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Introduction: Gait biomechanics are associated with knee osteoarthritis (OA) structural progression, but no studies have included: i) all three lower extremity joints, ii) non-frontal plane factors, iii) temporal loading patterns, and iv) progression from structural and symptomatic perspectives. This dissertation addressed gaps in our understanding of lower limb biomechanics and their implication for determining whether we have identified and are targeting the most effective biomechanical variables in the development and evaluation of conservative interventions to slow knee OA structural and symptom progression (progression to TKA). Methods: 54 patients with knee OA underwent baseline gait analysis. Three-dimensional hip, knee, and ankle angles and moments were calculated. Waveform characteristics were determined using Principal Component Analysis (PCA), and knee adduction moment (KAM) peak and impulse were calculated. At follow-up 5-8 years later, 26 patients reported undergoing total knee arthroplasty (TKA). Unpaired Student’s t-tests detected differences in baseline demographic and gait characteristics between TKA and no-TKA groups. Receiver operating curve analysis determined discriminative abilities of these differences. Stepwise discrimination analysis determined which multivariate combination best classified the TKA group. Logistic regression analysis determined the predictive ability of the multivariate model. Results: There were no baseline differences in clinical and spatiotemporal gait characteristics, but the TKA group showed significant gait biomechanical differences, including higher KAM magnitude (KAMPC1), less difference between early and mid-stance KAM (KAMPC2), higher KAM peak and impulse, reduced early stance knee flexion and late stance knee extension moments (KFMPC2), and reduced stance dorsiflexion moments (AFMPC4). The multivariate discriminant function with the highest classification rate (74.1%) combined KAMPC1, KFMPC2, and AFMPC4, with sensitivity of 84.6 and specificity of 71.4. A one-unit increase in the model score increased risk of progression to TKA six-fold. Conclusion: Higher KAMPC1 scores suggest higher overall loading during gait. Lower KFMPC2 and AFMPC4 scores suggest inability to unload the knee and therefore sustained loading. Interventions reducing overall load and altering patterns of loading (i.e. increase unloading) may reduce risk of progression to TKA. Future research should determine how components of the discriminant model can be altered conservatively, and what impact alterations have on the risk of progression to TKA.

Walking pigeons display a characteristic behaviour: head-bobbing. Head-bobbing consists of two phases, the hold phase during which the head is kept stable in space, and the thrust phase during which the head is quickly moved forward. But why do pigeons and so many other birds head-bob? Two theories have been developed to answer this question. First, head-bobbing may have a visual function, namely object detection during the hold phase and depth perception during the thrust phase. Second, head-bobbing may have the biomechanical function of increasing the stability. The present study aimed to gain further insight into why pigeons head-bob. A gait cycle analysis of walking pigeons revealed that the hold phase starts at a specific point in the gait cycle and is not dependent on the walking speed. The point in the gait cycle at which the hold phase starts indicates a potential increase in stability during the single stance phase, as it leads to a longer period of time during which the center of mass is above the base of support. The end of the hold phase, however, is dependent on the walking speed, specifically the step length for a given walking speed. I found that the thrust phase duration is constant for all walking speeds and the distance the head travels during that time is equal to the step length. With increasing walking speed the head moves faster during the thrust phase and the hold phase duration is decreased leading to a higher head-bobbing frequency. With fast enough walking speed the hold phase is eventually eliminated, marking the transition point from walking with head-bobbing to fast walking without head-bobbing. The exact velocity of this transition point was predicted for each individual and was dependent on the maximal step length of each pigeon. All head-bobbing parameters could be described with the step-frequency, the thrust phase duration, and the maximal step length, indicating that head-bobbing behavior is individual for every pigeon and depends on its body size. / Thesis (Master, Biology) -- Queen's University, 2013-07-22 23:11:41.557

With the popularity of outdoor activities like hiking, the demands of certain types of employment, or being a student, an individual’s ability to carry a load is an important mobility consideration. By understanding the changes to an individual’s gait when supporting a backpack load, an individual’s ability to carry heavy loads for prolonged periods could be improved. Most biomechanical studies have examined the changes in able-bodied gait when carrying a load. However, research is lacking on the effect of backpack loads on amputee gait patterns. This project examined the effects of a backpack load on the gait patterns of unilateral transtibial amputees. Ten participants performed walking trials on four surfaces (level ground, uneven ground, walking up an incline, and walking down an incline), without a pack and with a pack. A total of 40 trials were collected per subject, with 10 trials collected on each surface. Three-dimensional motion data were collected with an eight-camera Vicon Motion Analysis system to describe limb motion as well as compare kinematic outcomes between tasks and conditions. Force platform data were collected during the level ground trials and used to calculate kinetic measures for both limbs. With the addition of the pack changes were seen on each surface, with different changes occurring to each limb. The ramp up surface created the most changes when comparing the two conditions. The only change seen across all four surfaces was a decrease in ankle dorsiflexion before push-off on the prosthetic limb. The two next most common changes were increases in knee and hip flexion during weight-acceptance.

In legged terrestrial locomotion, the duration of stance phase, i.e., when limbs are in contact with the substrate, is positively correlated with limb length, and negatively correlated with the metabolic cost of transport. These relationships are well documented at the interspecific level, across a broad range of body sizes and travel speeds. However, such relationships are harder to evaluate within species (i.e., where natural selection operates), largely for practical reasons, including low population variance in limb length, and the presence of confounding factors such as body mass, or training. Here, we compared spatiotemporal kinematics of gait in Longshanks, a long-legged mouse line created through artificial selection, and in random-bred, mass-matched Control mice raised under identical conditions. We used a gait treadmill to test the hypothesis that Longshanks have longer stance phases and stride lengths, and decreased stride frequencies in both fore- and hind limbs, compared with Controls. Our results indicate that gait differs significantly between the two groups. Specifically, and as hypothesized, stance duration and stride length are 8–10% greater in Longshanks, while stride frequency is 8% lower than in Controls. However, there was no difference in the touch-down timing and sequence of the paws between the two lines. Taken together, these data suggest that, for a given speed, Longshanks mice take significantly fewer, longer steps to cover the same distance or running time compared to Controls, with important implications for other measures of variation among individuals in whole-organism performance, such as the metabolic cost of transport.

Although poor walking is the most common symptom of peripheral artery disease (PAD), reported results are inconsistent when comparing gait parameters between PAD patients and healthy controls. This inconsistency may be due to frailty, which is highly prevalent among PAD patients. To address this hypothesis, 41 participants, 17 PAD (74 +/- 8 years) and 24 aged-matched controls (76 +/- 7 years), were recruited. Gait was objectively assessed using validated wearable sensors. Analysis of covariate (ANCOVA) tests were used to compare gait parameters between PAD and non-PAD groups, considering age, gender, and body mass index as covariates, while stratified based on frailty status. According to the Fried frailty index, 47% of PAD and 50% of control participants were non-frail and the rest were classified as pre-frail. Within non-frail participants, gait speed, body sway during walking, stride length, gait cycle time, double-support, knee range of motion, speed variability, mid-swing speed, and gait initiation were significantly different between PAD and control groups (effect size d = 0.75 +/- 0.43). In the pre-frail group, however, most of the gait differences were diminished except for gait initiation and gait variability. Results suggest that gait initiation is the most sensitive parameter for detecting gait impairment in PAD participants when compared to controls, regardless of frailty status (d = 1.30-1.41; p<0.050). The observed interaction effect between frailty and PAD on gait parameters confirms the importance of assessing functionality in addition to age to provide more consistency in detecting motor performance impairments due to PAD.

Finally, the research of classifying and identifying individuals through their walking patterns is introduced. Alive biometrical features in dynamic human gait are adopted in the intelligent shoe system. Since gait data are dynamic, non-linear, stochastic, time-varying, noisy and multi-channel, we must select a modeling framework capable of dealing with these expected complexities in the data. Using the proposed machine learning methods, support vector machine (SVM) and hidden Markov models (HMMs), we build up probabilistic models that take the information of human walking patterns into account, and compare the overall similarity among human walking patterns of several wearers. / In this thesis, we will build intelligent shoes under the framework for capturing and analyzing dynamic human gait. Existing MEMS technology makes it possible to integrate all the sensors and circuits inside a small module. In designing our intelligent shoe system, we require the following key characteristics in our system: (1) It should be convenient to wear and socially acceptable. Thus, the sensors and electronic hardware installed should not substantially change the weight and weight balance of a typical shoe, lest it alters how an individual normally walks. (2) We want to analyze a user's motion in real-time through a wireless interface to a remote laptop or other computer; we will also incorporate on-shoe data logging hardware for off-line analysis. (3) Sensors that monitor gait motion conditions may need to be attached to the insoles, in closer proximity to the foot of users. In order to investigate the problem of capturing power parasitically from normal human-body-motion for use in personal electronics applications, we also plan to develop an electromechanical generator embedded within the shoe for parasitic power collection from heel strike. / Next, we can encode specific motions to control external devices through a wireless interface. This same system architecture that allows us to classify broad categories of motion also allows the intelligent shoe to act as a programmable, low-data rate control interface. We apply the system to several successful tasks based on this platform, especially the Shoe-Mouse. By using this interface, we can operate a device with our feet. / Then, we present potential use of machine learning techniques, in particular support vector machine (SVM), and the intelligent shoe platform to detect discrete stages in the cyclic motion of dynamic human gait, and construct an identifier of five discrete events that occur in a cyclic process for precise control of functional electrical stimulation (FES). With the information of when the legs are in each phase of a gait, the timing of specific gait phase can be assessed. / Huang, Bufu. / "September 2007." / Adviser: Yangsheng Xu. / Source: Dissertation Abstracts International, Volume: 69-08, Section: B, page: 4931. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 122-131). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese. / School code: 1307.

A question which has arisen clinically is the inability to generate adequate vertical force during the second half of the stance phase in cerebral palsy gait. Neither the mechanism nor the consequences of this inability are understood. It implies that the centre of mass (CoM) is inadequately supported with the potential for collapse of the limb in single support. Normal walking is achieved by the sophisticated control of the neuromuscular and skeletal systems with the purpose of advancing the body with minimum energy expenditure. These control systems are affected by damage to the brain in children with cerebral palsy and result in a multitude of problems which affect their gait making it difficult to determine cause and effect. This study aimed to improve the understanding of the ground reaction forces and motion of the CoM. Objectives The principle objectives were to analyse the supporting forces of the CoM during gait in normal adults, children, and children with diplegic cerebral palsy, by examining the inter-relationships of the vertical and horizontal components of the ground reaction force with the vertical component of motion and temporal parameters of the CoM. Design The study of adults and children’s data was both prospective and retrospective. The study of cerebral palsy data was retrospective. A new software programme was developed to extract specific gait parameters from both normal and cerebral palsy gait patterns. A novel approach to analyse the interaction of motion and force data in normal walking was subsequently developed. Background In normal gait, the vertical component of the ground reaction force forms a double hump where both humps are equal in magnitude and greater than body weight. It is widely accepted that the first hump (FZ1) is associated with deceleration of the downward motion of the CoM as the foot “impacts” the ground and the second hump (FZ2) is the action of “push off” as the body is propelled upwards and forwards. Walking requires force contributions from both legs but traditionally computed three-dimensional (3D) gait analysis packages presents the force data with both legs superimposed, rather than sequentially in time. This gives the impression that there is no period of overlap of the forces and thus ignores the critically important period where the CoM is transferred from one leg to the other during double support. By changing the presentation to view it sequentially in time, plus superimposing the CoM kinematics onto the same scale allowed their interactions to be observed and objectively measured. Methods The kinematic and kinetic data of 53 normal adults, 33 normal children, and 57 diplegic cerebral palsy children were acquired for the study. A new gait cycle, based on CoM motion, was defined to allow analysis of the forces in relation to CoM motion. Software was developed to extract specified parameters from the gait data. Impulse calculations over specific periods (based on the vertical motion of the CoM) allowed analysis of the vertical force contribution of each leg to the vertical support of the CoM. Results The results showed that inadequate generation of vertical force in children with diplegic cerebral palsy was widespread. In approximately 40% of such children there was a reduced ability to generate an adequate FZ2, which resulted in a reduced ability to control of the descent velocity of the CoM. The mean reduction in descent velocity in cerebral palsy was only 54% compared to 86% in adults. Integration of the vertical force and motion of the CoM showed that FZ2 was associated with controlling the descent velocity of the CoM. This reverses the traditionally accepted concept of “impact” and is contrary to the belief that FZ2 is associated with ‘push off’. Conclusions and Relevance This study emphasises the importance of the role of the supporting leg in the second half of stance. Failure to generate an adequate FZ2, which is currently ignored in clinical practice, should be given priority in patient management. This new knowledge has significant implications from a clinical perspective, not only in diplegic cerebral palsy, but in pathologies such as amputees, spina-bifida, and other neuro-muscular conditions.

Thesis (M.D.) -- University of Texas Southwestern Medical Center at Dallas, 2007. / Vita. Bibliography: pp. 42-45.

The incidence of falls is common in older adults and becomes more frequent with advancing age. Falls and injuries associated with falls are among the most debilitating and traumatic medical problems encountered by the elderly. There is evidence that indicates there may be a cause and effect relationship between specific gait parameters and falling. If a simple gait test can predict fallers, it could become a valuable tool for identifying individuals at high risk of falling. The purposes of this study were 1) to determine whether performance on the Functional Ambulation Profile (FAP) could accurately predict fallers and non-fallers in a prospective manner and 2) to identify gait parameters within the FAP that would best classify fallers. My hypothesis for this study include 1) the Functional Ambulation Profile (FAP) will accurately predict subjects as fallers and non-fallers and 2) of the five variables that comprise the FAP walking velocity, right and left step length:leg length ratio, step width will be the most powerful predictors of fall status. Two hundred twenty six subjects were evaluated using the GAITRite electronic walkway. Falls surveillance was conducted for 8 months after each participant's specific GAITRite testing date. Average height, weight and BMI were 161.9 �� 8.7 cm, 68.1 �� 16.7 kg, and 25.9 �� 4.1 kg/m��, respectively. Men and women were analyzed separately using analysis of variance, logistic regression and relative operating characteristic curves. There was no difference between fallers and non-fallers for any of the FAP variables for both the men and women. Regression results indicated the overall model for FAP to predict fallers was not statistically significant for either men or women, (p=0.706 and p=0.543, respectively). In addition, none of the five variables that make up the FAP was significant enough to be included in a stepwise logistic model, thus we were unable to develop an alternative model for predicting fallers based on gait variables. A secondary analysis found that the FAP was unable to distinguish multiple fallers (3 or more) from occasional and non-fallers in this same study population. The results of this study indicate that the FAP does not predict falls in independently living men and women over the age of 70. Further, none of the five gait variables that compose the FAP was a significant independent predictor of falls in this same population. Based on the results of this study we conclude that the FAP alone is not sufficient to predict risk of falling among older adults. Because of the complexity of all the physical, psychological and environmental elements that can lead to falling, tests based on only spatial and temporal gait characteristics do not appear to be good fall predictors for independent older adults. / Graduation date: 2003