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. 2022 Mar 28;22(7):2583.
doi: 10.3390/s22072583.

Ideal Combinations of Acceleration-Based Intensity Metrics and Sensor Positions to Monitor Exercise Intensity under Different Types of Sports

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Ideal Combinations of Acceleration-Based Intensity Metrics and Sensor Positions to Monitor Exercise Intensity under Different Types of Sports

Wei-Han Chen et al. Sensors (Basel). .

Abstract

This study quantified the strength of the relationship between the percentage of heart rate reserve (%HRR) and two acceleration-based intensity metrics (AIMs) at three sensor-positions during three sport types (running, basketball, and badminton) under three intensity conditions (locomotion speeds). Fourteen participants (age: 24.9 ± 2.4 years) wore a chest strap HR monitor and placed three accelerometers at the left wrist (non-dominant), trunk, and right shank, respectively. The %HRR and two different AIMs (Player Load per minute [PL/min] and mean amplitude deviation [MAD]) during exercise were calculated. During running, both AIMs at the shank and PL at the wrist had strong correlations (r = 0.777-0.778) with %HRR; while other combinations were negligible to moderate (r = 0.065-0.451). For basketball, both AIMs at the shank had stronger correlations (r = 0.604-0.628) with %HRR than at wrist (r = 0.536-0.603) and trunk (r = 0.403-0.463) with %HRR. During badminton exercise, both AIMs at shank had stronger correlations (r = 0.782-0.793) with %HRR than those at wrist (r = 0.587-0.621) and MAD at trunk (r = 0.608) and trunk (r = 0.314). Wearing the sensor on the shank is an ideal position for both AIMs to monitor external intensity in running, basketball, and badminton, while the wrist and using PL-derived AIM seems to be the second ideal combination.

Keywords: acceleration; racquet sports; running; team sports; wearable electronic devices.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Accelerometers were placed on the left wrist (a), trunk (b) and shank (c).
Figure 2
Figure 2
Custom basketball exercise routine (a) and badminton six-point footwork (b).
Figure 3
Figure 3
Change of %HRR among three exercise intensity levels under different sports (n = 14). Bonferroni post hoc test: significantly different than a Level 1, b Level 2, and c Level 3 (p < 0.05); Wilcoxon signed rank test: significantly different than * Level 1, Level 2, and Level 3 (p < 0.05).
Figure 4
Figure 4
Change of PL/min among three exercise intensity levels under different sports (n = 14). Bonferroni post hoc test: significantly different than a Level 1, b Level 2, and c Level 3 (p < 0.05); Wilcoxon signed rank test: significantly different than * Level 1, Level 2, and Level 3 (p < 0.05).
Figure 5
Figure 5
Change of MAD among three exercise intensity levels under different sports (n = 14). Bonferroni post hoc test: significantly different than a Level 1, b Level 2, and c Level 3 (p < 0.05); Wilcoxon signed rank test: significantly different than * Level 1, Level 2, and Level 3 (p < 0.05).
Figure 6
Figure 6
The within-sport Pearson (r) (n = 42) and across-sports Spearman (ρ) (n = 126) correlation coefficient for %HRR and PL.
Figure 7
Figure 7
The within-sport Pearson (r) (n = 42) and across-sports Spearman (ρ) (n = 126) correlation coefficient for %HRR and MAD.

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