Power requirements and mechanical efficiency of treadmill walking

The instantaneous energy levels of body segments are computed from kinematic measurements on a level treadmill at various speeds with freely chosen step rates and a constant speed with different imposed step rates. The changes in the energy levels of segments are combined to compute the average work rate required to accelerate the total body (positive internal work). This work is compared to total metabolic power consumption to obtain a minimal estimate of mechanical efficiency. The efficiency increases rapidly from 9% to 0.84 m/sec to a maximum of 23% at 1.70 m/sec. Thereafter, the efficiency slowly decreases with speed to 18% at 2.35 m/sec. When different step rates are imposed at one constant speed, the average positive work rate remains constant. This work rate level is identical to that required for walking at the same speed with self-determined (free) step rate. Thus, maximum gross efficiency results at the free step rate.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24523/1/0000802.pd

Kinematic prediction of intersegment loads and power at the joints of the leg in walking

The left and right ground reactions are predicted from computed absolute motion data with the aid of some simple assumptions regarding symmetry between the forward shear forces during the double support phase and the rate at which support is transferred from one leg to the other. The computed ground forces are then used to evaluate forces, moments and power at the joints of the lower limb. The power supplied at the joints of the lower limbs is found to agree well with the power required to increase the energy level of the body.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24573/1/0000855.pd

Computer generation of human gait kinematics

The paper describes a computer program that generates absolute motion variables of human gait from predetermined relative motions. Relative displacements are measured over a range of step rates during both free (self-determined step rate at different speeds) and forced (forced step rate at a constant speed) walking, converted into harmonic coefficients and stored in an array as a function of step rate. Only six variable identifiers need to be specified to compute any absolute variable or its derivatives at any desirable step rate. The paper displays some examples of measured relative motions and reconstituted absolute variables.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/23673/1/0000641.pd

Investigating the correlation between paediatric stride interval persistence and gross energy expenditure

<p>Abstract</p> <p>Background</p> <p>Stride interval persistence, a term used to describe the correlation structure of stride interval time series, is thought to provide insight into neuromotor control, though its exact clinical meaning has not yet been realized. Since human locomotion is shaped by energy efficient movements, it has been hypothesized that stride interval dynamics and energy expenditure may be inherently tied, both having demonstrated similar sensitivities to age, disease, and pace-constrained walking.</p> <p>Findings</p> <p>This study tested for correlations between stride interval persistence and measures of energy expenditure including mass-specific gross oxygen consumption per minute (<inline-formula><graphic file="1756-0500-3-47-i1.gif"/></inline-formula>), mass-specific gross oxygen cost per meter (<it>VO</it>₂) and heart rate (HR). Metabolic and stride interval data were collected from 30 asymptomatic children who completed one 10-minute walking trial under each of the following conditions: (i) overground walking, (ii) hands-free treadmill walking, and (iii) handrail-supported treadmill walking. Stride interval persistence was not significantly correlated with <inline-formula><graphic file="1756-0500-3-47-i1.gif"/></inline-formula> (p > 0.32), <it>VO</it>₂(p > 0.18) or HR (p > 0.56).</p> <p>Conclusions</p> <p>No simple linear dependence exists between stride interval persistence and measures of gross energy expenditure in asymptomatic children when walking overground and on a treadmill.</p

Do Humans Optimally Exploit Redundancy to Control Step Variability in Walking?

It is widely accepted that humans and animals minimize energetic cost while walking. While such principles predict average behavior, they do not explain the variability observed in walking. For robust performance, walking movements must adapt at each step, not just on average. Here, we propose an analytical framework that reconciles issues of optimality, redundancy, and stochasticity. For human treadmill walking, we defined a goal function to formulate a precise mathematical definition of one possible control strategy: maintain constant speed at each stride. We recorded stride times and stride lengths from healthy subjects walking at five speeds. The specified goal function yielded a decomposition of stride-to-stride variations into new gait variables explicitly related to achieving the hypothesized strategy. Subjects exhibited greatly decreased variability for goal-relevant gait fluctuations directly related to achieving this strategy, but far greater variability for goal-irrelevant fluctuations. More importantly, humans immediately corrected goal-relevant deviations at each successive stride, while allowing goal-irrelevant deviations to persist across multiple strides. To demonstrate that this was not the only strategy people could have used to successfully accomplish the task, we created three surrogate data sets. Each tested a specific alternative hypothesis that subjects used a different strategy that made no reference to the hypothesized goal function. Humans did not adopt any of these viable alternative strategies. Finally, we developed a sequence of stochastic control models of stride-to-stride variability for walking, based on the Minimum Intervention Principle. We demonstrate that healthy humans are not precisely “optimal,” but instead consistently slightly over-correct small deviations in walking speed at each stride. Our results reveal a new governing principle for regulating stride-to-stride fluctuations in human walking that acts independently of, but in parallel with, minimizing energetic cost. Thus, humans exploit task redundancies to achieve robust control while minimizing effort and allowing potentially beneficial motor variability

Movement consistency during repetitive tool use action

The consistency and repeatability of movement patterns has been of long-standing interest in locomotor biomechanics, but less well explored in other domains. Tool use is one of such a domain; while the complex dynamics of the human-tool-environment system have been approached from various angles, to date it remains unknown how the rhythmicity of repetitive tool-using action emerges. To examine whether the spontaneously adopted movement frequency is a variable susceptible to individual execution approaches or emerges as constant behaviour, we recorded sawing motion across a range of 14 experimental conditions using various manipulations. This was compared to free and pantomimed arm movements. We found that a mean (SD) sawing frequency of 2.0 (0.4) Hz was employed across experimental conditions. Most experimental conditions did not significantly affect the sawing frequency, signifying the robustness of this spontaneously emerging movement. Free horizontal arm translation and miming of sawing was performed at half the movement frequency with more than double the excursion distance, showing that not all arm movements spontaneously emerge at the observed sawing parameters. Observed movement frequencies across all conditions could be closely predicted from movement time reference data for generic arm movements found in the Methods Time Measurement literature, highlighting a generic biomechanical relationship between the time taken for a given distance travelled underlying the observed behaviour. We conclude that our findings lend support to the hypothesis that repetitive movements during tool use are executed according to generic and predictable musculoskeletal mechanics and constraints, albeit in the context of the general task (sawing) and environmental constraints such as friction, rather than being subject to task-specific control or individual cognitive schemata

Structural aspects of robot performance

http://deepblue.lib.umich.edu/bitstream/2027.42/8485/5/bad7928.0001.001.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/8485/4/bad7928.0001.001.tx

Kinematics and force control of robot grippers

http://deepblue.lib.umich.edu/bitstream/2027.42/6286/5/bac7426.0001.001.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/6286/4/bac7426.0001.001.tx

Effects of Geometric Parameters on Manipulator Dynamic Performance

Introduction With recent emphasis on high speed tasks for robots, dynamic performance has become one of the most significant design factors. Robot manipulators have highly nonlinear and coupled dynamics which produce complex behavior. Such behavior reflects factors such as interactions between the multiple joints, nonlinear effects arising from Coriolis and centripetal accelerations, and variation of generalized inertia with arm configuration. These factors are functions of both inertia and geometric quantities. One of the questions that has not been fully answered in robotics is, how does the kinematic structure of a manipulator (geometric and joint variable parameters) influence both its geometric and dynamic performance? Different aspects of this question have been investigated by various authors. Many researchers [1, 2, etc.] have studied the geometric relationships between the workspace volume and dexterity of the manipulator with its kinematic structure. They have developed functions which yield the size of the workspace and the locations of voids in the workspace. Other researchers Other efforts toward improving dynamic performance have been in developing control algorithms. In general, many as