Development of Muscle Mass: How Much Is Optimum for Performance?

Young, Warren; Talpey, Scott; Bartlett, Rogan; Lewis, Mitchell; Mundy, Stephanie; Smyth, Andrew; Welsh, Tim

doi:10.1519/ssc.0000000000000443

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…Resistance training provides several health benefits related to enhancing muscle strength, reversing muscle loss, reducing body fat, improving cardiovascular health, enhancing mental health and increasing bone mineral density [1][2][3][4][5][6]. Accordingly, resistance training should be considered essential for the whole population, but it is even more relevant when the target is the transference into some specific activity or daily life tasks [7,8], injury prevention [9] or maximizing sports performance [10].…”

Section: Introductionmentioning

confidence: 99%

Electromyographic activity in deadlift exercise and its variants. A systematic review

2020

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The main purpose of this review was to systematically analyze the literature concerning studies which have investigated muscle activation when performing the Deadlift exercise and its variants. This study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Statement (PRISMA). Original studies from inception until March 2019 were sourced from four electronic databases including PubMed, OVID, Scopus and Web of Science. Inclusion criteria were as follows: (a) a cross-sectional or longitudinal study design; (b) evaluation of neuromuscular activation during Deadlift exercise or variants; (c) inclusion of healthy and trained participants, with no injury issues at least for six months before measurements; and (d) analyzed "sEMG amplitude", "muscle activation" or "muscular activity" with surface electromyography (sEMG) devices. Major findings indicate that the biceps femoris is the most studied muscle, followed by gluteus maximus, vastus lateralis and erector spinae. Erector spinae and quadriceps muscles reported greater activation than gluteus maximus and biceps femoris muscles during Deadlift exercise and its variants. However, the Romanian Deadlift is associated with lower activation for erector spinae than for biceps femoris and semitendinosus. Deadlift also showed greater activation of the quadriceps muscles than the gluteus maximus and hamstring muscles. In general, semitendinosus muscle activation predominates over that of biceps femoris within hamstring muscles complex. In conclusion 1) Biceps femoris is the most evaluated muscle, followed by gluteus maximus, vastus lateralis and erector spinae during Deadlift exercises; 2) Erector spinae and quadriceps muscles are more activated than gluteus maximus and biceps femoris muscles within Deadlift exercises; 3) Within the hamstring muscles complex, semitendinosus elicits slightly greater muscle activation than biceps femoris during Deadlift exercises; and 4) A unified criterion upon methodology is necessary in order to report reliable outcomes when using surface electromyography recordings.

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Section: Introductionmentioning

confidence: 99%

Electromyographic activity in deadlift exercise and its variants. A systematic review

2020

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“…However it should be noted, that not all sports necessarily benet from powerliftingtype of strength training, i.e. the strength gains do not necessarily transfer to improvements in sports performance [532,778,905,906]. For example, sports requiring explosive power such as boxing [498,765], taekwondo [485], track and eld sprinting [307,500], and mixed martial arts (MMA) [317,367,416,433,472,888], often bene- lifting techniques [171].…”

Section: Deep Learning Enabled Exercise and Strength Trainingmentioning

confidence: 99%

Precision strength training: Data-driven artificial intelligence approach to strength and conditioning

Teikari¹,

Pietrusz²

2021

Preprint

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In strength training, personalised strength training (autoregulation) approaches have been used to individualise exercise programs with monitoring an for dynamic adjustment based on their responses to training. While this transition from tradition-based training to evidence-based training framework has been an improvement in training practices, we argue that the future of strength training will also incorporate deep learning models powered by data. We refer to this data-driven framework as precision strength training inspired by the similar modeling frameworks used in precision medicine. In contrast to current personalised training in which the acquired athlete data is often subject to human expert decision-making, we are anticipating the rise of human-in-the-loop systems with an augmented coach who will be doing decisions collaboratively with the machine. Similar to other precision frameworks, such as precision health, we envision such a future to take decades to be realised and we focus here on practical short-term targets on a way to long-term realisation. In this chapter, we will review the measurement technology needed for continuous data acquisition from an individual during training/physical activity, how to acquire these datasets for the development of such systems and, how a proof-of-concept system could be developed for powerlifting training with applicability to general strength and conditioning (S&C) and physical rehabilitation purposes. Additionally, we will evaluate how the user experience (UX) of the system feedback and visualisation could be designed.

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Development of Muscle Mass: How Much Is Optimum for Performance?

Cited by 2 publications

References 14 publications

Electromyographic activity in deadlift exercise and its variants. A systematic review

Electromyographic activity in deadlift exercise and its variants. A systematic review

Precision strength training: Data-driven artificial intelligence approach to strength and conditioning

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