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Accelerometry is a recent method used to quantify workload in team sports. A rapidly increasing number of studies supports the practical implementation of accelerometry monitoring to regulate and optimize training schemes. Therefore, the purposes of this study were: (1) to reflect the current state of knowledge about accelerometry as a method of workload monitoring in invasion team sports according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, and (2) to conclude recommendations for application and scientific investigations. The Web of Science, PubMed and Scopus databases were searched for relevant published studies according to the following keywords: "accelerometry" or "accelerometer" or "microtechnology" or "inertial devices", and "load" or "workload", and "sport". Of the 1383 studies initially identified, 118 were selected for a full review. The main results indicate that the most frequent findings were (i) devices' body location: scapulae; (b) devices brand: Catapult Sports; (iii) variables: PlayerLoadTM and its variations; (iv) sports: rugby, Australian football, soccer and basketball; (v) sex: male; (vi) competition level: professional and elite; and (vii) context: separate training or competition. A great number of variables and devices from various companies make the comparability between findings difficult; unification is required. Although the most common location is at scapulae because of its optimal signal reception for time-motion analysis, new methods for multi-location skills and locomotion assessment without losing tracking accuracy should be developed., Competing Interests: The authors have declared that no competing interests exist

Gómez-Carmona, CD, Bastida-Castillo, A, González-Custodio, A, Olcina, G, and Pino-Ortega, J. Using an inertial device (WIMU PRO) to quantify neuromuscular load in running: reliability, convergent validity, and influence of type of surface and device location. J Strength Cond Res 34(2): 365-373, 2020-Currently, the use of accelerometers in sport is increasing, and thus, the devices are required to be valid and reliable. This study tested (a) the reliability and validity of WIMU PRO accelerometers to measure PlayerLoad (PL) and (b) the influence of speed, inertial device location, and type of surface where the incremental test is performed. Twenty resistance-trained men (age: 27.32 ± 6.65 years; height: 1.74 ± 0.03 m; body mass: 68.96 ± 4.37 kg; and body mass index: 22.76 ± 1.11 kg·m) volunteered to participate in the study that lasted 5 weeks. Four progressive incremental tests were performed in treadmill and athletic track conditions. External load variable (PL) and physiological variables (heart rate [HR] and SmO2) were recorded by 4 WIMU PRO inertial devices (scapulae, center of mass, knee, and ankle), a GARMIN HR band, and a MOXY near-infrared spectroscopy device, respectively. High reliability was found on both types of surface, showing the best values at the ankle (treadmill: intraclass correlation coefficient [ICC] = 0.99, coefficient of variation [CV] = 4.65%; track: ICC = 0.96, CV = 6.54%). A nearly perfect convergent validity was shown with HRAVG (r = 0.99) and a moderate one with SmO2 (r = -0.69). Significant differences in the PL variable between surfaces were reported in all locations except the scapulae (p = 0.173), and the higher values were found on the track. In the analysis per location, the ankle location reported the highest values at all speeds and on the 2 surfaces analyzed. Assessment needs to be individualized, due to the great variability of gait biomechanics among subjects. The accelerometer location should be chosen according to the purpose of the measurement, with the ankle location being recommended for neuromuscular load analysis in running.

With the development of new microsensor technology to assess load in sports, some indicators of external load through accelerometry-based data have been created by sport technology companies. Thus, the study aim was to analyze the agreement between different accelerometry-based external load indicators (ABELIs) available in sport science. A U-16 male soccer team was assessed during three official matches, divided by periods, to obtain 3-D accelerometry data (x, y and z axes). An average of 1,420,000 data points was analyzed per axis per player. The ABELIs were calculated using this information, and the agreement between them was explored. The following ABELIs were considered after a literature review: AcelT, Player Load RT , PlayerLoad TM , Impulse Load, Player Load RE and Total Load. In order to compare ABELIs, two analyses were performed using: (1) absolute data; and (2) normalized and centered data (Z-scores). In absolute and centered data, very large to nearly perfect correlations (1st period: r > 0.803, p > 0.01; 2nd period: r > 0.919; p > 0.01) were found. Instead, very large differences were found in absolute values (bias = -579,226.6 to 285,931.1; t = -224.66 to 213.91, p < 0.01), and no differences in scaled and centered values (bias = 0; t = 1; p = 1). In conclusion, considering the different output (magnitude and units) among ABELIs, the standardization of a universal index to calculate accelerometer load is needed in order to make possible between-study comparison., Competing Interests: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Objectives: (1) To describe the fast Fourier transform (FFT) multijoint as monopodal postural stability measurement in well-trained athletes, (2) to compare the within-subject FFT between laterality, joints, and body segments, and (3) to establish the within- and between-subject relationship between joints., Methods: Twelve national-level basketball players participated voluntarily in this investigation. The participants performed two 60-second repetitions of a monopodal stability test (1 repetition with each lower limb), separated by 3 minutes of active recovery. All tests were recorded by 4 WIMU PRO™ inertial devices located on the ankle, knee, lumbar spine, and thoracic spine. The main variable was total acceleration, where the FFT was applied., Results: The higher instability results were found in the ankle and in the nondominant lower limb (dominant = 1.131 [0.122] a.u. (arbitrary units); nondominant = 1.141 [0.172] a.u). In the body segment analysis, the greater percentage of differences (%diff) were shown between lumbar spine and knee in the dominant (%diff = -2.989%; d = 0.87) and nondominant (%diff = -3.243%; d = 0.90) lower limb. Finally, very large between-subjects variability was found in all joints and body segments., Conclusions: The described protocol is proposed for monopodal postural stability assessment, being useful to provide information about the stability of joints and the body segment between joints. Besides, a within-subject analysis is recommended, and the FFT calculation will enable a linear analysis of each test.

Featured Application: Latin dance presents a safe, engaging form of weight-bearing exercise for older adults that could help to mitigate age-related physical decline. Quantifying limb impacts during dance using wearable sensors informs guidelines for an appropriate workload to strengthen lower extremity bones and muscles in older populations vulnerable to sarcopenia and falls. As global aging rises, identifying strategies to mitigate age-related physical decline has become an urgent priority. Dance represents a promising exercise modality for older adults, yet few studies have quantified the external loads older dancers experience. This study aimed to characterize the impacts accumulated across lower limb and spinal locations in older adults during Latin dance. Thirty older Latin dancers (age = 66.56 ± 6.38 years; female = 93.3%) wore inertial sensors on the scapulae, lumbar spine, knees, and ankles during a 1 h class. A distal-to-proximal gradient emerged in the total impacts (F = 429.29; p < 0.01; ωp2 = 0.43) and per intensities (F = 103.94-to-665.55; p < 0.01; ωp2 = 0.07-to-0.54), with the highest impacts sustained in the ankles (≈9000 total impacts) from 2 g to >10 g (p < 0.01; d = 1.03-to-4.95; ankles > knees > lower back > scapulae) and knees (≈12,000 total impacts) when <2 g (p < 0.01, d = 2.73-to-3.25; knees > ankles > lower back > scapulae). The majority of the impacts remained below 6 g across all anatomical locations (>94%). The impacts also increased in lower limb locations with faster tempos (r = 0.10-to-0.52; p < 0.01), while subtly accumulating over successive songs rather than indicating fatigue (r = 0.11-to-0.35; p < 0.01). The mild ankle and knee loads could strengthen the dancers' lower extremity bones and muscles in a population vulnerable to sarcopenia, osteoporosis, and falls. Quantifying the workload via accelerometry enables creating personalized dance programs to empower healthy aging. With global aging rising, this work addresses a timely public health need regarding sustainable lifelong exercise for older people. Ranging from low to moderate, the measured impact magnitudes suggest that dance lessons may provide enough osteogenic stimulus without overloading structures. [ABSTRACT FROM AUTHOR]

BACKGROUND: Previous studies have analysed the effect of wearing high-heeled shoes (HHS) on gait analysis, balance and its relation to health. However, further research is needed to study its effect on the difference of chain reactions in the transfer of body impacts from the lower to the upper limbs. OBJECTIVES: The aims of the present research were: (a) to compare the effects of wearing HHS on impacts across body joints during walking with sport shoes (SS) as a reference, and (b) to examine such effects at different speeds. METHODS: Seven well-trained women completed this study. Incremental treadmill walking test were performed with two different footwear: SS and HHS. Inertial devices were used to quantify the chain reactions at selected anatomical lower limbs and trunk locations. Statistical analysis included the Wilcoxon test with ranges and Cohen's d effect size with percentage of differences. RESULTS: The highest values were found at the heel in both footwear and in both legs (SS: right = 0.76 ± 0.27, left = 0.79 ± 0.27; HHS: right = 1.07 ± 0.38, left = 1.11 ± 0.41), while the lowest values were registered at lower and upper back. Furthermore, significant differences were found with the HHS load being higher at all locations (p < 0.05; % = 𝑑𝑖𝑓𝑓 12.20–36.36%), influenced by the walking speed. In addition, a strong influence of footwear in the change of the laterality profile was found (p < 0.05). CONCLUSIONS: These findings suggest that the use of HHS increase the load on the lower limb and the trunk. Until reaching 5 km/h during walking, no significant differences were found between wearing HHS or SS in accelerometer load, producing exponential differences from this speed. The great between-subject variability implies that within-subject analysis is recommended, as it is more related to real clinical practice. [ABSTRACT FROM AUTHOR]

Copyright of RICYDE. Revista Internacional de Ciencias del Deporte is the property of Revista Internacional de Ciencias del Deporte and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aims of this study were to: (1) identify the representative external load profile of match-play in Spanish professional soccer players by principal components analysis (PCA), and (2) analyse the effect of match location (home vs away), match outcome (win vs draw vs loss) and length of the microcycle (5 vs 6 vs 7 vs 8 vs 9 days) on the external load profile. Data were collected during one season consisting of 42 matches in LaLiga 123 and 11 external load variables were selected after the PCA. TD, total distance covered; DIS0–6: distance from 0 to 6 km/h; DIS21–24: distance from 21 to 24 km/h; HSRD: high-speed running distance above 21 km/h; HSRA: total of high-speed running actions above 21 km/h; VMAX: maximum speed in km/h; Sprints: total of actions above 24 km/h; ACC: total of accelerations; ACCG-avg: average accelerometer G-force; ACCMAX: maximum acceleration (m/s2); DECMAX: maximum deceleration (m/s2). Match location had an impact on HSRD (p < 0.01; ES = 0.05), DIS0–6 (p < 0.01; ES = 0.05), and ACCMAX (p < 0.01; ES = 0.05). Match outcome had a relation to TD (p < 0.01; ES = 0.05), DIS0–6 (p < 0.01; ES = 0.05) and HSRD (p < 0.01; ES = 0.05). Length of the microcycle had an impact on TD (p < 0.01; ES = 0.05), DIS0–6 (p < 0.01; ES = 0.11), ACC (p < 0.01; ES = 0.04) and VMAX (p < 0.01; ES = 0.04). This study provides coaches a selection of variables for match-play analysis, which could represent two-thirds of external load profile. Then, professionals should consider that these contextual variables could have an impact on the external load profile. [ABSTRACT FROM AUTHOR]

Copyright of Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación is the property of Federacion Espanola de Asociaciones de Docentes de Educacion Fisica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The external workload measured in one anatomical location does not determine the total load supported by the human body. Therefore, the purpose of the present study was to characterize the multi-location external workload through PlayerLoadRT of 13 semi-professional women's basketball players, as well as to analyze differences among anatomical locations (inter-scapulae line, lumbar region, 2× knee, 2× ankle) and laterality (left vs. right) during five tests that represent the most common movements in basketball—(a) linear locomotion, 30-15 IFT; (b) acceleration and deceleration, 16.25-m RSA (c) curvilinear locomotion, 6.75-m arc (d) jump, Abalakov test (e) small-sided game, 10' 3 vs. 3 10 × 15-m. Statistical analysis was composed of a repeated-measures t-test and eta partial squared effect size. Regarding laterality, differences were found only in curvilinear locomotion, with a higher workload in the outer leg (p < 0.01; ηp2 = 0.33–0.63). In the vertical profile, differences among anatomical locations were found in all tests (p < 0.01; ηp2 = 0.56–0.98). The nearer location to ground contact showed higher values except between the scapulae and lumbar region during jumps (p = 0.83; ηp2 = 0.00). In conclusion, the multi-location assessment of external workload through a previously validated test battery will make it possible to understand the individual effect of external workload in each anatomical location that depends on the type of locomotion. These results should be considered when designing specific strategies for training and injury prevention. [ABSTRACT FROM AUTHOR]

The present study analyzed the multi-location external workload profile in basketball players using a previously validated test battery and compared the demands among anatomical locations. A basketball team comprising 13 semi-professional male players was evaluated in five tests (abilities/skills/tests): (a) aerobic, linear movement, 30-15 IFT; (b) lactic anaerobic, acceleration and deceleration, 16.25 m RSA (c) alactic anaerobic, curvilinear movement, 6.75 m arc (d) elastic, jump, Abalakov test (e) physical-conditioning, small-sided game, 10' 3 vs.3 10 × 15 m. PlayerLoadRT was evaluated at six anatomical locations simultaneously (interscapular line, lumbar region, knees and ankles) by six WIMU PROTM inertial devices attached to the player using an ad hoc integral suit. Statistical analysis was composed of an ANOVA of repeated measures and partial eta squared effect sizes. Significant differences among anatomical locations were found in all tests with higher values in the location nearer to ground contact (p < 0.01). However, differences between lower limb locations were only found in curvilinear movements, with a higher workload in the outside leg (p < 0.01). Additionally, high between-subject variability was found in team players, especially at lower limb locations. In conclusion, multi-location evaluation in sports movements will make it possible to establish an individual external workload profile and design specific strategies for training and injury prevention programs. [ABSTRACT FROM AUTHOR]