Thank you very much for downloading biomechanics and motor control of human movement. Maybe you have knowledge that, people have search hundreds times for their favorite books like this biomechanics and motor control of human movement, but end up in infectious downloads. Rather than enjoying a good book with a cup of tea in the afternoon, instead they juggled with some malicious virus inside their laptop.

Biomechanics And Motor Control Of Human Movement

Throughout the sport-science and sports-medicine literature, the term "elite" subjects might be one of the most overused and ill-defined terms. Currently, there is no common perspective or terminology to characterize the caliber and training status of an individual or cohort. This paper presents a 6-tiered Participant Classification Framework whereby all individuals across a spectrum of exercise backgrounds and athletic abilities can be classified. The Participant Classification Framework uses training volume and performance metrics to classify a participant to one of the following: Tier 0: Sedentary; Tier 1: Recreationally Active; Tier 2: Trained/Developmental; Tier 3: Highly Trained/National Level; Tier 4: Elite/International Level; or Tier 5: World Class. We suggest the Participant Classification Framework can be used to classify participants both prospectively (as part of study participant recruitment) and retrospectively (during systematic reviews and/or meta-analyses). Discussion around how the Participant Classification Framework can be tailored toward different sports, athletes, and/or events has occurred, and sport-specific examples provided. Additional nuances such as depth of sport participation, nationality differences, and gender parity within a sport are all discussed. Finally, chronological age with reference to the junior and masters athlete, as well as the Paralympic athlete, and their inclusion within the Participant Classification Framework has also been considered. It is our intention that this framework be widely implemented to systematically classify participants in research featuring exercise, sport, performance, health, and/or fitness outcomes going forward, providing the much-needed uniformity to classification practices.

Defining Training and Performance Caliber: A Participant Classification Framework.

This review covers underlying physiological characteristics and training considerations that may affect muscular strength including improving maximal force expression and time-limited force expression. Strength is underpinned by a combination of morphological and neural factors including muscle cross-sectional area and architecture, musculotendinous stiffness, motor unit recruitment, rate coding, motor unit synchronization, and neuromuscular inhibition. Although single- and multi-targeted block periodization models may produce the greatest strength-power benefits, concepts within each model must be considered within the limitations of the sport, athletes, and schedules. Bilateral training, eccentric training and accentuated eccentric loading, and variable resistance training may produce the greatest comprehensive strength adaptations. Bodyweight exercise, isolation exercises, plyometric exercise, unilateral exercise, and kettlebell training may be limited in their potential to improve maximal strength but are still relevant to strength development by challenging time-limited force expression and differentially challenging motor demands. Training to failure may not be necessary to improve maximum muscular strength and is likely not necessary for maximum gains in strength. Indeed, programming that combines heavy and light loads may improve strength and underpin other strength-power characteristics. Multiple sets appear to produce superior training benefits compared to single sets; however, an athlete’s training status and the dose–response relationship must be considered. While 2- to 5-min interset rest intervals may produce the greatest strength-power benefits, rest interval length may vary based an athlete’s training age, fiber type, and genetics. Weaker athletes should focus on developing strength before emphasizing power-type training. Stronger athletes may begin to emphasize power-type training while maintaining/improving their strength. Future research should investigate how best to implement accentuated eccentric loading and variable resistance training and examine how initial strength affects an athlete’s ability to improve their performance following various training methods.

The Importance of Muscular Strength: Training Considerations

Background/Aim - To investigate the role of eccentric knee flexor strength, between-limb imbalance and biceps femoris long head (BFlh) fascicle length on the risk of a future hamstring strain injury (HSI). Methods - Elite soccer players (n=152) from eight different teams participated. Eccentric knee flexor strength during the Nordic hamstring exercise and BFlh fascicle length were assessed at the beginning of pre-season. The occurrences of a HSI following this were recorded by the team medical staff. Relative risk (RR) was determined for univariate data, and logistic regression was employed for multivariate data. Results - Twenty-seven new HSIs were reported. Eccentric knee flexor strength below 337N (RR = 4.4; 95% CI = 1.1 to 17.5) and BFlh fascicles shorter than 10.56cm (RR = 4.1; 95% CI=1.9 to 8.7) significantly increased the risk of a subsequent HSI. Multivariate logistic regression revealed significant effects when combinations of age, previous history of HSI, eccentric knee flexor strength and BFlh fascicle length were explored. From these analyses the likelihood of a future HSI in older athletes or those with a previous HSI history was reduced if high levels of eccentric knee flexor strength and longer BFlh fascicles were present. Conclusions - The presence of short BFlh fascicles and low levels of eccentric strength in elite soccer players increase the risk of a future HSI. The greater risk of a future HSI in older players or those with a previous HSI is reduced when they possess longer BFlh fascicles and high levels of eccentric strength.

Short biceps femoris fascicles and eccentric knee flexor weakness increase the risk of hamstring injury in elite football (soccer): A prospective cohort study

The external movement loads imposed on players during competitive team sports are commonly measured using global positioning system devices. Information gleaned from analyses is employed to calibrate physical conditioning and injury prevention strategies with the external loads imposed during match play. Intense accelerations and decelerations are considered particularly important indicators of external load. However, to date, no prior meta-analysis has compared high and very high intensity acceleration and deceleration demands in elite team sports during competitive match play. The objective of this systematic review and meta-analysis was to quantify and compare high and very high intensity acceleration vs. deceleration demands occurring during competitive match play in elite team sport contexts. A systematic review of four electronic databases (CINAHL, MEDLINE, SPORTDiscus, Web of Science) was conducted to identify peer-reviewed articles published between January 2010 and April 2018 that had reported higher intensity (> 2.5 m·s−2) accelerations and decelerations concurrently in elite team sports competitive match play. A Boolean search phrase was developed using key words synonymous to team sports (population), acceleration and deceleration (comparators) and match play (outcome). Articles only eligible for meta-analysis were those that reported either or both high (> 2.5 m·s−2) and very high (> 3.5 m·s−2) intensity accelerations and decelerations concurrently using global positioning system devices (sampling rate: ≥ 5 Hz) during elite able-bodied (mean age: ≥ 18 years) team sports competitive match play (match time: ≥ 75%). Separate inverse random-effects meta-analyses were conducted to compare: (1) standardised mean differences (SMDs) in the frequency of high and very high intensity accelerations and decelerations occurring during match play, and (2) SMDs of temporal changes in high and very high intensity accelerations and decelerations across first and second half periods of match play. Using recent guidelines recommended for the collection, processing and reporting of global positioning system data, a checklist was produced to help inform a judgement about the methodological limitations (risk of detection bias) aligned to ‘data collection’, ‘data processing’ and ‘normative profile’ for each eligible study. For each study, each outcome was rated as either ‘low’, ‘unclear’ or ‘high’ risk of bias. A total of 19 studies met the eligibility criteria, comprising seven team sports including American Football (n = 1), Australian Football (n = 2), hockey (n = 1), rugby league (n = 4), rugby sevens (n = 3), rugby union (n = 2) and soccer (n = 6) with a total of 469 male participants (mean age: 18–29 years). Analysis showed only American Football reported a greater frequency of high (SMD = 1.26; 95% confidence interval [CI] 1.06–1.43) and very high (SMD = 0.19; 95% CI − 0.42 to 0.80) intensity accelerations compared to decelerations. All other sports had a greater frequency of high and very high intensity decelerations compared to accelerations, with soccer demonstrating the greatest difference for both the high (SMD = − 1.74; 95% CI − 1.28 to − 2.21) and very high (SMD = − 3.19; 95% CI − 2.05 to − 4.33) intensity categories. When examining the temporal changes from the first to the second half periods of match play, there was a small decrease in both the frequency of high and very high intensity accelerations (SMD = 0.50 and 0.49, respectively) and decelerations (SMD = 0.42 and 0.46, respectively). The greatest risk of bias (40% ‘high’ risk of bias) observed across studies was in the ‘data collection’ procedures. The lowest risk of bias (35% ‘low’ risk of bias) was found in the development of a ‘normative profile’. To ensure that elite players are optimally prepared for the high-intensity accelerations and decelerations imposed during competitive match play, it is imperative that players are exposed to comparable demands under controlled training conditions. The results of this meta-analysis, accordingly, can inform practical training designs. Finally, guidelines and recommendations for conducting future research, using global positioning system devices, are suggested.

/pdf/high-intensity-acceleration-and-deceleration-demands-in-2xfbgi13u4.pdf

High-Intensity Acceleration and Deceleration Demands in Elite Team Sports Competitive Match Play: A Systematic Review and Meta-Analysis of Observational Studies

Two reactive strength index (RSI) variants exist, the RSI and RSI modified (RSImod) which are typically calculated during the drop jump (DJ) and countermovement jump (CMJ), respectively. Both RSI variants have been used to monitor athletes’ ability to complete stretch-shortening cycle actions quickly, but they have never been compared. The purpose of this study was to determine if they yield relatable information about reactive strength characteristics. Male professional rugby league players (n = 21, age = 20.8±2.3 years, height = 1.82±0.06 m and body mass = 94.3±8.4 kg) performed three DJs (30 cm) and CMJs on a force plate. RSI and RSImod were subsequently calculated by dividing jump height by ground contact time (GCT) and time to take-off (TTT), respectively. All variables were highly reliable (intraclass correlation coefficient ≥0.78) with acceptable levels of variability (coefficient of variation ≤8.2%), albeit larger variability was noted for DJ variables. Moreover, there was a large relationship between RSI and RSImod (r=0.524, P=0.007), whereas very large relationships were noted between jump heights (r=0.762, P<0.001) and between GCT and TTT (ρ=0.705, P<0.001). Additionally, RSI (0.90±0.22) was largely and significantly (d=2.57, P<0.001) greater than RSImod (0.47±0.08). The DJ-derived RSI yields much larger values than the CMJ-derived RSImod and although a large relationship was noted between them, it equated to just 22% shared variance. These results suggest that the two RSI variants do not explain each other well, indicating that they do not assess entirely the same reactive strength qualities and should not be used interchangeably.

Relationship between reactive strength index variants in rugby league players

Summary: the aim of this review was to summarize the research to date on lower limb stiffness in relation to both its effect on performance and training considerations. Evidence suggests that some amount of lower limb stiffness is required for successful athletic performance, but too much stiffness may be detrimental. To avoid recruiting excessive stiffness, it is suggested that the reactive strength index should be used. In terms of training to increase lower limb stiffness, it is recommended that resistance training should be performed with loads above 75% of 1 repetition maximum and should precede high-intensity plyometric and power training.

Lower Limb Stiffness: Effect on Performance and Training Considerations

The dynamic strength index (DSI), often calculated as the ratio of countermovement jump (CMJ) propulsion peak force to isometric mid-thigh pull (IMTP) peak force, is said to inform whether ballistic or maximal strength training is warranted for a given athlete CMJ propulsion peak force is highly influenced by jump strategy, however, which is not highlighted by the DSI alone This study aimed to quantitatively compare CMJ force-, power-, velocity-, and displacement-time curves between athletes who achieved high versus low DSI scores Fifty-three male collegiate athletes performed three CMJs and IMTPs on a force platform Athletes were ranked based on DSI score and the CMJ kinetic and kinematic-time curves of the bottom and top twenty athletes were compared The low DSI group (055 ± 010 vs 092 ± 011) produced greater IMTP peak force (467 ± 150 vs 311 ± 66 N·kg−1) but a larger braking net impulse in the CMJ, leading to greater braking velocity and larger countermovement displacement This strategy resulted in a similar CMJ propulsion peak force (259 ± 22 vs 254 ± 31 N·kg−1) to the high DSI group These results, taken together with those of previous studies, support the notion of ballistic versus maximal strength training likely being better suited to low versus high DSI scorers, respectively

https://www.mdpi.com/2075-4663/5/4/72/pdf

Influence of Dynamic Strength Index on Countermovement Jump Force-, Power-, Velocity-, and Displacement-Time Curves.

The purpose of this study was to explore the relationships between isometric mid-thigh pull (IMTP) force-time characteristics (peak force and time-specific force vales (100–250 ms)) and dynamic performance and compare dynamic performance between stronger and weaker athletes. Forty-three athletes from different sports (rowing, soccer, bicycle motocross, and hockey) performed three trials of the squat jump (SJ), countermovement jump (CMJ), and IMTP, and performed a one repetition maximum power clean (PC). Reactive strength index modified (RSImod) was also calculated from the CMJ. Statistically significant large correlations between IMTP force-time characteristics and PC (ρ = 0.569–0.674, p < 0.001), and moderate correlations between IMTP force-time characteristics (excluding force at 100 ms) and RSImod (ρ = 0.389–0.449, p = 0.013–0.050) were observed. Only force at 250 ms demonstrated a statistically significant moderate correlation with CMJ height (ρ = 0.346, p = 0.016) and no statistically significant associations were observed between IMTP force-time characteristics and SJ height. Stronger athletes (top 10) demonstrated statistically significantly greater CMJ heights, RSImods, and PCs (p ≤ 0.004, g = 1.32–1.89) compared to weaker (bottom 10) athletes, but no differences in SJ height were observed (p = 0.871, g = 0.06). These findings highlight that the ability to apply rapidly high levels of force in short time intervals is integral for PC, CMJ height, and reactive strength.

https://www.mdpi.com/2075-4663/5/3/68/pdf

Relationships between Isometric Force-Time Characteristics and Dynamic Performance

Countermovement jump (CMJ) force-time testing is commonly used to monitor seasonal alterations in athletes’ CMJ strategy (to infer alterations in neuromuscular function). The flight time to contraction time (FT:CT) ratio and reactive strength index modified (RSImod) are considered to be two primary CMJ variables of interest. Due to similar calculations, it is likely that the FT:CT ratio and RSImod share similar reliability and an almost perfect relationship. Consequently, there may be no requirement to include both variables in CMJ monitoring reports. This study aimed to investigate this by recruiting twenty-five males to perform three CMJs on a force platform across two sessions that were separated by one week. The FT:CT ratio and two calculations of RSImod (based on the jump height from either flight time or take-off velocity) were then calculated using robust methods. The between-day reliability was good-excellent for all of the variables (95% confidence interval range of the coefficient of variation = 2.02–9.22%) with no significant between-day differences noted (p ≥ 0.231). There was an almost perfect positive relationship between the FT:CT ratio and RSImod regardless of the calculation method (r = 0.944–0.947, p < 0.001). As the FT:CT ratio and RSImod yield similar absolute reliability and share 90% of common variance, there is little reason to include both variables in CMJ monitoring reports.

/pdf/reliability-of-and-relationship-between-flight-time-to-253iiq3kv9.pdf

Reliability of and Relationship between Flight Time to Contraction Time Ratio and Reactive Strength Index Modified.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

John J. McMahon

Author Tools

Chat about Author