scholarly journals Validation of Inertial Sensor to Measure Barbell Kinematics across a Spectrum of Loading Conditions

Sports ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 93
Author(s):  
John C. Abbott ◽  
John P. Wagle ◽  
Kimitake Sato ◽  
Keith Painter ◽  
Thaddeus J. Light ◽  
...  
Keyword(s):  
Effect Size ◽  
Peak Velocity ◽  
Inertial Sensor ◽  
Measurement Unit ◽  
Mean Velocity ◽  
Back Squat ◽  
Pearson Correlations ◽  
Internal Error ◽  
3D Motion Capture ◽  
Level Of Agreement

The aim of this study was to evaluate the level of agreement in measuring back squat kinematics between an inertial measurement unit (IMU) and a 3D motion capture system (3DMOCAP). Kinematic variables included concentric peak velocity (CPV), concentric mean velocity (CMV), eccentric peak velocity (EPV), eccentric mean velocity (EMV), mean propulsive velocity (MPV), and POP-100: a proprietary variable. Sixteen resistance-trained males performed an incrementally loaded one repetition maximum (1RM) squat protocol. A series of Pearson correlations, 2 × 4 RM ANOVA, Cohen’s d effect size differences, coefficient of variation (CV), and standard error of the estimate (SEE) were calculated. A large relationship existed for all variables between devices (r = 0.78–0.95). Between-device agreement for CPV worsened beyond 60% 1RM. The remaining variables were in agreement between devices with trivial effect size differences and similar CV magnitudes. These results support the use of the IMU, regardless of relative intensity, when measuring EMV, EPV, MPV, and POP-100. However, practitioners should carefully select kinematic variables of interest when using the present IMU device for velocity-based training (VBT), as certain measurements (e.g., CMV, CPV) do not possess practically acceptable reliability or accuracy. Finally, the IMU device exhibited considerable practical data collection concerns, as one participant was completely excluded and 13% of the remaining attempts displayed obvious internal error.

Is a Head-Worn Inertial Sensor a Valid Tool to Monitor Swimming?

2021 ◽  
pp. 1-4
Author(s):  
Stephanie J. Shell ◽  
Brad Clark ◽  
James R. Broatch ◽  
Katie Slattery ◽  
Shona L. Halson ◽  
...  
Keyword(s):  
Correlation Coefficient ◽  
Video Analysis ◽  
Inertial Sensor ◽  
Absolute Error ◽  
Wearable Device ◽  
Measurement Unit ◽  
Fisher Exact Test ◽  
Mean Velocity ◽  
Video Footage ◽  
Stroke Type

Purpose: This study aimed to independently validate a wearable inertial sensor designed to monitor training and performance metrics in swimmers. Methods: A total of 4 male (21 [4] y, 1 national and 3 international) and 6 female (22 [3] y, 1 national and 5 international) swimmers completed 15 training sessions in an outdoor 50-m pool. Swimmers were fitted with a wearable device (TritonWear, 9-axis inertial measurement unit with triaxial accelerometer, gyroscope, and magnetometer), placed under the swim cap on top of the occipital protuberance. Video footage was captured for each session to establish criterion values. Absolute error, standardized effect, and Pearson correlation coefficient were used to determine the validity of the wearable device against video footage for total swim distance, total stroke count, mean stroke count, and mean velocity. A Fisher exact test was used to analyze the accuracy of stroke-type identification. Results: Total swim distance was underestimated by the device relative to video analysis. Absolute error was consistently higher for total and mean stroke count, and mean velocity, relative to video analysis. Across all sessions, the device incorrectly detected total time spent in backstroke, breaststroke, butterfly, and freestyle by 51% (15%). The device did not detect time spent in drill. Intraclass correlation coefficient results demonstrated excellent intrarater reliability between repeated measures across all swimming metrics. Conclusions: The wearable device investigated in this study does not accurately measure distance, stroke count, and velocity swimming metrics or detect stroke type. Its use as a training monitoring tool in swimming is limited.

scholarly journals Validity and Reliability of Kinematics Measured with PUSH Band vs. Linear Encoder in Bench Press and Push-Ups

Sports ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 207 ◽  
Author(s):  
Roland van den Tillaar ◽  
Nick Ball
Keyword(s):  
Bench Press ◽  
Peak Velocity ◽  
Validity And Reliability ◽  
Mean Velocity ◽  
Movement Velocity ◽  
Lower Velocity ◽  
Linear Encoder ◽  
Measurement Devices ◽  
Level Of Agreement ◽  
Push Up

Background: The aim of this study was to compare the validity and reliability of a PUSH band device with a linear encoder to measure movement velocity with different loads during the push-up and bench press exercises. Methods: Twenty resistance-trained athletes performed push-up and bench press exercises with four different loads: without weight vest, 10-20-30 kg weight vest, bench press: 50–82% of their assumed 1 repetition maximum (1 RM) in steps of 10 kg. A linear encoder (Musclelab) and the PUSH band measured mean and peak velocity during both exercises. Several statistical analyses were used to investigate the validity and reliability of the PUSH band with the linear encoder. Results: The main findings of this study demonstrated only moderate associations between the PUSH band and linear encoder for mean velocity (r = 0.62, 0.70) and peak velocity (r = 0.46, 0.49) for both exercises. Furthermore, a good level of agreement (peak velocity: ICC = 0.60, 0.64; mean velocity: ICC = 0.77, 0.78) was observed between the two measurement devices. However, a significant bias was found with lower velocity values measured with the PUSH band in both exercises. In the push-up, both the linear encoder and PUSH band were deemed very reliable (ICC > 0.98; the coefficient of variation (CV): 5.9–7.3%). Bench press reliability decreased for the PUSH band (ICC < 0.95), and the coefficient of variance increased to (12.8–13.3%) for the velocity measures. Calculated 1 RM with the two devices was the same for the push-up, while in bench press the PUSH band under-estimated the 1 RM by 14 kg compared to the linear encoder. Conclusions: It was concluded that the PUSH band will show decreased reliability from velocity measures in a bench press exercise and underestimate load-velocity based 1 RM predictions. For training, the PUSH band can be used during push-ups, however caution is suggested when using the device for the purposes of feedback in bench press at increasing loads.

scholarly journals The Reliability and Validity of Current Technologies for Measuring Barbell Velocity in the Free-Weight Back Squat and Power Clean

Sports ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 94
Author(s):  
Steve W. Thompson ◽  
David Rogerson ◽  
Harry F. Dorrell ◽  
Alan Ruddock ◽  
Andrew Barnes
Keyword(s):  
Peak Velocity ◽  
Reliability And Validity ◽  
Systematic Bias ◽  
Mean Velocity ◽  
Validity Data ◽  
Back Squat ◽  
Free Weight ◽  
Device Reliability ◽  
Measurement Units ◽  
Power Clean

This study investigated the inter-day and intra-device reliability, and criterion validity of six devices for measuring barbell velocity in the free-weight back squat and power clean. In total, 10 competitive weightlifters completed an initial one repetition maximum (1RM) assessment followed by three load-velocity profiles (40–100% 1RM) in both exercises on four separate occasions. Mean and peak velocity was measured simultaneously on each device and compared to 3D motion capture for all repetitions. Reliability was assessed via coefficient of variation (CV) and typical error (TE). Least products regression (LPR) (R2) and limits of agreement (LOA) assessed the validity of the devices. The Gymaware was the most reliable for both exercises (CV < 10%; TE < 0.11 m·s−1, except 100% 1RM (mean velocity) and 90‒100% 1RM (peak velocity)), with MyLift and PUSH following a similar trend. Poorer reliability was observed for Beast Sensor and Bar Sensei (CV = 5.1–119.9%; TE = 0.08–0.48 m·s−1). The Gymaware was the most valid device, with small systematic bias and no proportional or fixed bias evident across both exercises (R2 > 0.42–0.99 LOA = −0.03–0.03 m·s−1). Comparable validity data was observed for MyLift in the back squat. Both PUSH devices produced some fixed and proportional bias, with Beast Sensor and Bar Sensei being the least valid devices across both exercises (R2 > 0.00–0.96, LOA = −0.36–0.46 m·s−1). Linear position transducers and smartphone applications could be used to obtain velocity-based data, with inertial measurement units demonstrating poorer reliability and validity.

Cluster Sets: Permitting Greater Mechanical Stress Without Decreasing Relative Velocity

2017 ◽  
Vol 12 (4) ◽  
pp. 463-469 ◽  
Author(s):  
James J. Tufano ◽  
Jenny A. Conlon ◽  
Sophia Nimphius ◽  
Lee E. Brown ◽  
Harry G. Banyard ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Peak Velocity ◽  
Training Load ◽  
Mean Power ◽  
Mean Velocity ◽  
External Work ◽  
Back Squat ◽  
Mechanical Power Output ◽  
Cluster Sets ◽  
External Loads

Purpose:To determine the effects of intraset rest frequency and training load on muscle time under tension, external work, and external mechanical power output during back-squat protocols with similar changes in velocity.Methods:Twelve strength-trained men (26.0 ± 4.2 y, 83.1 ± 8.8 kg, 1.75 ± 0.06 m, 1.88:0.19 one-repetition-maximum [1RM] body mass) performed 3 sets of 12 back squats using 3 different set structures: traditional sets with 60% 1RM (TS), cluster sets of 4 with 75% 1RM (CS4), and cluster sets of 2 with 80% 1RM (CS2). Repeated-measures ANOVAs were used to determine differences in peak force (PF), mean force (MF), peak velocity (PV), mean velocity (MV), peak power (PP), mean power (MP), total work (TW), total time under tension (TUT), percentage mean velocity loss (%MVL), and percentage peak velocity loss (%PVL) between protocols.Results:Compared with TS and CS4, CS2 resulted in greater MF, TW, and TUT in addition to less MV, PV, and MP. Similarly, CS4 resulted in greater MF, TW, and TUT in addition to less MV, PV, and MP than TS did. There were no differences between protocols for %MVL, %PVL, PF, or PP.Conclusions:These data show that the intraset rest provided in CS4 and CS2 allowed for greater external loads than with TS, increasing TW and TUT while resulting in similar PP and %VL. Therefore, cluster-set structures may function as an alternative method to traditional strength- or hypertrophy-oriented training by increasing training load without increasing %VL or decreasing PP.

The Reliability of Individualized Load–Velocity Profiles

2018 ◽  
Vol 13 (6) ◽  
pp. 763-769 ◽  
Author(s):  
Harry G. Banyard ◽  
Kazunori Nosaka ◽  
Alex D. Vernon ◽  
G. Gregory Haff
Keyword(s):  
Linear Regression ◽  
Peak Velocity ◽  
Intraclass Correlation ◽  
Velocity Profiles ◽  
Mean Velocity ◽  
Movement Velocity ◽  
Repetition Maximum ◽  
Back Squat ◽  
Free Weight ◽  
Order Polynomial

Purpose: To examine the reliability of peak velocity (PV), mean propulsive velocity (MPV), and mean velocity (MV) in the development of load–velocity profiles (LVP) in the full-depth free-weight back squat performed with maximal concentric effort. Methods: Eighteen resistance-trained men performed a baseline 1-repetition maximum (1-RM) back-squat trial and 3 subsequent 1-RM trials used for reliability analyses, with 48-h intervals between trials. 1-RM trials comprised lifts from 6 relative loads including 20%, 40%, 60%, 80%, 90%, and 100% 1-RM. Individualized LVPs for PV, MPV, or MV were derived from loads that were highly reliable based on the following criteria: intraclass correlation coefficient (ICC) >.70, coefficient of variation (CV) ≤10%, and Cohen d effect size (ES) <0.60. Results: PV was highly reliable at all 6 loads. MPV and MV were highly reliable at 20%, 40%, 60%, 80%, and 90% but not 100% 1-RM (MPV: ICC = .66, CV = 18.0%, ES = 0.10, SEM = 0.04 m·s−1; MV: ICC = .55, CV = 19.4%, ES = 0.08, SEM = 0.04 m·s−1). When considering the reliable ranges, almost perfect correlations were observed for LVPs derived from PV20–100% (r = .91–.93), MPV20–90% (r = .92–.94), and MV20–90% (r = .94–.95). Furthermore, the LVPs were not significantly different (P > .05) between trials or movement velocities or between linear regression versus 2nd-order polynomial fits. Conclusions: PV20–100%, MPV20–90%, and MV20–90% are reliable and can be utilized to develop LVPs using linear regression. Conceptually, LVPs can be used to monitor changes in movement velocity and employed as a method for adjusting sessional training loads according to daily readiness.

Sensitivity of the iLOAD® Application for Monitoring Changes in Barbell Velocity Following Power- and Strength-Oriented Resistance Training Programs

2020 ◽  
pp. 1-5
Author(s):  
Alejandro Pérez-Castilla ◽  
Daniel Boullosa ◽  
Amador García-Ramos
Keyword(s):  
Resistance Training ◽  
Effect Size ◽  
Bench Press ◽  
Size Range ◽  
Training Group ◽  
Linear Velocity ◽  
Power Training ◽  
Mean Velocity ◽  
Back Squat ◽  
Velocity Transducer

Objective: To evaluate the sensitivity of the iLOAD® application to detect the changes in mean barbell velocity of complete sets following power- and strength-oriented resistance training (RT) programs. Methods: Twenty men were randomly assigned to a power training group (countermovement jump and bench press throw at 40% of the 1-repetition maximum [1RM]) or strength training group (back squat and bench press at 70% to 90% of 1RM). Single sets of 10 repetitions at 25% and 70% of 1RM during the back squat and bench press exercises were assessed before and after the 4-week RT programs simultaneously with the iLOAD® application and a linear velocity transducer. Results: The power training group showed a greater increment in velocity performance at the 25% of 1RM (effect size range = 0.66–1.53) and the 70% of 1RM (effect size range = 0.11–0.30). The percent change in mean velocity after the RT programs highly correlated between the iLOAD® application and the linear velocity transducer for the back squat (r range = .85–.88) and bench press (r range = .87–.93). However, the iLOAD® application revealed a 2% greater increase in mean velocity after training compared to the linear velocity transducer. Conclusions: The iLOAD® application is a cost-effective, portable, and easy-to-use tool which can be used to detect changes in mean barbell velocity after power- and strength-oriented RT programs.

scholarly journals Assessment of Back-Squat Performance at Submaximal Loads: Is the Reliability Affected by the Variable, Exercise Technique, or Repetition Criterion?

2021 ◽  
Vol 18 (9) ◽  
pp. 4626
Author(s):  
Alejandro Pérez-Castilla ◽  
Danica Janicijevic ◽  
Zeki Akyildiz ◽  
Deniz Senturk ◽  
Amador García-Ramos
Keyword(s):  
Peak Power ◽  
Peak Velocity ◽  
Average Score ◽  
Experimental Session ◽  
Mean Power ◽  
Mean Velocity ◽  
Repetition Maximum ◽  
Performance Variables ◽  
Back Squat ◽  
Squat Exercise

This study aimed to compare the between-session reliability of different performance variables during 2 variants of the Smith machine back-squat exercise. Twenty-six male wrestlers performed 5 testing sessions (a 1-repetition maximum [1RM] session, and 4 experimental sessions [2 with the pause and 2 with the rebound technique]). Each experimental session consisted of performing 3 repetitions against 5 loads (45–55–65–75–85% of the 1RM). Mean velocity (MV), mean power (MP), peak velocity (PV), and peak power (PP) variables were recorded by a linear position transducer (GymAware PowerTool). The best and average scores of the 3 repetitions were considered for statistical analyses. The coefficient of variation (CV) ranged from 3.89% (best PV score at 55% 1 RM using the pause technique) to 10.29% (average PP score at 85% 1 RM using the rebound technique). PP showed a lower reliability than MV, MP, and PV (CVratio ≥ 1.26). The reliability was comparable between the exercise techniques (CVratio = 1.08) and between the best and average scores (CVratio = 1.04). These results discourage the use of PP to assess back-squat performance at submaximal loads. The remaining variables (MV, MP, or PV), exercise techniques (pause or rebound), and repetition criteria (best score or average score) can be indistinctly used due to their acceptable and comparable reliability.

Validity of Various Methods for Determining Velocity, Force, and Power in the Back Squat

2017 ◽  
Vol 12 (9) ◽  
pp. 1170-1176 ◽  
Author(s):  
Harry G. Banyard ◽  
Ken Nosaka ◽  
Kimitake Sato ◽  
G. Gregory Haff
Keyword(s):  
Peak Power ◽  
Peak Velocity ◽  
Force Plate ◽  
Testing Device ◽  
Mean Power ◽  
Mean Velocity ◽  
Repetition Maximum ◽  
Back Squat ◽  
Free Weight ◽  
Criterion Variables

Purpose:To examine the validity of 2 kinematic systems for assessing mean velocity (MV), peak velocity (PV), mean force (MF), peak force (PF), mean power (MP), and peak power (PP) during the full-depth free-weight back squat performed with maximal concentric effort. Methods:Ten strength-trained men (26.1 ± 3.0 y, 1.81 ± 0.07 m, 82.0 ± 10.6 kg) performed three 1-repetition-maximum (1RM) trials on 3 separate days, encompassing lifts performed at 6 relative intensities including 20%, 40%, 60%, 80%, 90%, and 100% of 1RM. Each repetition was simultaneously recorded by a PUSH band and commercial linear position transducer (LPT) (GymAware [GYM]) and compared with measurements collected by a laboratory-based testing device consisting of 4 LPTs and a force plate. Results:Trials 2 and 3 were used for validity analyses. Combining all 120 repetitions indicated that the GYM was highly valid for assessing all criterion variables while the PUSH was only highly valid for estimations of PF (r = .94, CV = 5.4%, ES = 0.28, SEE = 135.5 N). At each relative intensity, the GYM was highly valid for assessing all criterion variables except for PP at 20% (ES = 0.81) and 40% (ES = 0.67) of 1RM. Moreover, the PUSH was only able to accurately estimate PF across all relative intensities (r = .92–.98, CV = 4.0–8.3%, ES = 0.04–0.26, SEE = 79.8–213.1 N). Conclusions:PUSH accuracy for determining MV, PV, MF, MP, and PP across all 6 relative intensities was questionable for the back squat, yet the GYM was highly valid at assessing all criterion variables, with some caution given to estimations of MP and PP performed at lighter loads.

scholarly journals Eccentric Force-Velocity Characteristics during a Novel Squat Protocol in Trained Rugby Union Athletes—Pilot Study

2021 ◽  
Vol 6 (2) ◽  
pp. 32
Author(s):  
Conor McNeill ◽  
C. Martyn Beaven ◽  
Daniel T. McMaster ◽  
Nicholas Gill
Keyword(s):  
Pilot Study ◽  
Dynamic Performance ◽  
Intraclass Correlation ◽  
Rugby Union ◽  
Mean Velocity ◽  
Force Development ◽  
Back Squat ◽  
Force Velocity ◽  
Force Time ◽  
Change In Mean

Eccentric strength characteristics have been shown to be important factors in physical performance. Many eccentric tests have been performed in isolation or with supramaximal loading. The purpose of this study was to investigate within- and between- session reliability of an incremental eccentric back squat protocol. Force plates and a linear position transducer captured force-time-displacement data across six loading conditions, separated by at least seven days. The reliability of eccentric specific measurements was assessed using coefficient of variation (CV), change in mean, and intraclass correlation coefficient (ICC). Eccentric peak force demonstrated good ICC (≥0.82) and TE (≤7.3%) for each load. Variables based on mean data were generally less reliable (e.g., mean rate of force development, mean force, mean velocity). This novel protocol meets acceptable levels of reliability for different eccentric-specific measurements although the extent to which these variables affect dynamic performance requires further research.

scholarly journals Left atrial 4D flow cardiovascular magnetic resonance: a reproducibility study in sinus rhythm and atrial fibrillation

2021 ◽  
Vol 23 (1) ◽  
Author(s):  
Marco Spartera ◽  
Guilherme Pessoa-Amorim ◽  
Antonio Stracquadanio ◽  
Adam Von Ende ◽  
Alison Fletcher ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Blood Pressure ◽  
Heart Rate ◽  
Cardiovascular Magnetic Resonance ◽  
Magnetic Resonance ◽  
Sinus Rhythm ◽  
Left Atrial ◽  
Peak Velocity ◽  
4D Flow ◽  
Mean Velocity

Abstract Background Four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) allows sophisticated quantification of left atrial (LA) blood flow, and could yield novel biomarkers of propensity for intra-cardiac thrombus formation and embolic stroke. As reproducibility is critically important to diagnostic performance, we systematically investigated technical and temporal variation of LA 4D flow in atrial fibrillation (AF) and sinus rhythm (SR). Methods Eighty-six subjects (SR, n = 64; AF, n = 22) with wide-ranging stroke risk (CHA2DS2VASc 0–6) underwent LA 4D flow assessment of peak and mean velocity, vorticity, vortex volume, and stasis. Eighty-five (99%) underwent a second acquisition within the same session, and 74 (86%) also returned at 30 (27–35) days for an interval scan. We assessed variability attributable to manual contouring (intra- and inter-observer), and subject repositioning and reacquisition of data, both within the same session (same-day scan–rescan), and over time (interval scan). Within-subject coefficients of variation (CV) and bootstrapped 95% CIs were calculated and compared. Results Same-day scan–rescan CVs were 6% for peak velocity, 5% for mean velocity, 7% for vorticity, 9% for vortex volume, and 10% for stasis, and were similar between SR and AF subjects (all p > 0.05). Interval-scan variability was similar to same-day scan–rescan variability for peak velocity, vorticity, and vortex volume (all p > 0.05), and higher for stasis and mean velocity (interval scan CVs of 14% and 8%, respectively, both p < 0.05). Longitudinal changes in heart rate and blood pressure at the interval scan in the same subjects were associated with significantly higher variability for LA stasis (p = 0.024), but not for the remaining flow parameters (all p > 0.05). SR subjects showed significantly greater interval-scan variability than AF patients for mean velocity, vortex volume, and stasis (all p < 0.05), but not peak velocity or vorticity (both p > 0.05). Conclusions LA peak velocity and vorticity are the most reproducible and temporally stable novel LA 4D flow biomarkers, and are robust to changes in heart rate, blood pressure, and differences in heart rhythm.

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