Effects of pediatric obesity on joint kinematics and kinetics during 2 walking cadences

Objective: To determine whether differences existed in lower-extremity joint biomechanics during self-selected walking cadence (SW) and fast walking cadence (FW) in overweight- and normal-weight children.---------- Design: Survey.---------- Setting: Institutional gait study center.---------- Participants: Participants (N=20; mean age ± SD, 10.4±1.6y) from referred and volunteer samples were classified based on body mass index percentiles and stratified by age and sex. Exclusion criteria were a history of diabetes, neuromuscular disorder, or recent lower-extremity injury.---------- Main Outcome Measures: Sagittal, frontal, and transverse plane angular displacements (degrees) and peak moments (newton meters) at the hip, knee, and ankle joints.---------- Results: The level of significance was set at P less than .008. Compared with normal-weight children, overweight children had greater absolute peak joint moments at the hip (flexor, extensor, abductor, external rotator), the knee (flexor, extensor, abductor, adductor, internal rotator), and the ankle (plantarflexor, inverter, external/internal rotators). After including body weight as a covariate, overweight children had greater peak ankle dorsiflexor moments than normal-weight children. No kinematic differences existed between groups. Greater peak hip extensor moments and less peak ankle inverter moments occurred during FW than SW. There was greater angular displacement during hip flexion as well as less angular displacement at the hip (extension, abduction), knee (flexion, extension), and ankle (plantarflexion, inversion) during FW than SW.---------- Conclusions: Overweight children experienced increased joint moments, which can have long-term orthopedic implications and suggest a need for more nonweight-bearing activities within exercise prescription. The percent of increase in joint moments from SW to FW was not different for overweight and normal-weight children. These findings can be used in developing an exercise prescription that must involve weight-bearing activity.

Paediatric obesity, physical activity and the musculoskeletal system

The current epidemic of paediatric obesity is consistent with a myriad of health-related comorbid conditions. Despite the higher prevalence of orthopaedic conditions in overweight children, a paucity of published research has considered the influence of these conditions on the ability to undertake physical activity. As physical activity participation is directly related to improvements in physical fitness, skeletal health and metabolic conditions, higher levels of physical activity are encouraged, and exercise is commonly prescribed in the treatment and management of childhood obesity. However, research has not correlated orthopaedic conditions, including the increased joint pain and discomfort that is commonly reported by overweight children, with decreases in physical activity. Research has confirmed that overweight children typically display a slower, more tentative walking pattern with increased forces to the hip, knee and ankle during 'normal' gait. This research, combined with anthropometric data indicating a higher prevalence of musculoskeletal malalignment in overweight children, suggests that such individuals are poorly equipped to undertake certain forms of physical activity. Concomitant increases in obesity and decreases in physical activity level strongly support the need to better understand the musculoskeletal factors associated with the performance of motor tasks by overweight and obese children.

Bulk compressive properties of the heel fat pad during walking: a pilot investigation in plantar heel pain

Background: Altered mechanical properties of the heel pad have been implicated in the development of plantar heel pain. However, the in vivo properties of the heel pad during gait remain largely unexplored in this cohort. The aim of the current study was to characterise the bulk compressive properties of the heel pad in individuals with and without plantar heel pain while walking. ---------- Methods: The sagittal thickness and axial compressive strain of the heel pad were estimated in vivo from dynamic lateral foot radiographs acquired from nine subjects with unilateral plantar heel pain and an equivalent number of matched controls, while walking at their preferred speed. Compressive stress was derived from simultaneously acquired plantar pressure data. Principal viscoelastic parameters of the heel pad, including peak strain, secant modulus and energy dissipation (hysteresis), were estimated from subsequent stress–strain curves.---------- Findings: There was no significant difference in loaded and unloaded heel pad thickness, peak stress, peak strain, or secant and tangent modulus in subjects with and without heel pain. However, the fat pad of symptomatic feet had a significantly lower energy dissipation ratio (0.55 ± 0.17 vs. 0.69 ± 0.08) when compared to asymptomatic feet (P < .05).---------- Interpretation: Plantar heel pain is characterised by reduced energy dissipation ratio of the heel pad when measured in vivo and under physiologically relevant strain rates.

Incidental walking activity is sufficient to induce time-dependent conditioning of the Achilles tendon

The Achilles tendon has been seen to exhibit time-dependent conditioning when isometric muscle actions were of a prolonged duration, compared to those involved in dynamic activities, such as walking. Since, the effect of short duration muscle activation associated with dynamic activities is yet to be established, the present study aimed to investigate the effect of incidental walking activity on Achilles tendon diametral strain. Eleven healthy male participants refrained from physical activity in excess of the walking required to carry out necessary daily tasks and wore an activity monitor during the 24 h study period. Achilles tendon diametral strain, 2 cm proximal to the calcaneal insertion, was determined from sagittal sonograms. Baseline sonographic examinations were conducted at ∼08:00 h followed by replicate examinations at 12 and 24 h. Walking activity was measured as either present (1) or absent (0) and a linear weighting function was applied to account for the proximity of walking activity to tendon examination time. Over the course of the day the median (min, max) Achilles tendon diametral strain was −11.4 (4.5, −25.4)%. A statistically significant relationship was evident between walking activity and diametral strain (P < 0.01) and this relationship improved when walking activity was temporally weighted (AIC 131 to 126). The results demonstrate that the short yet repetitive loads generated during activities of daily living, such as walking, are sufficient to induce appreciable time-dependant conditioning of the Achilles tendon. Implications arise for the in vivo measurement of Achilles tendon properties and the rehabilitation of tendinopathy.

Improved joint control using a genetic algorithm for a humanoid robot

This paper describes experiments conducted in order to simultaneously tune 15 joints of a humanoid robot. Two Genetic Algorithm (GA) based tuning methods were developed and compared against a hand-tuned solution. The system was tuned in order to minimise tracking error while at the same time achieve smooth joint motion. Joint smoothness is crucial for the accurate calculation of online ZMP estimation, a prerequisite for a closedloop dynamically stable humanoid walking gait. Results in both simulation and on a real robot are presented, demonstrating the superior smoothness performance of the GA based methods.

Biologically inspired joint control for a humanoid robot

The GuRoo is a 1.2 m tall, 23 degree of freedom humanoid constructed at the University of Queensland for research into humanoid robotics. The key challenge being addressed by the GuRoo project is the development of appropriate learning strategies for control and coordination of the robot's many joints. The development of learning strategies is seen as a way to side-step the inherent intricacy of modeling a multi-DOF biped robot. This paper outlines the approach taken to generate an appropriate control scheme for the joints of the GuRoo. The paper demonstrates the determination of local feedback control parameters using a genetic algorithm. The feedback loop is then augmented by a predictive modulator that learns a form of feed-forward control to overcome the irregular loads experienced at each joint during the gait cycle. The predictive modulator is based on the CMAC architecture. Results from tests on the GuRoo platform show that both systems provide improvements in stability and tracking of joint control.

The modulation of outdoor running speed : the influence of gradient

This thesis aimed to investigate the way in which distance runners modulate their speed in an effort to understand the key processes and determinants of speed selection when encountering hills in natural outdoor environments. One factor which has limited the expansion of knowledge in this area has been a reliance on the motorized treadmill which constrains runners to constant speeds and gradients and only linear paths. Conversely, limits in the portability or storage capacity of available technology have restricted field research to brief durations and level courses. Therefore another aim of this thesis was to evaluate the capacity of lightweight, portable technology to measure running speed in outdoor undulating terrain. The first study of this thesis assessed the validity of a non-differential GPS to measure speed, displacement and position during human locomotion. Three healthy participants walked and ran over straight and curved courses for 59 and 34 trials respectively. A non-differential GPS receiver provided speed data by Doppler Shift and change in GPS position over time, which were compared with actual speeds determined by chronometry. Displacement data from the GPS were compared with a surveyed 100m section, while static positions were collected for 1 hour and compared with the known geodetic point. GPS speed values on the straight course were found to be closely correlated with actual speeds (Doppler shift: r = 0.9994, p < 0.001, Δ GPS position/time: r = 0.9984, p < 0.001). Actual speed errors were lowest using the Doppler shift method (90.8% of values within ± 0.1 m.sec -1). Speed was slightly underestimated on a curved path, though still highly correlated with actual speed (Doppler shift: r = 0.9985, p < 0.001, Δ GPS distance/time: r = 0.9973, p < 0.001). Distance measured by GPS was 100.46 ± 0.49m, while 86.5% of static points were within 1.5m of the actual geodetic point (mean error: 1.08 ± 0.34m, range 0.69-2.10m). Non-differential GPS demonstrated a highly accurate estimation of speed across a wide range of human locomotion velocities using only the raw signal data with a minimal decrease in accuracy around bends. This high level of resolution was matched by accurate displacement and position data. Coupled with reduced size, cost and ease of use, the use of a non-differential receiver offers a valid alternative to differential GPS in the study of overground locomotion. The second study of this dissertation examined speed regulation during overground running on a hilly course. Following an initial laboratory session to calculate physiological thresholds (VO2 max and ventilatory thresholds), eight experienced long distance runners completed a self- paced time trial over three laps of an outdoor course involving uphill, downhill and level sections. A portable gas analyser, GPS receiver and activity monitor were used to collect physiological, speed and stride frequency data. Participants ran 23% slower on uphills and 13.8% faster on downhills compared with level sections. Speeds on level sections were significantly different for 78.4 ± 7.0 seconds following an uphill and 23.6 ± 2.2 seconds following a downhill. Speed changes were primarily regulated by stride length which was 20.5% shorter uphill and 16.2% longer downhill, while stride frequency was relatively stable. Oxygen consumption averaged 100.4% of runner’s individual ventilatory thresholds on uphills, 78.9% on downhills and 89.3% on level sections. Group level speed was highly predicted using a modified gradient factor (r2 = 0.89). Individuals adopted distinct pacing strategies, both across laps and as a function of gradient. Speed was best predicted using a weighted factor to account for prior and current gradients. Oxygen consumption (VO2) limited runner’s speeds only on uphill sections, and was maintained in line with individual ventilatory thresholds. Running speed showed larger individual variation on downhill sections, while speed on the level was systematically influenced by the preceding gradient. Runners who varied their pace more as a function of gradient showed a more consistent level of oxygen consumption. These results suggest that optimising time on the level sections after hills offers the greatest potential to minimise overall time when running over undulating terrain. The third study of this thesis investigated the effect of implementing an individualised pacing strategy on running performance over an undulating course. Six trained distance runners completed three trials involving four laps (9968m) of an outdoor course involving uphill, downhill and level sections. The initial trial was self-paced in the absence of any temporal feedback. For the second and third field trials, runners were paced for the first three laps (7476m) according to two different regimes (Intervention or Control) by matching desired goal times for subsections within each gradient. The fourth lap (2492m) was completed without pacing. Goals for the Intervention trial were based on findings from study two using a modified gradient factor and elapsed distance to predict the time for each section. To maintain the same overall time across all paced conditions, times were proportionately adjusted according to split times from the self-paced trial. The alternative pacing strategy (Control) used the original split times from this initial trial. Five of the six runners increased their range of uphill to downhill speeds on the Intervention trial by more than 30%, but this was unsuccessful in achieving a more consistent level of oxygen consumption with only one runner showing a change of more than 10%. Group level adherence to the Intervention strategy was lowest on downhill sections. Three runners successfully adhered to the Intervention pacing strategy which was gauged by a low Root Mean Square error across subsections and gradients. Of these three, the two who had the largest change in uphill-downhill speeds ran their fastest overall time. This suggests that for some runners the strategy of varying speeds systematically to account for gradients and transitions may benefit race performances on courses involving hills. In summary, a non – differential receiver was found to offer highly accurate measures of speed, distance and position across the range of human locomotion speeds. Self-selected speed was found to be best predicted using a weighted factor to account for prior and current gradients. Oxygen consumption limited runner’s speeds only on uphills, speed on the level was systematically influenced by preceding gradients, while there was a much larger individual variation on downhill sections. Individuals were found to adopt distinct but unrelated pacing strategies as a function of durations and gradients, while runners who varied pace more as a function of gradient showed a more consistent level of oxygen consumption. Finally, the implementation of an individualised pacing strategy to account for gradients and transitions greatly increased runners’ range of uphill-downhill speeds and was able to improve performance in some runners. The efficiency of various gradient-speed trade- offs and the factors limiting faster downhill speeds will however require further investigation to further improve the effectiveness of the suggested strategy.

Cerebellar augmented joint control for a humanoid robot

The joints of a humanoid robot experience disturbances of markedly different magnitudes during the course of a walking gait. Consequently, simple feedback control techniques poorly track desired joint trajectories. This paper explores the addition of a control system inspired by the architecture of the cerebellum to improve system response. This system learns to compensate the changes in load that occur during a cycle of motion. The joint compensation scheme, called Trajectory Error Learning, augments the existing feedback control loop on a humanoid robot. The results from tests on the GuRoo platform show an improvement in system response for the system when augmented with the cerebellar compensator.

Falls in Parkinson's disease : kinematic evidence for impaired head and trunk control

Changes in stride characteristics and gait rhythmicity characterize gait in Parkinson's disease and are widely believed to contribute to falls in this population. However, few studies have examined gait in PD patients who fall. This study reports on the complexities of walking in PD patients who reported falling during a 12-month follow-up. Forty-nine patients clinically diagnosed with idiopathic PD and 34 controls had their gait assessed using three-dimensional motion analysis. Of the PD patients, 32 (65%) reported at least one fall during the follow-up compared with 17 (50%) controls. The results showed that PD patients had increased stride timing variability, reduced arm swing and walked with a more stooped posture than controls. Additionally, PD fallers took shorter strides, walked slower, spent more time in double-support, had poorer gait stability ratios and did not project their center of mass as far forward of their base of support when compared with controls. These stride changes were accompanied by a reduced range of angular motion for the hip and knee joints. Relative to walking velocity, PD fallers had increased mediolateral head motion compared with PD nonfallers and controls. Therefore, head motion could exceed “normal” limits, if patients increased their walking speed to match healthy individuals. This could be a limiting factor for improving gait in PD and emphasizes the importance of clinically assessing gait to facilitate the early identification of PD patients with a higher risk of falling.

Predictors of future falls in Parkinson disease

Background: Falls are a major health and injury problem for people with Parkinson disease (PD). Despite the severe consequences of falls, a major unresolved issue is the identification of factors that predict the risk of falls in individual patients with PD. The primary aim of this study was to prospectively determine an optimal combination of functional and disease-specific tests to predict falls in individuals with PD. ----- ----- Methods: A total of 101 people with early-stage PD undertook a battery of neurologic and functional tests in their optimally medicated state. The tests included Tinetti, Berg, Timed Up and Go, Functional Reach, and the Physiological Profile Assessment of Falls Risk; the latter assessment includes physiologic tests of visual function, proprioception, strength, cutaneous sensitivity, reaction time, and postural sway. Falls were recorded prospectively over 6 months. ----- ----- Results: Forty-eight percent of participants reported a fall and 24% more than 1 fall. In the multivariate model, a combination of the Unified Parkinson's Disease Rating Scale (UPDRS) total score, total freezing of gait score, occurrence of symptomatic postural orthostasis, Tinetti total score, and extent of postural sway in the anterior-posterior direction produced the best sensitivity (78%) and specificity (84%) for predicting falls. From the UPDRS items, only the rapid alternating task category was an independent predictor of falls. Reduced peripheral sensation and knee extension strength in fallers contributed to increased postural instability. ----- ----- Conclusions: Falls are a significant problem in optimally medicated early-stage PD. A combination of both disease-specific and balance- and mobility-related measures can accurately predict falls in individuals with PD.

Learning articulated motion structures with Bayesian Networks

This paper presents a general methodology for learning articulated motions that, despite having non-linear correlations, are cyclical and have a defined pattern of behavior Using conventional algorithms to extract features from images, a Bayesian classifier is applied to cluster and classify features of the moving object. Clusters are then associated in different frames and structure learning algorithms for Bayesian networks are used to recover the structure of the motion. This framework is applied to the human gait analysis and tracking but applications include any coordinated movement such as multi-robots behavior analysis.