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Abstract: Staunton, CA, Stanger, JJ, Wundersitz, DW, Gordon, BA, Custovic, E, and Kingsley, MI. Criterion validity of a MARG sensor to assess countermovement jump performance in elite basketballers. J Strength Cond Res 35(3): 797-803, 2021-This study assessed the criterion validity of a magnetic, angular rate, and gravity (MARG) sensor to measure countermovement jump (CMJ) performance metrics, including CMJ kinetics before take-off, in elite basketballers. Fifty-four basketballers performed 2 CMJs on a force platform with data simultaneously recorded by a MARG sensor located centrally on the player's back. Vertical accelerations recorded from the MARG sensor were expressed relative to the direction of gravity. Jumps were analyzed by a blinded assessor and the best jump according to the force platform was used for comparison. Pearson correlation coefficients (r) and mean bias with 95% ratio limits of agreement (95% RLOA) were calculated between the MARG sensor and the force platform for jumps performed with correct technique (n = 44). The mean bias for all CMJ metrics was less than 3%. Ninety-five percent RLOA between MARG- and force platform-derived flight time and jump height were 1 ± 7% and 1 ± 15%, respectively. For CMJ performance metrics before takeoff, impulse displayed less random error (95% RLOA: 1 ± 13%) when compared with mean concentric power and time to maximum force displayed (95% RLOA: 0 ± 29% and 1 ± 34%, respectively). Correlations between MARG and force platform were significant for all CMJ metrics and ranged from large for jump height (r = 0.65) to nearly perfect for mean concentric power (r = 0.95). Strong relationships, low mean bias, and low random error between MARG and force platform suggest that MARG sensors can provide a practical and inexpensive tool to measure impulse and flight time-derived CMJ performance metrics., (Copyright © 2018 National Strength and Conditioning Association.)

Alexander, JP, Hopkinson, TL, Wundersitz, DWT, Serpell, BG, Mara, JK, and Ball, NB. Validity of a wearable accelerometer device to measure average acceleration values during high-speed running. J Strength Cond Res 30(11): 3007-3013, 2016-The aim of this study was to determine the validity of an accelerometer to measure average acceleration values during high-speed running. Thirteen subjects performed three sprint efforts over a 40-m distance (n = 39). Acceleration was measured using a 100-Hz triaxial accelerometer integrated within a wearable tracking device (SPI-HPU; GPSports). To provide a concurrent measure of acceleration, timing gates were positioned at 10-m intervals (0-40 m). Accelerometer data collected during 0-10 m and 10-20 m provided a measure of average acceleration values. Accelerometer data was recorded as the raw output and filtered by applying a 3-point moving average and a 10-point moving average. The accelerometer could not measure average acceleration values during high-speed running. The accelerometer significantly overestimated average acceleration values during both 0-10 m and 10-20 m, regardless of the data filtering technique (p < 0.001). Body mass significantly affected all accelerometer variables (p < 0.10, partial η = 0.091-0.219). Body mass and the absence of a gravity compensation formula affect the accuracy and practicality of accelerometers. Until GPSports-integrated accelerometers incorporate a gravity compensation formula, the usefulness of any accelerometer-derived algorithms is questionable.

The aim of this study was to determine if residual neuromuscular fatigue influenced subsequent match and training activity in professional women's basketball. Prior to matches and training sessions throughout a season, players performed countermovement jumps while wearing a magnetic, angular rate and gravity (acceleration) sensor on their upper back. Flight time to contraction time ratio was used to determine neuromuscular performance and to identify neuromuscular fatigue. Average session intensity and volume, the proportion of live time spent in different intensity bands (matches), and absolute and relative time spent in different intensity bands (training) were quantified using accelerometry. Residual neuromuscular fatigue was deemed to be present when the decrement in neuromuscular performance relative to pre-season baseline was greater than the smallest worthwhile change. Players displayed residual neuromuscular fatigue before 16% of matches and 33% of training sessions. When players were fatigued prior to matches, the proportion of live time undertaking supramaximal activity was 5.7% less (p = 0.02) and moderate-vigorous activity was 3.7% more than when not fatigued (p = 0.02). When fatigued prior to training, the players displayed a 2.6% decrement in average intensity (p = 0.02), 2.8% decrement in absolute (p = 0.01) and 5.0% decrement in relative (p = 0.01) maximal activity, as well as 13.3% decrement in absolute (p < 0.01) and 6.8% decrement in relative (p < 0.01) supramaximal activity when compared to not being fatigued. These findings suggest that residual neuromuscular fatigue influences players' ability to perform supramaximal activity, which highlights the importance of monitoring neuromuscular performance throughout a professional season. Highlights Residual neuromuscular fatigue can influence the amount of supramaximal activity players perform in a subsequent training session or match. Practices should be implemented to minimise residual neuromuscular fatigue carried into matches while maintaining a sufficient training volume to elicit physiological adaptations. MARG sensors can be used as an affordable and time-efficient tool for regularly monitoring countermovement jump-derived neuromuscular fatigue. [ABSTRACT FROM AUTHOR]

Context: Accelerometer peak impact accelerations are being used to measure player physical demands in contact sports. However, their accuracy to do so has not been ascertained. Purpose: To compare peak-impact-acceleration data from an accelerometer contained in a wearable tracking device with a 3-dimensional motion-analysis (MA) system during tackling and bumping. Methods: Twenty-five semielite rugby athletes wore a tracking device containing a 100-Hz triaxial accelerometer (MinimaxX S4, Catapult Innovations, Australia). A single retroreflective marker was attached to the device, with its position recorded by a 12-camera MA system during 3 physical-collision tasks (tackle bag, bump pad, and tackle drill; N = 625). The accuracy, effect size, agreement, precision, and relative errors for each comparison were obtained as measures of accelerometer validity. Results: Physical-collision peak impact accelerations recorded by the accelerometer overestimated (mean bias 0.60 g) those recorded by the MA system (P < .01). Filtering the raw data at a 20-Hz cutoff improved the accelerometer's relationship with MA data (mean bias 0.01 g; P > .05). When considering the data in 9 magnitude bands, the strongest relationship with the MA system was found in the 3.0-g or less band, and the precision of the accelerometer tended to reduce as the magnitude of impact acceleration increased. Of the 3 movements performed, the tackle-bag task displayed the greatest validity with MA. Conclusions: The findings indicate that the MinimaxX S4 accelerometer can accurately measure physical-collision peak impact accelerations when data are filtered at a 20-Hz cutoff frequency. As a result, accelerometers may be useful to measure physical collisions in contact sports. [ABSTRACT FROM AUTHOR]

The purpose of this study was to validate peak acceleration data from an accelerometer contained within a wearable tracking device while walking, jogging and running. Thirty-nine participants walked, jogged and ran on a treadmill while 10 peak accelerations per movement were obtained (n = 390). A single triaxial accelerometer measured resultant acceleration during all movements. To provide a criterion measure of acceleration, a 12-camera motion analysis (MA) system tracked the position of a retro-reflective marker affixed to the wearable tracking device. Peak raw acceleration recorded by the accelerometer significantly overestimated peak MA acceleration (P < 0.01). Filtering accelerometer data improved the relationship with the MA system (P < 0.01). However, only the 10 Hz and 8 Hz cut-off frequencies significantly reduced the errors found. The walk movement demonstrated the highest accuracy, agreement and precision and the lowest relative errors. Linear increases in error were observed for jog compared with walk and for run compared to both other movements. As the magnitude of acceleration increased, the strength of the relationship between the accelerometer and the criterion measure decreased. These results indicate that filtered accelerometer data provide an acceptable means of assessing peak accelerations, in particular for walking and jogging. [ABSTRACT FROM AUTHOR]