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Margin of stability (MOS) is considered a measure of mechanical gait stability. Due to broad application of treadmills in gait assessment experiments, we aimed to determine if walking on a treadmill vs. overground would affect MOS during three speed-matched conditions. Eight healthy young participants walked on a treadmill and overground at Slow, Preferred, and Fast speed-matched conditions. The mean and variability (standard deviation) of the MOS in anterior-posterior and mediolateral directions at heel contact were calculated. Anterior-posterior and mediolateral mean MOS values decreased with increased speed for both overground and treadmill; although mediolateral mean MOS was always wider on the treadmill compared to overground. Due to lack of optic flow and different proprioceptive inputs during treadmill walking, subjects may employ strategies to increase their lateral stability on treadmill compared to overground. Anterior-posterior MOS variability increased with speed overground, while it did not change on treadmill, which might be due to the fixed speed of treadmill. Whereas, lateral variability on both treadmill and overground was U-shaped. Walking at preferred speed was less variable (may be interpreted as more stable) laterally, compared to fast and slow speeds. Caution should be given when interpreting MOS between modes and speeds of walking. As sagittal plane walking is functionally unstable, this raises the consideration as to the meaningfulness of using MOS as a global measure of gait stability in this direction.

The metabolic rate of walking can be reduced by applying a constant forward force at the center of mass. It has been shown that the metabolically optimal constant force magnitude minimizes propulsion ground reaction force at the expense of increased braking. This led to the hypothesis that selectively assisting propulsion could lead to greater benefits. We used a robotic waist tether to evaluate the effects of forward forces with different timings and magnitudes. Here, we show that it is possible to reduce the metabolic rate of healthy participants by 48% with a greater efficiency ratio of metabolic cost reduction per unit of net aiding work compared with other assistive robots. This result was obtained using a sinusoidal force profile with peak timing during the middle of the double support. The same timing could also reduce the metabolic rate in patients with peripheral artery disease. A model explains that the optimal force profile accelerates the center of mass into the inverted pendulum movement during single support. Contrary to the hypothesis, the optimal force timing did not entirely coincide with propulsion. Within the field of wearable robotics, there is a trend to use devices to mimic biological torque or force profiles. Such bioinspired actuation can have relevant benefits; however, our results demonstrate that this is not necessarily optimal for reducing metabolic rate.

Marker occlusion during camera-based movement analysis is common. Different interpolation techniques are available for estimating location of missing marker trajectories.What is the effect of gap location and interpolation technique on linear and nonlinear measures for a given kinematic time series?Kinematic data were recorded during motor-assisted elliptical training and treadmill walking. Gap-filling techniques (i.e., Cubic, Makima, Autoregressive, Nearest Neighbor, and No Interpolation) and gap locations experimentally applied to each cycle across initially complete time series (Gap 1: local minimum and maximum peaks; Gap 2: maximum peaks; Gap 3: maximum peaks at negative slope; Gap 4: random locations) were examined during linear (Maxima and Minima joint angles) and nonlinear [maximum Lyapunov exponent (LyE)] measures.Gap-filling technique and gap location influenced values calculated for linear and nonlinear measures of joint motions. When referenced to the gold standard (original data series without gaps), across all joints studied the average % error of Maxima and Minima joint angles and LyE % error were lower when applying Cubic, Makima, Autoregressive, and Nearest Neighbor techniques compared to No Interpolation (p 0.0001). The % error of Maxima joint angles was lower for Gaps 1, 3, and 4 compared to Gap 2 (p = 0.0003), while % error of Minima joint angles was lower for Gaps 2 and 3, compared to Gaps 1 and 4 (p 0.0001). An interaction between gap-filling technique and gap location was identified for LyE % error, in which Gap 4 % error was significantly greater during No Interpolation compared to other gap-filling techniques (p 0.0001).Findings can guide selection of appropriate techniques to manage missing kinematic data points in camera-based motion analysis time series. Gap-filling techniques significantly reduced error in calculating select linear and nonlinear measures of variability, with Cubic most consistently resulting in the greatest reduction in error.

The purpose of this research was to compare children's lower extremity muscle activity and kinematics while walking at fast pace and training at fast speeds with and without motor-assistance on a pediatric-modified motor-assisted elliptical. Twenty-one children without disabilities were recruited and fifteen completed all three training conditions at self-selected fast pace. Repeated-measures ANOVAs identified muscle demand (peak, mean, duration) differences across device conditions and fast walking. Root mean square error compared overall kinematic profiles and statistical parametric mapping identified kinematic differences between conditions. Motor-assisted training reduced lower extremity muscle demands compared to training without the motor's assistance (16 of 21 comparisons) and to fast walking (all but one comparison). Training without the motor's assistance required less muscle effort than fast walking (16 of 21 comparisons). Kinematic differences between device conditions and fast walking were greater distally (thigh, knee, ankle) than proximally (trunk, pelvis, hip). In summary, transitioning from training with to without the motor's assistance promoted progressively greater activity across the lower extremity muscles studied, with sagittal plane kinematic changes most apparent at the distal joints. Our findings highlight how motor-assistance can be manipulated to customize physiologic challenges to lower extremity muscles prior to fast overground walking.

Purpose: Falls are one of the main causes of injuries in older adults. This study evaluated a low-cost footswitch device that was designed to measure gait variability and investigates whether there are any relationships between variability metrics and clinical balance tests for individuals with a history of previous falls. Methods: Sixteen older adults completed a history of falls questionnaire, three functional tests related to fall risk, and walked on a treadmill with the footswitch device. We extracted the stride times from the device and applied two nonlinear variability analyses: coefficient of variation and detrended fluctuation analysis. Results: The temporal variables and variability metrics from the footswitch device correlated with gold-standard measurements based on ground reaction force data. One variability metric (detrended fluctuation analysis) showed a significant relationship with the presence of past falls with a sensitivity of 43%. Conclusion: This feasibility study demonstrates the basis for using low-cost footswitch devices to predict fall risk.

Walking on different grades becomes challenging on energetic and muscular levels compared to level walking. While it is not possible to eliminate the cost of raising or lowering the centre of mass (COM), it could be possible to minimize the cost of distal joints with shoes that offset downhill or uphill grades. We investigated the effects of shoe outsole geometry in 10 participants walking at 1 m s −1 on downhill, level and uphill grades. Level shoes minimized metabolic rate during level walking ( P second-order effect < 0.001). However, shoes that entirely offset the (overall) treadmill grade did not minimize the metabolic rate of walking on grades: shoes with a +3° (upward) inclination minimized metabolic rate during downhill walking on a −6° grade, and shoes with a −3° (downward) inclination minimized metabolic rate during uphill walking on a +6° grade ( P interaction effect = 0.023). Shoe inclination influenced (distal) ankle joint parameters, including soleus muscle activity, ankle moment and work rate, whereas treadmill grade influenced (whole-body) ground reaction force and COM work rate as well as (distal) ankle joint parameters including tibialis anterior and plantarflexor muscle activity, ankle moment and work rate. Similar modular footwear could be used to minimize joint loads or assist with walking on rolling terrain.

This research is aimed toward using variable input speed for triple-objective optimization of kinematic characteristics of a Geneva wheel mechanism. High-tech optimization methods including genetic algorithm (GA) and imperialist competitive algorithm (ICA) are used in this study. The objective functions in both methods are magnitude of the maximum output angular velocity, magnitude of the maximum output angular acceleration as well as magnitude of the maximum output angular jerk of driven wheel. The motion equations of Geneva mechanism are first extracted with their boundary conditions determined. Then, above objective functions are minimized using the considered algorithms. Utilization of the input velocity may contribute to improve output kinematic characteristics of the mechanism.

This paper is aimed to study the behavior of sandwich panels made of Aluminum face sheet and Aluminum corrugated core under impact loading. Sandwich panels with square and triangular corrugated cores of two different heights are constructed and the effect of corrugated geometry on the level of absorbed energy as well as the panel strength are investigated. Drop Hammer by a cylindrical impactor with the weight of 25 kg is applied for exerting the impact. Acceleration, velocity, and displacement of impactor as well as the absorbed energy are evaluated throughout the test. The damage mechanisms include the buckling of core walls, separation of core from surface sheets, and formation of plastic hinges in the core plate. The results show that panel height and the geometry of its core play an important role in the energy absorbability impact strength, as the panels with more height have higher energy absorbability and panels with square core have higher impact strength than ones with triangular core. At the end, the numerical method confirms the Experimental method.

The sandwich structures with aluminum foam core and metal surfaces have widespread use in the absorption of energy, because they are light weighted with high performance in dissipating energy. The cell structure of the foam core is subjected to plastic deformation in the constant compression level that absorbs a lot of kinetic energy before destruction of the structure. In this research, experimental tests of low-velocity impact on the sandwich structure by a drop machine are simulated by LS-DYNA software. Numerical results are obtained for different velocities and weights of projectile on samples of aluminum foam core sandwich panels with relative density (the ratio of the density of aluminum foam to the density of solid aluminum) of 18, 23, and 27. The results are compared with experimental results which reveal a good conformity. As well, from the numerical simulations, the effect of weight, velocity and energy of the projectile and the density of the foam core on the global deformation and energy loss rate of projectile have been studied.

The sandwich panel structures with aluminum foam core and metal surfaces have light weight with high performance in dispersing energy. This has led to their widespread use in the absorption of energy. The cell structure of foam core is subjected to plastic deformation in the constant tension level that absorbs a lot of kinetic energy before destruction of the structure. In this research, by making samples of aluminum foam core sandwich panels with aluminum surfaces, experimental tests of low velocity impact by a drop machine are performed for different velocities and weights of projectile on samples of sandwich panels with aluminum foam core with relative density of 18%, 23%, and 27%. The output of device is acceleration‐time diagram which is shown by an accelerometer located on the projectile. From the experimental tests, the effect of weight, velocity and energy of the projectile and density of the foam on the global deformation, and energy decrease rate of projectile have been studied. The results of the experimental testes show that by increasing the density of aluminum foam, the overall impression is reduced and the slop of energy loss of projectile increases. Also by increasing the velocity of the projectile, the energy loss increases.

Analytical and finite element simulations are used to predict the effect of core density on the energy absorption of composite sandwich panels under low-velocity impact. The composite sandwich panel contains two facesheets and a foam-filled corrugated core. Analytical model is defined as a two degree-of-freedom system based on equivalent mass, spring, and dashpot to predict the local and global deformation response of a simply supported panel. The results signify a good agreement between analytical and numerical predictions.

Motion capture laboratories can measure multiple variables at high frame rates, but we can only measure the average metabolic rate of a stride using respiratory measurements. Biomechanical simulations with equations for calculating metabolic rate can estimate the time profile of metabolic rate within the stride cycle. A variety of methods and metabolic equations have been proposed, including metabolic time profile estimations based on joint parameters. It is unclear whether differences in estimations are due to differences in experimental data or due to methodological differences. This study aimed to compare two methods for estimating the time profile of metabolic rate, within a single dataset. Knowledge about the consistency of different methods could be useful for applications such as detecting which part of the gait cycle causes increased metabolic cost in patients. Here we compare estimations of metabolic rate time profiles using a musculoskeletal and a joint-space method. The musculoskeletal method was driven by kinematics and electromyography data and used muscle metabolic rate equations, whereas the joint-space method used metabolic rate equations based on joint parameters. Both estimations of changes in stride average metabolic rate correlated significantly with large changes in indirect calorimetry from walking on different grades showing that both methods accurately track changes. However, estimations of changes in stride average metabolic rate did not correlate significantly with more subtle changes in indirect calorimetry due to walking with different shoe inclinations, and both the musculoskeletal and joint-space time profile estimations did not correlate significantly with each other except in the most downward shoe inclination. Estimations of the relative cost of stance and swing matched well with previous simulations with similar methods and estimations from experimental perturbations. Rich experimental datasets could further advance time profile estimations. This knowledge could be useful to develop therapies and assistive devices that target the least metabolically economic part of the gait cycle., Author summary Respiratory oxygen consumption measurements allow recording of the average metabolic cost of walking, but the slow rate of these measurements prevents assessing which part of the gait cycle has the highest metabolic cost. Simulation methods allow estimation of the time profile of metabolic cost within the gait cycle. We compared estimations of the metabolic cost of walking using a method that is based on kinematic and electromyography recordings from participants in conjunction with muscle metabolic rate equations and a method based on joint kinematics and kinetics. While both methods are able to accurately estimate large changes in the average metabolic cost from walking on different inclinations, the time profiles estimated by the two methods are different, indicating that estimations of the time profile of metabolic cost are dependent on the estimation method. Both estimation methods matched well with the results from experimental perturbation studies that suggest that the metabolic cost of the swing phase is approximately 10% to 20% of the metabolic cost of the entire gait cycle. Advances in estimations of the time profile of metabolic cost could lead to practical applications such as designing rehabilitation robots that assist specifically during the phase with the highest metabolic cost.

Most of the real time chemical process loops are unstable in nature and designing a suitable controller for such systems are difficult than open loop stable processes. In this work, an attempt is made with a two degree of freedom setpoint weighted PID controller tuning procedure for a class of unstable systems using the recent heuristic algorithms such as Particle Swarm Optimization and Bacterial Foraging Optimization. The problem considered in this study is to aptly tune the controller in order to enhance the overall closed loop performance. A novel objective function proposed in this study is used to monitor the heuristic algorithms in order to get the optimal controller parameters like Kp, Ki, Kd, and α with minimized iteration number. The proposed method is validated with a simulation study and this helps to accomplish enhanced system performance such as smooth reference tracking, satisfactory disturbance rejection, and error minimization for a class of unstable systems

This paper is aimed to study the behavior of sandwich panels made of Aluminum face sheet and Aluminum corrugated core under impact loading. Sandwich panels with square and triangular honeycombs of two different heights are constructed and the effect of honeycomb geometry on the level of absorbed energy as well as the panel strength are investigated. Drop Hammer apparatus by a cylindrical impactor with the weight of 25 kg is applied for exerting the impact. Acceleration, velocity, and displacement of impactor as well as the absorbed energy are evaluated throughout the test. The damage mechanisms include the buckling of core walls, separation of core from surface sheets, and formation of plastic hinges in the core plate. The results show that panel height and the geometry of its core play an important role on the impact strength, as the panels with more height have higher energy absorbability and panels with square core have higher impact strength than ones with triangular core.

This paper proposes a novel method to tune the I-PD controller structure for the time-delayed unstable process (TDUP) using Bacterial Foraging Optimization (BFO) algorithm. The tuning process is focussed to search the optimal controller parameters ( 𝐾 𝑝 , 𝐾 𝑖 , 𝐾 𝑑 ) by minimising the multiple objective performance criterion. A comparative study on various cost functions like Integral of Squared Error (ISE), Integral of Absolute Error (IAE), Integral of Time-weighted Squared Error (ITSE), and Integral of Time weighted Absolute Error (ITAE) have been attempted for a class of TDUP. A simulation study for BFO-based I-PD tuning has been done to validate the performance of the proposed method. The results show that the tuning approach is a model independent approach and provides enhanced performance for the setpoint tracking with improved time domain specifications.