I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

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Biomechanics And Motor Control Of Human Movement

: This thesis applies neural network feature selection techniques to multivariate time series data to improve prediction of a target time series. Two approaches to feature selection are used. First, a subset enumeration method is used to determine which financial indicators are most useful for aiding in prediction of the S&P 500 futures daily price. The candidate indicators evaluated include RSI, Stochastics and several moving averages. Results indicate that the Stochastics and RSI indicators result in better prediction results than the moving averages. The second approach to feature selection is calculation of individual saliency metrics. A new decision boundary-based individual saliency metric, and a classifier independent saliency metric are developed and tested. Ruck's saliency metric, the decision boundary based saliency metric, and the classifier independent saliency metric are compared for a data set consisting of the RSI and Stochastics indicators as well as delayed closing price values. The decision based metric and the Ruck metric results are similar, but the classifier independent metric agrees with neither of the other metrics. The nine most salient features, determined by the decision boundary based metric, are used to train a neural network and the results are presented and compared to other published results. (AN)

/pdf/nonlinear-time-series-analysis-1j3a35n4y3.pdf

Nonlinear Time Series Analysis.

Exercise Physiology: Energy, Nutrition and Human Performance

With efficiencies derived from evolution, growth and learning, humans are very well-tuned for locomotion. Metabolic energy used during walking can be partly replaced by power input from an exoskeleton, but is it possible to reduce metabolic rate without providing an additional energy source? This would require an improvement in the efficiency of the human-machine system as a whole, and would be remarkable given the apparent optimality of human gait. Here we show that the metabolic rate of human walking can be reduced by an unpowered ankle exoskeleton. We built a lightweight elastic device that acts in parallel with the user's calf muscles, off-loading muscle force and thereby reducing the metabolic energy consumed in contractions. The device uses a mechanical clutch to hold a spring as it is stretched and relaxed by ankle movements when the foot is on the ground, helping to fulfil one function of the calf muscles and Achilles tendon. Unlike muscles, however, the clutch sustains force passively. The exoskeleton consumes no chemical or electrical energy and delivers no net positive mechanical work, yet reduces the metabolic cost of walking by 7.2 ± 2.6% for healthy human users under natural conditions, comparable to savings with powered devices. Improving upon walking economy in this way is analogous to altering the structure of the body such that it is more energy-effective at walking. While strong natural pressures have already shaped human locomotion, improvements in efficiency are still possible. Much remains to be learned about this seemingly simple behaviour.

/pdf/reducing-the-energy-cost-of-human-walking-using-an-unpowered-16re45bn85.pdf

Reducing the energy cost of human walking using an unpowered exoskeleton

Over time, leg prostheses have improved in design, but have been incapable of actively adapting to different walking velocities in a manner comparable to a biological limb. People with a leg amputation using such commercially available passive-elastic prostheses require significantly more metabolic energy to walk at the same velocities, prefer to walk slower and have abnormal biomechanics compared with non-amputees. A bionic prosthesis has been developed that emulates the function of a biological ankle during level-ground walking, specifically providing the net positive work required for a range of walking velocities. We compared metabolic energy costs, preferred velocities and biomechanical patterns of seven people with a unilateral transtibial amputation using the bionic prosthesis and using their own passive-elastic prosthesis to those of seven non-amputees during level-ground walking. Compared with using a passive-elastic prosthesis, using the bionic prosthesis decreased metabolic cost by 8 per cent, increased trailing prosthetic leg mechanical work by 57 per cent and decreased the leading biological leg mechanical work by 10 per cent, on average, across walking velocities of 0.75–1.75 m s−1 and increased preferred walking velocity by 23 per cent. Using the bionic prosthesis resulted in metabolic energy costs, preferred walking velocities and biomechanical patterns that were not significantly different from people without an amputation.

https://royalsocietypublishing.org/doi/pdf/10.1098/rspb.2011.1194

Bionic ankle–foot prosthesis normalizes walking gait for persons with leg amputation

The metabolic cost of walking is determined by many mechanical tasks, but the individual contribution of each task remains unclear. We hypothesized that the force generated to support body weight a...

Independent metabolic costs of supporting body weight and accelerating body mass during walking

The recent competitive successes of a bilateral, transtibial amputee sprint runner who races with modern running prostheses has triggered an international controversy regarding the relative functio...

/pdf/the-fastest-runner-on-artificial-legs-different-limbs-4fkljey6tx.pdf

The fastest runner on artificial legs: different limbs, similar function?

During bouncing gaits such as hopping and running, leg muscles generate force to enable elastic energy storage and return primarily from tendons and, thus, demand metabolic energy. In an effort to reduce metabolic demand, we designed two elastic leg exoskeletons that act in parallel with the wearer's legs; one exoskeleton consisted of a multiple leaf (MLE) and the other of a single leaf (SLE) set of fiberglass springs. We hypothesized that hoppers, hopping on both legs, would adjust their leg stiffness while wearing an exoskeleton so that the combination of the hopper and exoskeleton would behave as a linear spring-mass system with the same total stiffness as during normal hopping. We also hypothesized that decreased leg force generation while wearing an exoskeleton would reduce the metabolic power required for hopping. Nine subjects hopped in place at 2.0, 2.2, 2.4, and 2.6 Hz with and without an exoskeleton while we measured ground reaction forces, exoskeletal compression, and metabolic rates. While wearing an exoskeleton, hoppers adjusted their leg stiffness to maintain linear spring-mass mechanics and a total stiffness similar to normal hopping. Without accounting for the added weight of each exoskeleton, wearing the MLE reduced net metabolic power by an average of 6% and wearing the SLE reduced net metabolic power by an average of 24% compared with hopping normally at frequencies between 2.0 and 2.6 Hz. Thus, when hoppers used external parallel springs, they likely decreased the mechanical work performed by the legs and substantially reduced metabolic demand compared with hopping without wearing an exoskeleton.

Leg exoskeleton reduces the metabolic cost of human hopping

The biomechanical and metabolic demands of human running are distinctly affected by velocity and body weight. As runners increase velocity, ground reaction forces (GRF) increase, which may increase the risk of an overuse injury, and more metabolic power is required to produce greater rates of muscular force generation. Running with weight support attenuates GRFs, but demands less metabolic power than normal weight running. We used a recently developed device (G-trainer) that uses positive air pressure around the lower body to support body weight during treadmill running. Our scientific goal was to quantify the separate and combined effects of running velocity and weight support on GRFs and metabolic power. After obtaining this basic data set, we identified velocity and weight support combinations that resulted in different peak GRFs, yet demanded the same metabolic power. Ideal combinations of velocity and weight could potentially reduce biomechanical risks by attenuating peak GRFs while maintaining aerobic and neuromuscular benefits. Indeed, we found many combinations that decreased peak vertical GRFs yet demanded the same metabolic power as running slower at normal weight. This approach of manipulating velocity and weight during running may prove effective as a training and/or rehabilitation strategy.

/pdf/effects-of-velocity-and-weight-support-on-ground-reaction-2f37ajstdw.pdf

Alena M. Grabowski

Papers

Bionic ankle–foot prosthesis normalizes walking gait for persons with leg amputation

Independent metabolic costs of supporting body weight and accelerating body mass during walking

The fastest runner on artificial legs: different limbs, similar function?

Leg exoskeleton reduces the metabolic cost of human hopping

Effects of velocity and weight support on ground reaction forces and metabolic power during running.