DVS Edition Citation

Biró, A, Kovács, L & Szilágyi, L. (2026). Bioinformatics-inspired IMU stride sequence modeling for fatigue detection using spectral-entropy features and hybrid AI in performance sports. Sensors, 26 (2), 525. Zugriff am 11.03.2026 unter https://doi.org/10.3390/s26020525

APA (7th ed.) Citation

Biró, A., Kovács, L., & Szilágyi, L. (2026). Bioinformatics-inspired IMU stride sequence modeling for fatigue detection using spectral-entropy features and hybrid AI in performance sports. Sensors, 26(2), 525.

Chicago Style (17th ed.) Citation

Biró, A., L. Kovács, and L. Szilágyi. "Bioinformatics-inspired IMU Stride Sequence Modeling for Fatigue Detection Using Spectral-entropy Features and Hybrid AI in Performance Sports." Sensors 26, no. 2 (2026): 525.

MLA (9th ed.) Citation

Biró, A., et al. "Bioinformatics-inspired IMU Stride Sequence Modeling for Fatigue Detection Using Spectral-entropy Features and Hybrid AI in Performance Sports." Sensors, vol. 26, no. 2, 2026, p. 525.