP) and stronger gait synchronization (AP-mediolateral, ML, AP-V), and direction dependent effects of gait smoothness, which decreased in V direction, but increased in AP and ML directions with decreasing speeds. We found outcome-dependent effects of age on the quantitative and qualitative gait measures, with either no differences between age-groups, age-related differences that existed regardless of speed, and age-related differences in the type of relationship with walking speed.SignificanceThe relationship between walking speed and quantitative and qualitative gait measures, and the effects of age on this relationship, depends on the type of gait measure studied.     

Kinematic changes in patients with severe knee osteoarthritis are a result of reduced walking speed rather than disease severity

BackgroundKinematic changes in patients with knee osteoarthritis (OA) have been extensively studied. Concerns have been raised whether the measured spatiotemporal and kinematic alterations are associated with disease progression or merely a result of reduced walking speed.Research question: The purpose of this study was to investigate the effect of walking speed on kinematic parameters in patients with knee OA using statistical parametric mapping (SPM).MethodsTwenty-three patients with unilateral knee OA scheduled for a total knee replacement and 28 age matched control subjects were included in this study. Spatiotemporal parameters and sagittal plane kinematics were measured in the hip, knee, and ankle using the inertial sensors system RehaGait® while walking at a self-selected normal (patients and controls) and slow walking speed (controls) for a distance of 20 m. Gait parameters were compared between groups for self-selected walking speed and for matched walking speed using SPM with independent sample t tests.ResultsAt self-selected walking speed, patients had significantly lower knee flexion during stance (maximum difference, -6.8°) and during swing (-11.0°), as well as higher ankle dorsiflexion during stance phase (+12.5°) and lower peak hip extension at the end of stance compared to controls (+4.2°). At matched speed, there were no significant differences in joint kinematics between groups.SignificanceDifferences in sagittal plane gait kinematics between patients with knee OA and asymptomatic controls appear to be mainly a result of reduced walking speed. These results emphasize the importance of considering walking speed in research on gait kinematics in patients with knee OA and in clinical trials using gait parameters as outcome measures.     

The impact of walking speed on the kinetic behaviour of different foot joints

BackgroundThe foot and ankle complex consists of multiple joints which have been hypothesized to fulfill a significant role in the lower limb kinetic chain during human locomotion. Walking speed is known to affect the lower limb kinetic chain function. Yet, this effect still has to be investigated throughout multiple joints of the foot and ankle complex.Research questionWhat is the effect of walking speed on the kinetic behaviour of multiple joints of the foot and ankle complex?MethodsThis observational cross-sectional study investigated 15 asymptomatic male subjects. A three-and four-segment kinetic foot model was used to calculate power output and mechanical work during normal and high walking speed. One-dimensional Statistical Parametric Mapping (1D-SPM) linear regression was performed to examine the relationship between walking speed and kinetic data. Effect size calculations (Cohen’s D) were included to quantify the amount of effect that walking speed has on power output and mechanical work in multiple foot joints.ResultsThree-segment kinetic measurements showed a significant positive correlation between walking speed and power output in the ankle (p = 0.003) and first metatarsophalangeal joint (p = 0.0007). Peak power generation increased in the ankle (d = 1.59), chopart (d = 1.51) and first metatarsophalangeal (d = 1.25) joints during high-speed walking. The three joints combined produced net +0.097 J/kg in normal and +0.201 J/kg in high-speed walking. Four-segment kinetic measurements showed a significant positive correlation between walking speed and power output at the ankle (p = 0.036), chopart (p = 0.0001), lisfranc (p < 0.0001) and first metatarsophalangeal (p = 0.0063) joints. Peak power generation increased in the ankle (d = 1.32), chopart (d = 1.27), lisfranc (d = 1.22) and first metatarsophalangeal (d = 1.47) joints during high-speed walking. Four joints combined produced net +0.162 J/kg in normal and +0.261 J/kg in high-speed walking.SignificanceThese results add additional insight into foot function during increased walking speed.     

Concurrent validity of the GAITRite electronic walkway and the 10-m walk test for measurement of walking speed after stroke

Background: Walking speed is used to assess functional status, predict recovery, prescribe exercise, and track functional progress after stroke. Determining concurrent validity ensures that results from different tests of walking speed can be compared or used interchangeably. The GAITRite electronic walkway and the 10-m walk test (10MWT) are popular measurement tools of walking speed in the laboratory and in clinical settings, respectively.Research question: Do walking speeds in chronic stroke survivors measured with the 10-m walk test and GAITRite electronic walkway demonstrate concurrent validity?Methods: 77 participants with chronic stroke performed four trials of 10MWT and four trials of GAITRite—two trials at comfortable walking speed and two trials at maximal walking speed. Intraclass correlations [ICC (3,1), absolute agreement] and Bland-Altman plots were used to assess the relationship between gait speed from these two measures.Results: Walking speed showed poor to good absolute agreement between 10MWT and GAITRite for comfortable walking speed [ICC: 0.77 (95% CI: 0.46, 0.89; P < 0.001)] and excellent absolute agreement for maximal walking speed [ICC: 0.94 (95% CI: 0.91, 0.96; P < 0.001)]. Mean difference value (systematic bias) was different from 0 for comfortable walking [10MWT was faster; P < 0.001 (95% CI: 0.05, 0.10)] but not for maximal walking [P = 0.16 (95% CI: −0.01, 0.04)]. Limits of agreement were broad (comfortable walking speed, 0.43; maximal walking speed, 0.37), and there was proportional bias at both speeds whereby participants who walked faster tended to have a faster walking speed during 10MWT vs. GAITRite (comfortable walking speed, R² = 0.22, P < 0.001; maximal walking speed, R² = 0.08, P = 0.01).Significance: Systematic bias, proportional bias, and broad limits of agreement suggest that caution should be used when comparing walking speeds from 10MWT and GAITRite. It may not be appropriate to use them interchangeably. Conducting 10MWT and GAITRite tests at maximal walking speeds may allow more accurate comparisons between measures.     

Effectiveness of an innovative hip energy storage walking orthosis for improving paraplegic walking: A pilot randomized controlled study

BackgroundThe high energy cost of paraplegic walking using a reciprocating gait orthosis (RGO) is attributed to limited hip motion and excessive upper limb loading for support. To address the limitation, we designed the hip energy storage walking orthosis (HESWO) which uses a spring assembly on the pelvic shell to store energy from the movements of the healthy upper limbs and flexion-extension of the lumbar spine and hip and returns this energy to lift the pelvis and lower limb to assist with the swing and stance components of a stride. Our aim was to evaluate gait and energy cost indices for the HESWO compared to the RGO in patients with paraplegia.MethodsThe cross-over design was used in the pilot study. Twelve patients with a complete T4-L5 chronic spinal cord injury underwent gait training using the HESWO and RGO. Gait performance (continuous walking distance, as well as the maximum and comfortable walking speeds) and energy expenditure (at a walking speed of 3.3 m/min on a treadmill) were measured at the end of the 4-week training session.ResultsCompared to the RGO, the HESWO increased continuous walking distance by 24.7% (P < 0.05), maximum walking speed by 20.4% (P < 0.05) and the comfortable walking speed by 15.3% (P < 0.05), as well as decreasing energy expenditure by 13.9% (P < 0.05).ConclusionOur preliminary results provide support for the use of the HESWO as an alternative support for paraplegic walking.     

Time-integrated propulsive and braking impulses do not depend on walking speed

BackgroundEnhancing propulsion during walking is often a focus in physical therapy for those with impaired gait. However, there is no consensus in the literature for assessing braking and propulsion. Both are typically measured from the anterior-posterior ground reaction force (AP-GRF). While normalization of AP-GRF force by bodyweight is commonly done in the analysis, different methods for AP-GRF time axis normalization are used.Research questionDoes walking speed affect propulsion and/or braking, and how do different methods for calculating propulsion and braking impact the conclusion, in both healthy adults and those with lower limb impairment?MethodsWe investigated three different analysis methods for assessing propulsion. 1. BW-TimeIntegration: Bodyweight (BW) normalized time integration of AP-GRF (units of BWs). 2. BW-%StanceIntegration: BW normalized AP-GRF is resampled to percent stance phase prior to integration (units of BW%Stance). 3. BW-Peak: BW normalized peak force (units of BW). We applied these methods to two data sets. One data set included AP-GRFs from trials of slow, self-selected, and fast walking speeds for 203 healthy controls (HCs); a second data set included subjects with lower limb orthopedic injuries.ResultsUsing the BW-TimeIntegration method, we found no effect of walking speed on propulsion for HCs. Time integration over the longer stance phase of slower walking balanced the lower magnitude AP-GRFs of slower walking, resulting in a time-integrated impulse that was the same regardless of walking speed. In contrast, the other two methods that are not time integration methods found that propulsion increased with walking speed. Similarly, in the gait pathology data set, differences in results were found depending on the analysis method used.SignificanceFor many gait studies concerning propulsion and/or braking, the impulse measure used should be related to the body’s change of momentum, necessitating an analysis method with a time integration of the AP-GRF.     

Words matter: instructions dictate “self-selected” walking speed in young adults

BackgroundVariability in gait speed is influenced by age and health status. However, no study has investigated the effects of different instructions on gait speed.Research questionThis study investigated how walking prompts contributed to variability in gait speed.MethodsParticipants walked on a pressurized walkway. Gait speed variability was assessed using multilevel modeling.Results61% of the variance in gait speed was due to instruction, while 14% was due to individual differences.SignificanceReference values for gait speed across a number of prompts will be highly useful for assessing gait performance in young adults. Further, the instruction given produces a large amount of variability in selected walking speed. This finding urges researchers to maintain consistency when delivering walking instructions.     

Causal relationship between spatiotemporal parameters of walking and the locomotor rehabilitation index in healthy people

BackgroundWalking speed is a functional vital sign affecting mechanical parameters individually. Further, there is a tendency for pathological gait to occur at slower speeds, which does not always allow for an adequate comparison with normal gait. Therefore, recognizing the influence of spatiotemporal adjustments on healthy gait can broaden our understanding of the applicability of gait quality markers.Research questionThis study aimed to identify the causal relationship between the stride length–frequency walking ratio index (R_SL/SF) at the self-selected walking speed (SSWS) and optimal walking speed (OWS) and the locomotor rehabilitation index (LRI) in healthy adults.Materials and methodsHealthy adults (n = 68) of both sexes aged 20–59 years were included in this study. The SSWS was determined using a 30-m walkway. The OWS and LRI were predicted by equations proposed in the literature. The volunteers walked on the treadmill at speeds corresponding to the OWS and SSWS in two bouts of 60 s each, with a break in between. The spatiotemporal parameters were recorded using a high-speed digital video camera, digitalized, and mathematically processed. Multiple linear regression was applied using the forced regression method.ResultsSignificant correlations were found between the LRI and R_SL/SF at the SSWS (R = 0.397; p < 0.001) and OWS (R = 0.266; p = 0.014). The regression model showed that 16 % of the variability in the LRI was attributable to the R_SL/SF variability at the SSWS. The average and 95 % confidence interval LRI were 94.7 % (91.6 %–97.8 %).ConclusionThe LRI average is around 95 % for healthy and young adults and the R_SL/SF explained just 16 % of the variance in LRI.     

A prediction method of speed-dependent walking patterns for healthy individuals

BackgroundGait speed is one of the main biomechanical determinants of human movement patterns. However, in clinical gait analysis, the effect of gait speed is generally not considered, and people with disabilities are usually compared with able-bodied individuals even though disabled people tend to walk slower.Research questionsThis study proposes a simple way to predict the gait pattern of healthy individuals at a specific speed.MethodsThe method consists of creating a reference database for a range of gait speeds, and the gait-pattern prediction is implemented as follows: 1) the gait cycle is discretized from 0 to 100% for each variable, 2) a first or second-order polynomial is used to adjust the values of the reference dataset versus the corresponding gait speeds for each instant of the gait cycle to obtain the parameters of the regression, and 3) these regression parameters are then used to predict the new values of the gait pattern at any specific speed. Twenty-four healthy adults walked on the treadmill at eight different gait speeds, where the gait pattern was obtained by a 3D motion capture system and an instrumented treadmill.ResultsOverall, the predicted data presented good agreement with the experimental data for the joint angles and joint moments.SignificanceThese results demonstrated that the proposed prediction method can be used to generate more unbiased reference data for clinical gait analysis and might be suitably applied to other speed-dependent human movement patterns.     

Effects of walking speed on asymmetry and bilateral coordination of gait

The mechanisms regulating the bilateral coordination of gait in humans are largely unknown. Our objective was to study how bilateral coordination changes as a result of gait speed modifications during over ground walking. 15 young adults wore force sensitive insoles that measured vertical forces used to determine the timing of the gait cycle events under three walking conditions (i.e., usual-walking, fast and slow). Ground reaction force impact (GRFI) associated with heel-strikes was also quantified, representing the potential contribution of sensory feedback to the regulation of gait. Gait asymmetry (GA) was quantified based on the differences between right and left swing times and the bilateral coordination of gait was assessed using the phase coordination index (PCI), a metric that quantifies the consistency and accuracy of the anti-phase stepping pattern. GA was preserved in the three different gait speeds. PCI was higher (reduced coordination) in the slow gait condition, compared to usual-walking (3.51% vs. 2.47%, respectively, p = 0.002), but was not significantly affected in the fast condition. GRFI values were lower in the slow walking as compared to usual-walking and higher in the fast walking condition (p < 0.001). Stepwise regression revealed that slow gait related changes in PCI were not associated with the slow gait related changes in GRFI. The present findings suggest that left–right anti-phase stepping is similar in normal and fast walking, but altered during slow walking. This behavior might reflect a relative increase in attention resources required to regulate a slow gait speed, consistent with the possibility that cortical function and supraspinal input influences the bilateral coordination of gait.     

Gait Profile Score in able-bodied and post-stroke individuals adjusted for the effect of gait speed

Background: The Gait Profile Score (GPS) measures the quality of an individual’s walking by calculating the difference between the kinematic pattern and the average walking pattern of healthy individuals.Research questions: The purposes of this study were to quantify the effect of speed on the GPS and to determine whether the prediction of gait patterns at a specific speed would make the GPS outcome insensitive to gait speed in the evaluation of post-stroke individuals.Methods: The GPS was calculated for able-bodied individuals walking at different speeds and for the comparison of post-stroke individuals with able-bodied individuals using the original experimental data (standard GPS) and the predicted gait patterns at a given speed (GPS velocity, GPS^v). We employed standard gait analysis for data collection of the subjects. Sixteen participants with a stroke history were recruited for the post-stroke group, and 15 age-matched, able-bodied participants formed the control group.Results: Gait speed significantly affects the GPS and the method to predict the gait patterns at any speed is able to mitigate the effects of gait speed on the GPS. Overall, the gap between the GPS and GPS^v values across the post-stroke individuals was small (0.5° on average, range from 0.0° to 1.4°) and not statistically significant. However, there was a significant negative linear relationship in the absolute difference between the GPS and GPS^v values for the participants of the post-stroke group with gait speed, indicating that a larger difference between the speeds of the post-stroke participant and the reference dataset resulted in a larger difference between the GPS and GPS^v.Significance: The modified version of the GPS, the GPS^v, is effective in reducing the impact of gait speed on GPS; however, the observed difference between the two methods was only around 1° for the slowest individuals in comparison to the reference dataset.     

The gait profile score characterises walking performance impairments in young stroke survivors

BackgroundThe Gait Profile Score (GPS) provides a composite measure of the quality of joint movement during walking, but the relationship between this measure and metabolic cost, temporal (e.g. walking speed) and spatial (e.g. stride length) parameters in stroke survivors has not been reported.Research Question: The aims of this study were to compare the GPS (paretic, non-paretic, and overall score) of young stroke survivors to the healthy able-bodied control and determine the relationship between the GPS and metabolic cost, temporal (walking speed, stance time asymmetry) and spatial (stride length, stride width, step length asymmetry) parameters in young stroke survivors to understand whether the quality of walking affects walking performance in stroke survivors.MethodsThirty-nine young stroke survivors aged between 18 and 65years and 15 healthy age-matched able-bodied controls were recruited from six hospital sites in Wales, UK. Joint range of motion at the pelvis, hip, knee and ankle, and temporal and spatial parameters were measured during walking on level ground at self-selected speed with calculation of the Gait Variable Score and then the GPS.ResultsGPS for the paretic leg (9.40° (8.60–10.21) p < 0.001), non-paretic leg (11.42° (10.20–12.63) p < 0.001) and overall score (11.18° (10.26–12.09) p < 0.001)) for stroke survivors were significantly higher than the control (4.25° (3.40–5.10), 5.92° (5.11 (6.73)). All parameters with the exception of step length symmetry ratio correlated moderate to highly with the GPS for the paretic, non-paretic, and/or overall score (ρ = <−0.732 (p < 0.001)).SignificanceThe quality of joint movement during walking measured via the GPS is directly related to the speed and efficiency of walking, temporal (stance time symmetry) and spatial (stride length, stride width) parameters in young stroke survivors.     

The influence of walking speed on gait parameters in healthy people and in patients with osteoarthritis

It is difficult to identify objective parameters for assessing the joint function when evaluating the outcome of orthopaedic procedures, especially endoprosthetic replacement. Spatial and temporal parameters of gait have clinical relevance in the assessment of motor pathologies, particularly in orthopaedics. However, the influence of gait speed on these biomechanical parameters has been difficult to be taken into consideration so far. The objective of the present study was to analyse the impact of gait speed on gait parameters and to set a standard walking speed for patients with osteoarthritis by means of a special treadmill control mechanism. The second objective is to compare the gait patterns in patients with unilateral osteoarthritis of the hip joint or of the knee joint to the gait pattern of healthy control subjects. A total of 20 patients with severe unilateral osteoarthritis of the hip, 20 patients with severe unilateral osteoarthritis of the knee and 20 healthy elderly subjects without any history of lower extremity joint pathology were investigated at four different gait speeds. The gait analysis equipment used consisted of an infinitely adjustable force-instrumented treadmill and an ultrasound-based motion analyser system with electromyography. Our data suggest that most of the biomechanical parameters depend on gait speed. The highest gait speed that all our patients with severe osteoarthritis were suitable with, without pain and loss of coordination, was 2.00 km/h. Our findings indicate that the changes in gait parameters may occur in patients with unilateral osteoarthritis of the hip joint or the knee joint compared to the gait pattern of healthy control subjects. Hip joint or knee joint degeneration was compensated for in part by the pelvis and other joints in the lower limb. Reduced motion of the hip joint or knee joint leads to an increased pelvic motion, which should affect the natural mobility of the lumbar spine and cause pain in the lumbar region of the spine because of their kinematic interaction.