Nirjas: An open source framework for extracting metadata from the source code

Bhardwaj, Ayush; Sahil,; Pratap, Kaushlendra; Mishra, Gaurav Kumar

doi:10.1109/confluence52989.2022.9734222

Cited by 1 publication

(2 citation statements)

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“…Accelerometer data were recorded to a memory card and uploaded following the completion of ballet class. Data were processed using an open‐source customized R shiny 11 application designed for IMU data analysis in ballet 12 . The software processed raw inertial measurement data, filtered it using a fourth‐order zero‐lag low‐pass Butterworth filter with a cutoff frequency of 12 Hz, and calculated training load variables including PlayerLoad™, using the formula:

Player load goodbreak= \sqrt{\frac{{()(, α_{y 1} goodbreak- α_{γ - 1})}^{2} + {()(, α_{x 1} goodbreak- α_{x - 1})}^{2} + {()(, a_{z 1} goodbreak- α_{z - 1})}^{2}}{100}}

where α is acceleration; x , y , and z represent the anterior–posterior, mediolateral, and vertical planes of movement, respectively 13 …”

Section: Methodsmentioning

confidence: 99%

“…Data were processed using an open-source customized R shiny 11 application designed for IMU data analysis in ballet. 12 The software processed raw inertial measurement data, filtered it using a fourth-order zero-lag low-pass Butterworth filter with a cutoff frequency of 12 Hz, and calculated training load variables including PlayerLoad™, using the formula: where α is acceleration; x, y, and z represent the anteriorposterior, mediolateral, and vertical planes of movement, respectively. 13 A validated algorithm was used to identify the occurrence and height of jumps during class.…”

Section: Measurement Of Jump Loadmentioning

confidence: 99%

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Jumping demands during classical ballet class

Maloney,

Mattiussi,

Cleather

et al. 2023

Scandinavian Med Sci Sports

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Ballet class represents a considerable portion of professional ballet training, yet the external training load demands associated with class—and particularly the jumping demands—have not been investigated. The purpose of this study was to measure the jumping demands of ballet class by sex and rank. Eleven female and eight male elite professional ballet dancers participated in 109 ballet classes taught by 12 different teachers. Jump counts and jump heights were measured during each class. A Poisson generalized linear mixed effects model was used to examine the differences in jump counts between sexes and ranks. Greater jump counts were observed during class in men than in women (153, 95% confidence intervals [CI] [137, 170] vs. 119, 95% CI [109, 131], p = 0.004) and in junior ranking dancers compared with senior ranking dancers (151, 95% CI [138, 165] vs. 121, 95% CI [108, 135], p = 0.006). Female junior and senior ranking dancers jumped at rates of 9.2 ± 2.6 and 8.6 ± 4.7 jumps·min−1, respectively, while male junior and senior ranking dancers jumped at rates of 9.1 ± 2.6 and 8.7 ± 2.6 jumps·min−1, respectively. Across all classes, 73% of jumps observed were below 50% of maximum double‐legged countermovement jump height. Unlike rehearsals and performances, class offers dancers an opportunity to self‐regulate load, and as such, are a useful session to manage jump load, and facilitate gradual return‐to‐dance pathways. Communication between health care and artistic staff is essential to facilitate load management during class.

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