Walking Speed Variability Research Articles

LocateMe

Fine-grained localization is extremely important to accurately locate a user indoors. Although innovative solutions have already been proposed, there is no solution that is universally accepted, easily implemented, user centric, and, most importantly, works in the absence of GSM coverage or WiFi availability. The advent of sensor rich smartphones has paved a way to develop a solution that can cater to these requirements. By employing a smartphone's built-in magnetic field sensor, magnetic signatures were collected inside buildings. These signatures displayed a uniqueness in their patterns due to the presence of different kinds of pillars, doors, elevators, etc., that consist of ferromagnetic materials like steel or iron. We theoretically analyze the cause of this uniqueness and then present an indoor localization solution by classifying signatures based on their patterns. However, to account for user walking speed variations so as to provide an application usable to a variety of users, we follow a dynamic time-warping-based approach that is known to work on similar signals irrespective of their variations in the time axis. Our approach resulted in localization distances of approximately 2m--6m with accuracies between 80--100% implying that it is sufficient to walk short distances across hallways to be located by the smartphone. The implementation of the application on different smartphones yielded response times of less than five secs, thereby validating the feasibility of our approach and making it a viable solution.

Self-paced versus fixed speed treadmill walking

Instrumented treadmills are increasingly used in gait research, although the imposed walking speed is suggested to affect gait performance. A feedback-controlled treadmill that allows subjects to walk at their preferred speed, i.e. functioning in a self-paced (SP) mode, might be an attractive alternative, but could disturb gait through accelerations of the belt. We compared SP with fixed speed (FS) treadmill walking, and also considered various feedback modes. Nineteen healthy subjects walked on a dual-belt instrumented treadmill. Spatio-temporal, kinematic and kinetic gait parameters were derived from both the average stride patterns and stride-to-stride variability. For 15 out of 70 parameters significant differences were found between SP and FS. These differences were smaller than 1cm, 1°, 0.2Nm and 0.2W/kg for respectively stride length and width, joint kinematics, moments and powers. Since this is well within the normal stride variability, these differences were not considered to be clinically relevant, indicating that SP walking is not notably affected by belt accelerations. The long-term components of walking speed variability increased during SP walking (43%, p<0.01), suggesting that SP allows for more natural stride variability. Differences between SP feedback modes were predominantly found in the timescales of walking speed variability, while the gait pattern was similar between modes. Overall, the lack of clinically significant differences in gait pattern suggests that SP walking is a suitable alternative to fixed speed treadmill walking in gait analysis.

Gait recognition via optimally interpolated deformable contours

Gait as a biometric was inspired by the ability to recognize an acquaintance by his manner of walking even when seen at a distance. In this paper, we describe a novel Fourier descriptor based gait recognition method that models the periodic deformation of human contours. A new measure of similarity using the product of Fourier coefficients is proposed as a distance measure between closed curves. In order to maximize the similarity between subsequent closed curves, the assembly of contours in gait cycle is circularly shifted by a circular permutation matrix. Subsequently, an element-wise frame interpolation is correspondingly applied to produce length invariant gait signatures. The experiments on OU-ISIR gait database and CASIA gait database reveal promising recognition accuracy. The element-wise frame interpolation method is able to preserve temporal information even when the gait cycles change, and therefore offers a better robustness to slight variation in walking speed.

Temperature and starvation effects on food exploitation by Argentine ants and native ants in New Zealand

AbstractThe abundance and distribution of an invasive species is influenced by its relative ability to find resources under a variety of conditions. We examined the exploitative ability of the Argentine ant (Linepithema humile (Mayr)), in comparison with two common New Zealand ant species Monomorium antarcticum (Fr. Smith) and Prolasius advenus (Hymenoptera: Formicidae) (Fr. Smith), using maze trials under different temperature and starvation regimes. Our results showed temperature significantly affected the mean time to discover food resources, but different species responded differently to changes in temperature. A change in temperature from 23°C to 13°C resulted in an approximately 8‐fold increase in the time to discover food for native P. advenus, but discovery times remained relatively similar for invasive Argentine ants. Starvation did not significantly influence the ability of species to find food. Argentine ants consistently located and recruited to food faster than the native species. We examined for variation in walking speed under the experimental conditions as a mechanism for our results. The results revealed Argentine ants and P. advenus to have similar walking speeds at each temperature‐starvation treatment and both were faster than M. antarcticum. However, Argentine ants had rates of turning or returning to the nest that were lower than the native species. This result suggests that Argentine ants show greater ‘exploratory willingness’ or ‘novelty seeking’ behaviour. Our results suggest that Argentine ants are able to discovery and exploit resources more efficiently than these native species under a wide spectrum of environmental and physiological conditions. Such relative efficiencies have likely contributed to the success of this invader.

Walking during body-weight-supported treadmill training and acute responses to varying walking speed and body-weight support in ambulatory patients post-stroke

Rehabilitating walking in ambulatory patients post-stroke, with training that is safe, task-specific, intensive, and of sufficient duration, can be challenging. Some challenges can be met by using body-weight-supported treadmill training (BWSTT). However, it is not known to what degree walking characteristics are similar during BWSTT and overground walking. In addition, important questions regarding the training protocol of BWSTT remain unanswered, such as how proportion of body-weight support (BWS) and walking speed affect walking characteristics during training. The objective was therefore to investigate if and how kinematic walking characteristics are different between overground walking and treadmill walking with BWS in ambulatory patients post-stroke, and the acute response of altering walking speed and percent BWS during treadmill walking with BWS. A cross-sectional repeated-measures design was used. Ambulating patients post-stroke walked in slow, preferred, and fast walking speed overground and at comparable speeds on the treadmill with 20% and 40% BWS. Kinematic walking characteristics were obtained using a kinematic sensor attached over the lower back. Forty-four patients completed the protocol. Kinematic walking characteristics were similar during treadmill walking with BWS, compared to walking overground. During treadmill walking, choice of walking speed had greater impact on kinematic walking characteristics than proportion of BWS. Faster walking speeds tended to affect the kinematic walking characteristics positively. This implies that in order to train safely and with sufficient intensity and duration, therapists may choose to include BWSTT in walking rehabilitation also for ambulatory patients post-stroke without aggravating gait pattern during training.

In-home walking speeds and variability trajectories associated with mild cognitive impairment

To determine whether unobtrusive long-term in-home assessment of walking speed and its variability can distinguish those with mild cognitive impairment (MCI) from those with intact cognition. Walking speed was assessed using passive infrared sensors fixed in series on the ceiling of the homes of elderly individuals participating in the Intelligent Systems for Assessing Aging Change (ISAAC) cohort study. Latent trajectory models were used to analyze weekly mean speed and walking speed variability (coefficient of variation [COV]). ISAAC participants living alone included 54 participants with intact cognition, 31 participants with nonamnestic MCI (naMCI), and 8 participants with amnestic MCI at baseline, with a mean follow-up of 2.6 ± 1.0 years. Trajectory models identified 3 distinct trajectories (fast, moderate, and slow) of mean weekly walking speed. Participants with naMCI were more likely to be in the slow speed group than in the fast (p = 0.01) or moderate (p = 0.04) speed groups. For COV, 4 distinct trajectories were identified: group 1, the highest baseline and increasing COV followed by a sharply declining COV; groups 2 and 3, relatively stable COV; and group 4, the lowest baseline and decreasing COV. Participants with naMCI were more likely to be members of either highest or lowest baseline COV groups (groups 1 or 4), possibly representing the trajectory of walking speed variability for early- and late-stage MCI, respectively. Walking speed and its daily variability may be an early marker of the development of MCI. These and other real-time measures of function may offer novel ways of detecting transition phases leading to dementia.

Gait Recognition Across Various Walking Speeds Using Higher Order Shape Configuration Based on a Differential Composition Model

Gait has been known as an effective biometric feature to identify a person at a distance. However, variation of walking speeds may lead to significant changes to human walking patterns. It causes many difficulties for gait recognition. A comprehensive analysis has been carried out in this paper to identify such effects. Based on the analysis, Procrustes shape analysis is adopted for gait signature description and relevant similarity measurement. To tackle the challenges raised by speed change, this paper proposes a higher order shape configuration for gait shape description, which deliberately conserves discriminative information in the gait signatures and is still able to tolerate the varying walking speed. Instead of simply measuring the similarity between two gaits by treating them as two unified objects, a differential composition model (DCM) is constructed. The DCM differentiates the different effects caused by walking speed changes on various human body parts. In the meantime, it also balances well the different discriminabilities of each body part on the overall gait similarity measurements. In this model, the Fisher discriminant ratio is adopted to calculate weights for each body part. Comprehensive experiments based on widely adopted gait databases demonstrate that our proposed method is efficient for cross-speed gait recognition and outperforms other state-of-the-art methods.

Robust Gait-Based Person Identification against Walking Speed Variations

Robust Gait-Based Person Identification against Walking Speed Variations

P142 Pedometer and activity monitor step count reliability compared to visual during walking in patients with chronic respiratory disease

IntroductionChronic respiratory disease (CRD) is associated with reduced physical activity (PA), which pulmonary rehabilitation (PR) can improve. There are a variety of devices which monitor PA. Activity monitors (AM) are...

In-home daily walking variability: A marker of mild cognitive impairment

Background: Increased cognitive andmotor test-to-test variability are associated with Mild Cognitive Impairment (MCI). Home-based, unobtrusive and continuous assessment of walking speed may provide a means of capturing early changes in the real-world trajectory of activity variance characterizing MCI. We examined whether long-term in-home assessment of walking speed and its variability can distinguish MCI from those who are cognitively intact.Methods: Participants enrolled in the Intelligent Systems for Assessing Aging Change (ISSAC) study, a longitudinal study of unobtrusive in-home technologies to detect cognitive and motor decline in independently living seniors, were defined as MCI or normal at baseline using neuropsychological test data and pre-defined algorithms. Walking speed was assessed using passive infra-red sensors fixed in series on the ceiling of the homes of seniors. The weekly median speed and coefficient of variation (CoV) were analyzed using latent trajectory and mixed effects models. Results:Data from 111 ISAAC subjects living alone (35 with MCI) was acquired for a mean of 271.9 6 175.2 days. Mean cohort age was 84.9 6 4.8 yrs. Latent trajectory models identified 3 and 4 distinct trajectories for median speed and CoV, respectively. MCI was not associated with any of the trajectory patterns of weekly median walking speed, but was more likely to be in the group where CoV was high at baseline and remained high over time (OR 1⁄4 7.0; p 1⁄4 0.03), as opposed to be in the group with lower CoVovertime. The mixed effects model controlling for age and gender confirmed these findings showing that MCI was associated with a high CoVof walking speed (p 1⁄4 0.02) that remained high over time (no interaction of time*MCI). Absolute walking speed over time (i.e., weekly median speed) or speed obtained during annual in-person assessments with a stopwatch over the same approximate two year period were not significantly different between the MCI and cognitively intact groups. Conclusions: Unobtrusive home-based assessment of variability in walking speed provides an indicator of individuals with MCI. These and other real-time measures of function may be used to detect transition phases representing presymptomatic or latent disease leading to dementia and to assess treatment outcomes overtime.

Reliability and Validity of Bilateral Ankle Accelerometer Algorithms for Activity Recognition and Walking Speed After Stroke

Outcome measures of mobility for large stroke trials are limited to timed walks for short distances in a laboratory, step counters and ordinal scales of disability and quality of life. Continuous monitoring and outcome measurements of the type and quantity of activity in the community would provide direct data about daily performance, including compliance with exercise and skills practice during routine care and clinical trials. Twelve adults with impaired ambulation from hemiparetic stroke and 6 healthy controls wore triaxial accelerometers on their ankles. Walking speed for repeated outdoor walks was determined by machine-learning algorithms and compared to a stopwatch calculation of speed for distances not known to the algorithm. The reliability of recognizing walking, exercise, and cycling by the algorithms was compared to activity logs. A high correlation was found between stopwatch-measured outdoor walking speed and algorithm-calculated speed (Pearson coefficient, 0.98; P=0.001) and for repeated measures of algorithm-derived walking speed (P=0.01). Bouts of walking >5 steps, variations in walking speed, cycling, stair climbing, and leg exercises were correctly identified during a day in the community. Compared to healthy subjects, those with stroke were, as expected, more sedentary and slower, and their gait revealed high paretic-to-unaffected leg swing ratios. Test-retest reliability and concurrent and construct validity are high for activity pattern-recognition Bayesian algorithms developed from inertial sensors. This ratio scale data can provide real-world monitoring and outcome measurements of lower extremity activities and walking speed for stroke and rehabilitation studies.

Commentary on “Walking Stride Rate Patterns in Children and Youth”

“How should I apply this information?” This study used a unique way of analyzing stride rate data collected for children with cerebral palsy (CP) Gross Motor Function Classification System (GMFCS) levels I–III, children with distal arthrogryposis (AR), and youth who were typically developing (TD) over a 7-day period. The authors used data collected with the StepWatch Activity Monitor (SW). Trajectory curves were developed to represent the average number of minutes per day spent at each stride rate, from inactivity (0 strides/minute) to peak stride rate, for each group. They then compared the amount of inactivity, peak stride rates, and variability in stride rates across the 3 groups of children. Children with AR and CP had significantly increased periods of inactivity compared with the TD group. This suggests that these youth participate less in age-appropriate physical activities than TD peers. Less variability in walking speed with lower peak stride rates was found in the children with CP compared with the TD group. This was specifically evident in children classified as GMFCS levels II and III who may require orthoses and assistive devices for mobility. Variability is an important component of motor development, and variable walking speed is necessary for full participation in daily activities. Treatment interventions should, therefore, address increasing variability in gait speed for children with CP and AR. As these children age, orthotics and assistive devices should be reevaluated to ensure that they allow for maximum activity level and versatile speed of movement. Finally, SW measures the child's actual performance of the functional activity of walking in their natural environment over the course of the day. This is different from other outcome measures and may be useful if the goal of intervention is to increase a child's ability to keep up with peers in a school setting, or when preparing a child for participation in a recreation/sports program. “What should I be mindful about in applying this information?” The reader needs to remember that subjects were from a convenience sample and most were Caucasian. Although the authors analyzed stride rate patterns in a large number of youth who were TD, comparisons were made to smaller groups of children with CP and AR. Data were collected on children between the ages of 6 and 15 years; however, comparisons between the TD and CP groups were for children between 10 and 13 years. The reader also needs to be mindful about the use of secondary analysis of different data sets that may pose a problem of consistency in data collection. There are also many confounding variables; that is, environmental factors, body size, physical condition/fitness, etc, that were not monitored or explained that may affect the child's activity level. Strengths of the study include (1) nearly equal boys and girls in each age group, (2) clear method of determining noncompliance, (3) data averaged for 5 days within a 7-day period including 1 week-end day, (4) accuracy of the device demonstrated by comparing it to a manual count, and (5) a transformation method used to normalize data. Overall, an adequate picture of children's walking stride rate patterns is demonstrated for wide age range of both boys and girls. Donna Redman-Bentley, PT, PhD Western University of Health Sciences, Pomona, California Mary Wardell, PT, DPT, MS, PCS Long Beach Memorial Miller Children's Hospital, Long Beach, California

Using Video Animation to Assess Mobility in Older Adults

Although the importance of the context of task performance in the assessment of mobility in older adults is generally understood, there is little empirical evidence that demonstrates how sensitive older adults are to subtle changes in task demands. Thus, we developed a novel approach to examine this issue. We collected item response data to 81 animated video clips, where various mobility-related tasks were modified in a systematic fashion to manipulate task difficulty. The participants (N = 234), 166 women and 68 men, had an average age of 81.9 years and a variety of comorbidities. Histograms of item responses revealed dramatic and systematic effects on older adults' self-reported ability when varying walking speed, use of a handrail during ascent and descent of stairs, walking at different speeds outdoors over uneven terrain, and carrying an object. For example, there was almost a threefold increase in reporting the inability to walk at the fast speed compared with the slow speed for a minute or less, and twice as many participants reported the inability to walk at the fast speed outdoors over uneven terrain compared with indoors. The data provide clear evidence that varying the contextual features and demands of a simple task such as stair climbing has a significant impact on older adults' self-reporting of ability related to mobility. More work is needed on the psychometric properties of such assessments and to determine if this methodology has conceptual and clinical relevance in studying mobility disability.

Re-interpreting detrended fluctuation analyses of stride-to-stride variability in human walking

Detrended fluctuation analyses (DFA) have been widely used to quantify stride-to-stride temporal correlations in human walking. However, significant questions remain about how to properly interpret these statistical properties physiologically. Here, we propose a simpler and more parsimonious interpretation than previously suggested. Seventeen young healthy adults walked on a motorized treadmill at each of 5 speeds. Time series of consecutive stride lengths (SL) and stride times (ST) were recorded. Time series of stride speeds were computed as SS = SL/ST. SL and ST exhibited strong statistical persistence ( α ≫ 0.5). However, SS consistently exhibited slightly anti-persistent ( α < 0.5) dynamics. We created three surrogate data sets to directly test specific hypotheses about possible control processes that might have generated these time series. Subjects did not choose consecutive SL and ST according to either independently uncorrelated or statistically independent auto-regressive moving-average (ARMA) processes. However, cross-correlated surrogates, which preserved both the auto-correlation and cross-correlation properties of the original SL and ST time series successfully replicated the means, standard deviations, and (within computational limits) DFA α exponents of all relevant gait variables. These results suggested that subjects controlled their movements according to a two-dimensional ARMA process that specifically sought to minimize stride-to-stride variations in walking speed (SS). This interpretation fully agrees with experimental findings and also with the basic definitions of statistical persistence and anti-persistence. Our findings emphasize the necessity of interpreting DFA α exponents within the context of the control processes involved and the inherent biomechanical and neuro-motor redundancies available.

A Proof-of-Concept Study for Measuring Gait Speed, Steadiness, and Dynamic Balance Under Various Footwear Conditions Outside of the Gait Laboratory

This pilot study examined the effect of custom and prefabricated foot orthoses on self-selected walking speed, walking speed variability, and dynamic balance in the mediolateral direction. The gait of four healthy participants was analyzed with a body-worn sensor system across a distance of at least 30 m outside of the gait laboratory. Participants walked at their habitual speed in four conditions: barefoot, regular shoes, prefabricated foot orthoses, and custom foot orthoses. In the custom foot orthoses condition, gait speed was improved on average 13.5% over the barefoot condition and 9.8% over the regular shoe condition. The mediolateral range of motion of center of mass was reduced 55% and 56% compared with the shoes alone and prefabricated foot orthoses conditions, respectively. This may suggest better gait efficiency and lower energy cost with custom foot orthoses. This tendency remained after normalizing center of mass by gait speed, suggesting that irrespective of gait speed, custom foot orthoses improve center of mass motion in the mediolateral direction compared with other footwear conditions. Gait intercycle variability, measured by intercycle coefficient of variation of gait speed, was decreased on average by 25% and 19% compared with the barefoot and shoes-alone conditions, respectively. The decrease in gait unsteadiness after wearing custom foot orthoses may suggest improved proprioception from the increased contact area of custom foot orthoses versus the barefoot condition. These findings may open new avenues for objective assessment of the impact of prescribed footwear on dynamic balance and spatiotemporal parameters of gait and assess gait adaptation after use of custom foot orthoses.

Making virtual walking real

For us humans, walking is our most natural way of moving through the world. One of the major challenges in present research on navigation in virtual reality is to enable users to physically walk through virtual environments. Although treadmills, in principle, allow users to walk for extended periods of time through large virtual environments, existing setups largely fail to produce a truly immersive sense of navigation. Partially, this is because of inadequate control of treadmill speed as a function of walking behavior. Here, we present a new control algorithm that allows users to walk naturally on a treadmill, including starting to walk from standstill, stopping, and varying walking speed. The treadmill speed control consists of a feedback loop based on the measured user position relative to a given reference position, plus a feed-forward term based on online estimation of the user's walking velocity. The purpose of this design is to make the treadmill compensate fully for any persistent walker motion, while keeping the accelerations exerted on the user as low as possible. We evaluated the performance of the algorithm by conducting a behavioral experiment in which we varied its most important parameters. Participants walked at normal walking speed and then, on an auditory cue, abruptly stopped. After being brought back to the center of the treadmill by the control algorithm, they rated how smoothly the treadmill had changed its velocity in response to the change in walking speed. Ratings, in general, were quite high, indicating good control performance. Moreover, ratings clearly depended on the control algorithm parameters that were varied. Ratings were especially affected by the way the treadmill reversed its direction of motion. In conclusion, controlling treadmill speed in such a way that changes in treadmill speed are unobtrusive and do not disturb VR immersiveness is feasible on a normal treadmill with a straightforward control algorithm.

Walking Economy of Adults with Down Syndrome

This study intended to investigate walking economy (WE) in response to different treadmill speeds and grades in adults with Down syndrome (DS) and in non-disabled controls. Eighteen participants (14 males; 4 females) with DS (33.6+/-7.6 years) and 16 non-disabled (12 males, 4 females) controls (33.3+/-8.0 years) performed submaximal (2.5 km . h (-1) and 4 km . h (-1) at 0% grade; 4 km . h (-1) at 2.5% and 5% grade, for 5 min each) and maximal treadmill tests with metabolic and heart rate measurements. Oxygen uptake (VO(2)) was not different between groups at rest or during the slowest treadmill speed. However, at faster speeds and increased grades, adults with DS presented lower WE than controls (p<0.0001). Subsequent analyses revealed that, despite showing higher delta VO(2) response to the selected speed increments (p<0.0001), individuals with DS produced similar VO(2) increase as controls to grade variations. Therefore, adults with DS exhibit lower WE than non-disabled controls at a speed faster than their preferred walking speed. Additionally, in comparison to controls, individuals with DS show a greater change in energy expenditure with a change in walking speed. In conclusion, lower WE in individuals with DS is mainly related to their inability to adapt efficiently to positive variations in walking speed.

Regional Muscle and Whole-Body Composition Factors Related to Mobility in Older Individuals: A Review

To describe previously reported locomotor muscle and whole-body composition factors related to mobility in older individuals. A narrative review of the literature, including a combination of search terms related to muscle and whole-body composition factors and to mobility in older individuals, was carried out. Statistical measures of association and risk were consolidated to summarize the common effects between studies. Fifty-three studies were reviewed. Muscle and whole-body factors accounted for a substantial amount of the variability in walking speed, with coefficients of determination ranging from 0.30 to 0.47. Muscle power consistently accounted for a greater percentage of the variance in mobility than did strength. Risks associated with high fat mass presented a minimum odds ratio (OR) of 0.70 and a maximum OR of 4.07, while the minimum and maximum ORs associated with low lean mass were 0.87 and 2.30 respectively. Whole-body and regional fat deposits accounted for significant amounts of the variance in mobility. Muscle power accounts for a greater amount of the variance in the level of mobility in older individuals than does muscle strength. Whole-body fat accounts for a greater amount of the variance in level of mobility than does whole-body lean tissue. Fat stored within muscle also appears to increase the risk of a mobility limitation in older individuals.

Energy cost of walking: Solving the paradox of steady state in the presence of variable walking speed

Measurement of the energy cost of walking in children with cerebral palsy is used for baseline and outcome assessment. However, such testing relies on the establishment of steady state that is deemed present when oxygen consumption is stable. This is often assumed when walking speed is constant but in practice, speed can and does vary naturally. Whilst constant speed is achievable on a treadmill, this is often impractical clinically, thus rendering an energy cost test to an element of subjectivity. This paper attempts to address this issue by presenting a new method for calculating energy cost of walking that automatically applies a mathematically defined threshold for steady state within a (non-treadmill) walking trial and then strips out all of the non-steady state events within that trial. The method is compared with a generic approach that does not remove non-steady state data but rather uses an average value over a complete walking trial as is often used in the clinical environment. Both methods were applied to the calculation of several energy cost of walking parameters of self-selected walking speed in a cohort of unimpaired subjects and children with cerebral palsy. The results revealed that both methods were strongly correlated for each parameter but showed systematic significant differences. It is suggested that these differences are introduced by the rejection of non-steady state data that would otherwise have incorrectly been incorporated into the calculation of the energy cost of walking indices during self-selected walking with its inherent speed variation.

A comparative study of the physiological costs of walking in ten bilateral amputees

The physiological cost of walking is greater in bilateral amputees (BA) than in both unilateral amputee and non-pathological gait. The aim of this study was to describe the physiological costs and other standard gait characteristics in a sample population of BA, walking at self-selected (comfortable) speeds. Amputees had bilateral trans-tibial, bilateral trans-femoral or trans-tibial/trans-femoral amputations as a result of trauma or congenital defects. All amputees wore their own prosthetic limbs which were either full-length prostheses or short non-articulating pylon prostheses (SNAPPs). The results were compared with a base line data set collected from a non-pathological control group. It was anticipated that amputees with high-level amputations would walk at the slowest speeds, have the highest physiological costs and lowest perception of walking ability. However, varying walking speeds resulted in varying exercise intensities, exercise heart rates and perceptions of walking that could not be directly related to amputation levels. It is therefore concluded that bilateral amputee gait is complex, varied and not easily categorized.