Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 257

This bibliography lists 331 reports, articles and other documents introduced into the NASA scientific and technical information system in March 1984

Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 134)

This special bibliography lists 301 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System in October 1974

Investigation and Quantification of FES Exercise – Isometric Electromechanics and Perceptions of Its Usage as an Exercise Modality for Various Populations

Functional Electrical Stimulation (FES) is the triggering of muscle contraction by use of an electrical current. It can be used to give paralyzed individuals several health benefits, through allowing artificial movement and exercise. Although many FES devices exist, many aspects require innovation to increase usability and home translation. In addition, the effect of changing electrical parameters on limb biomechanics is not entirely understood; in particular with regards to stimulation duty cycle. This thesis has two distinct components. In the first (public health component), interview studies were conducted to understand several issues related to FES technology enhancement, implementation and home translation. In the second (computational biomechanics component), novel signal processing algorithms were designed that can be used to measure mechanical responses of muscles subjected to electrical stimulation. These experiments were performed by changing duty cycle and measuring its effect on quadriceps-generated knee torque. The studies of this thesis have presented several ideas, toolkits and results which have the potential to guide future FES biomechanics studies and the translatability of systems into regular usage for patients. The public health studies have provided conceptual frameworks upon which FES may be used in the home by patients. In addition, they have elucidated a range of issues that need to be addressed should FES technology reach its true potential as a therapy. The computational biomechanics studies have put forward novel data analysis techniques which may be used for understanding how muscle responds to electrical stimulation, as measured via torque. Furthermore, the effect of changing the electrical stimulation duty cycle on torque was successfully described, adding to an understanding of how electrical stimulation parameter modulation can influence joint biomechanics

Proceedings of the 11th International Conference on Kinanthropology

The 11th International Conference on Kinantropology was held on the Nov 29 – Dec 1, 2017 in Brno and was organized by the Faculty of Sports Studies, Masaryk University and the Faculty of Kinesiology, University of Zagreb. This year was divided into several themes: sports medicine, sport and social science, sport training, healthy lifestyle and healthy ageing, sports management, analysis of human movement. Part of the conference was also a symposium Atletika and Ortoreha that gathered specialists in physiotherapy

Human metabolic allometry from basal to maximal ambulatory states, including load carriage and its distribution

Whole-body metabolic rate is strongly linked with body size, as it is primarily determined by both the number of cells within the body and their tissue-specific metabolic rates. For these reasons alone there will always be some inter-individual variations in metabolism, at any given metabolic intensity. While variations in body mass can explain the majority of these differences between individuals, it still remains difficult to remove the effect of body mass from metabolic data, as the relationship between both variables does not scale by a one-to-one ratio. Accordingly, the ubiquitous mass-normalisation approach is ineffective at this task (mL.kg-1.min-1). Therefore, an alternative scaling method was required so that metabolic rate can be both described and analysed with minimal error. In animals, basal metabolic rate scales by a non-linear, allometric regression against body body mass, and can be described using the body-mass exponent, mass 0.67. However, in humans, the nature1 of the scaling relationship remains unconfirmed, with both linear (first-order polynomial) and non-linear (allometric) scaling approaches used by researchers. An often overlooked issue with this situation is that the predictive error between both models increases as the mass range widens. Accordingly, the primary aim within this series of investigation was to determine which scaling model was more appropriate to describe the relationship between metabolic rate and body mass in humans..