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Swimming in aquatic environments
Published in R. C. Richard Davison, Paul M. Smith, James Hopker, Michael J. Price, Florentina Hettinga, Garry Tew, Lindsay Bottoms, Sport and Exercise Physiology Testing Guidelines: Volume I – Sport Testing, 2022
Despite the unique challenges posed by water, a number of physiological parameters can be measured. These include blood lactate, heart rate, perceptual measures, deep body temperature, expired gas (mainly for the determination of oxygen consumption [V̇O2]) and swimming economy. Additionally, specialised cameras, inertial measurement units, electromyography (EMG) equipment and measuring active drag (MAD) systems can be used for biomechanical analyses.
Functional Rehabilitation
Published in James Crossley, Functional Exercise and Rehabilitation, 2021
There are several branches of biomechanics. Kinematics is the study of the relative movement of body segments through space. Kinetics investigates the forces that produce, arrest and modify motion, analyzing biomechanical forces like momentum, inertia, mechanical advantage and leverage. Ostokinematics and arthokinematics apply biomechanical principles to the movement of bones and joints. Kinematics – the study of human motionKinetics – the study of forces that produce, arrest and modify motionOsteokinematics – the study of bone motionArthrokinematics – the study of joint motion Biomechanics is frequently applied to enhance performance, improve safety and prevent injury. Biomechanists analyze film footage using mathematical models to find the most effective way to perform any task or skill – calculating the best way to sit, stand, walk, run, jump and throw, how we should organize movement and activate muscle. Deviation from correct form and technique is considered dysfunctional – a source of inefficiency, decreased performance, stress, strain and increased risk injury.
Biomechanics of Brain Injury in Athletes
Published in Mark R. Lovell, Ruben J. Echemendia, Jeffrey T. Barth, Michael W. Collins, Traumatic Brain Injury in Sports, 2020
Biomechanics is simply the application of the principles of mechanics to biological systems – most often the human system. Mechanics is that branch of physics dealing with the relationship between forces and movement. It encompasses related fields called statics, dynamics and kinematics. The head injury of interest here is that which occurs as a result of impact. Hence the biomechanics of head injury involves the study of the relationship between the forces that are developed or applied and the way the head moves during impact that are associated with head injury.
Assessment of spasticity: an overview of systematic reviews
Published in Physical Therapy Reviews, 2022
Saleh M. Aloraini, Emtenan Y. Alyosuf, Lamya I. Aloraini, Mishal M. Aldaihan
In the absence of a gold standard for assessing spasticity, the Ashworth scales are the most commonly used measures for spasticity. The Ashworth scales are easily used and require no special training or equipment. However, concerns regarding their validity and reliability still remain. Therefore, numerous efforts have been spent to develop biomechanical tools that can provide a proxy for spasticity in the clinical setting. However, to date, the psychometric evidence of biomechanical methods for assessing spasticity is lacking. Moreover, biomechanical tools often require specialized training to improve their clinical utility. Nonetheless, biomechanical tools still offer the best approach for assessing spasticity as they provide a quantifiable measure of spasticity that is reliable and sensitive. This is especially true for biomechanical measures when combined with neurophysiological measures [2, 5, 13]. Thus, future studies are needed that aim to develop an easy-to-use, valid and reliable biomechanical measure of spasticity.
The science of biomechanics can promote dancers’ injury prevention strategies
Published in Physical Therapy Reviews, 2021
Aspasia Fotaki, Athanasios Triantafyllou, Georgios Papagiannis, Sophia Stasi, Papathanasiou Georgios, Savvidou Olga, Charilaos K. Tsolakis, Panayiotis Koulouvaris
Biomechanics is the science of human movement that studies the body’s mechanical structure and function, providing data on muscular activation, and its motion characteristics [38–42]. Kneeland introduced dancing principles and techniques in the early 1960s and researchers of 1970s first created specific tools and research methodology which have evolved to the present training strategy and up-to-date measurement equipment [31]. Several investigations have studied different interest fields included jumping efficiency [43] alignment in movements such as ‘demi and grand plié releve, passé, degage, rond de jambe, grand battement, arm movements, turns, elevation work and falls’. Every movement was examined for its closed and opened kinetic chain, separately for each lower extremity, pelvic, and spine muscles [26,44,45].
General method for automated feature extraction and selection and its application for gender classification and biomechanical knowledge discovery of sex differences in spinal posture during stance and gait
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2021
Carlo Dindorf, Jürgen Konradi, Claudia Wolf, Bertram Taetz, Gabriele Bleser, Janine Huthwelker, Philipp Drees, Michael Fröhlich, Ulrich Betz
Human biomechanics is a complex and multivariate matter. To approach an understanding of its complexity, multiple parameters and modalities may have to be taken into account, which often results in multiple related tables of data (relational data). Modern movement tracking systems enable the collection of large, multivariate datasets (Phinyomark et al. 2018). However, classical inferences based static and hypothesis testing methods show limited capabilities in properly analyzing these huge amounts of data and included parameters (Bzdok et al. 2018). In order to generate actual benefit from the data that we can now capture, exploratory approaches, including machine learning methods such as automated feature extraction, selection and pattern recognition that can simultaneously consider a large amount of data and parameters, including their interactions, are gaining importance. Therefore, we propose a generally applicable ensemble feature selection approach in this work.