scholarly journals Epoch-by-epoch phase difference method to evaluate GNSS single-frequency phase data quality

2020 ◽  
Vol 36 ◽  
Author(s):  
M. Zhou ◽  
X. Liu ◽  
J. Guo ◽  
Q. Zhang ◽  
Z. Liu ◽  
...  
Keyword(s):  
Data Quality ◽  
Phase Difference ◽  
Difference Method ◽  
Single Frequency ◽  
Phase Data ◽  
Frequency Phase

Use of spatial phase difference method to detect microwaves associated with stator coil partial discharge in a generator

1997 ◽  
Vol 121 (2) ◽  
pp. 16-26 ◽  
Author(s):  
Masatake Kawada ◽  
Zen-Ichiro Kawasaki ◽  
Kenji Matsuura ◽  
Toshio Musashiya ◽  
Katsunori Otoba ◽  
...  
Keyword(s):  
Phase Difference ◽  
Difference Method ◽  
Partial Discharge ◽  
Spatial Phase

scholarly journals Bioimpedance Vector Patterns Changes in Response to Swimming Training: An Ecological Approach

2020 ◽  
Vol 17 (13) ◽  
pp. 4851 ◽  
Author(s):  
Joana F. Reis ◽  
Catarina N. Matias ◽  
Francesco Campa ◽  
José P. Morgado ◽  
Paulo Franco ◽  
...  
Keyword(s):  
Major Axis ◽  
Training Load ◽  
Single Frequency ◽  
Ecological Approach ◽  
Dry Land ◽  
Competitive Swimming ◽  
Cellular Density ◽  
Joint Interpretation ◽  
Phase Sensitive ◽  
Frequency Phase

Background and aim: Monitoring bioelectric phase angle (PhA) provides important information on the health and the condition of the athlete. Together with the vector length, PhA constitutes the bioimpedance vector analysis (BIVA) patterns, and their joint interpretation exceeds the limits of the evaluation of the PhA alone. The present investigation aimed to monitor changes in the BIVA patterns during a training macrocycle in swimmers, trying to ascertain if these parameters are sensitive to training load changes across a 13-week training period. Methods: Twelve national and international level swimmers (four females; eight males; 20.9 ± 1.9 years; with a competitive swimming background of 11.3 ± 1.8 years; undertaking 16–20 h of pool training and 4–5 h of dry-land training per week and 822.0 ± 59.0 International Swimming Federation (FINA) points) were evaluated for resistance (R) and reactance (Xc) using a single frequency phase sensitive bioimpedance device at the beginning of the macrocycle (M1), just before the beginning of the taper period (M2), and just before the main competition of the macrocycle (M3). At the three-time assessment points, swimmers also performed a 50 m all-out first stroke sprint with track start (T50 m) while time was recorded. Results: The results of the Hotelling T2 test showed a significant vector displacement due to simultaneous R and Xc changes (p < 0.001), where shifting from top to bottom along the major axis of the R-Xc graph from M1 to M2 was observed. From M2 to M3, a vector displacement up and left along the minor axis of the tolerance ellipses resulted in an increase in PhA (p < 0.01). The results suggest a gain in fluid with a decrease in cellular density from M1 to M2 due to decrements in R and Xc. Nevertheless, the reduced training load characterizing taper seemed to allow for an increase in PhA and, most importantly, an increase of Xc, thus demonstrating improved cellular health and physical condition, which was concomitant with a significant increase in the T50 m performance (p < 0.01). Conclusions: PhA, obtained by bioelectrical R and Xc, can be useful in monitoring the condition of swimmers preparing for competition. Monitoring BIVA patterns allows for an ecological approach to the swimmers’ health and condition assessment without resorting to equations to predict the related body composition variables.

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