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A study on the optimization of athletes’ fitness assessment and training program based on sports biomechanics

Yali Wang

Yali Wang

School of Basic Education and Art, Shandong Industrial Vocational CollegeZibo, China
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Wang, Yali
  
Sep 26, 2025
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Published Online: Sep 26, 2025
Received: Jan 05, 2025
Accepted: Apr 30, 2025
DOI: https://doi.org/10.2478/amns-2025-1035
Keywords
© 2025 Yali Wang, published by Sciendo.
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

The basic model of the decision support system
The basic model of the decision support system

Figure 2.

Training fitness assessment and optimization decision system
Training fitness assessment and optimization decision system

Figure 3.

Physical motion Angle contrast validation
Physical motion Angle contrast validation

Figure 4.

The muscle wire envelope is compared to the EMGworks muscle activation
The muscle wire envelope is compared to the EMGworks muscle activation

Figure 5.

The speed of 30 meters of the athletes before and after the intervention
The speed of 30 meters of the athletes before and after the intervention

Figure 6.

The results of the athletes’ strength analysis
The results of the athletes’ strength analysis

Basic information of the experimental object

Basic information Optimize training group (n=12) Traditional training group (n=12) T P
Mean SD Mean SD
Age 16.59 1.52 16.84 0.94 0.529 0.558
Height (cm) 185.63 9.48 186.42 10.75 1.114 0.264
Weight (kg) 74.52 9.65 74.82 9.76 1.063 0.352
Training period 5.26 1.32 5.29 1.54 0.952 0.358

Analysis of the effectiveness of the 5×30 meter sprint

Repeat sprint (s)
Group Before intervention After intervention T P
Mean SD Mean SD
Optimize training 4.98 0.52 4.51 0.25 7.425 0.000
Traditional training 4.96 0.58 4.88 0.51 1.263 0.048
T 0.042 4.526 —— ——
P 0.825 0.001 —— ——

The results and analysis of the Illinois trail index were conducted (s)

Group Before intervention After intervention T P
Mean SD Mean SD
Optimize training 16.58 1.54 15.24 0.59 2.596 0.032
Traditional training 16.48 0.85 16.30 0.87 1.326 0.095
T 0.524 4.526 —— ——
P 0.775 0.005 —— ——

The results of the subjects’ residual differences

Subjects FX(N) FY(N) FZ(N) MX(Nm) MY(Nm) MZ(Nm)
1 1.646 0.548 0.209 9.435 8.329 7.751
2 2.351 0.88 2.144 7.738 3.554 13.329
3 2.89 1.773 2.115 9.862 9.208 8.533
4 1.808 0.11 2.705 1.767 7.507 15.426
5 1.597 2.334 1.64 10.407 7.552 6.278
6 1.64 0.487 1.683 15.345 6.738 15.869
7 2.305 1.928 2.502 7.724 8.715 10.974
8 0.388 0.542 0.905 15.158 1.531 16.643
9 2.892 1.431 1.432 2.847 11.654 4.174
10 0.717 1.253 0.612 0.231 16.359 5.965
11 1.766 2.566 2.48 0.564 3.336 15.152
12 1.072 1.57 0.368 4.191 17.559 8.202
13 2.583 0.345 2.546 7.362 13.466 18.351
14 2.561 0.224 1.676 16.03 11.9 4.629
15 2.524 2.867 0.806 17.758 8.003 6.077
16 1.699 0.58 2.325 0.882 0.629 3.905
17 2.413 2.567 1.906 7.891 5.876 5.268
18 1.359 2.562 2.818 6.479 14.143 8.635
19 0.068 2.533 0.494 13.259 5.389 17.997
20 2.824 2.155 2.878 0.489 3.128 11.234
21 1.703 0.579 1.568 4.997 2.367 7.322
22 0.353 2.388 2.125 18.306 11.427 16.163
23 1.889 1.181 2.726 2.491 5.374 16.115
24 1.049 2.835 0.379 10.294 18.539 18.066
Language:
English
Publication timeframe:
1 times per year
Journal Subjects:
Life Sciences, Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics, Physics, other
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