APA (7th ed.) Citation

MS, G., A, N., S, T., & A, R. (2026). Multimodal apnea detection: Advancements through convolutional neural networks and STFT analysis of EEG, ECG, and nasal signals to tackle key challenges in innovation. Computer methods in biomechanics and biomedical engineering, 29(13), 3225. https://doi.org/10.1080/10255842.2025.2510367

Chicago Style (17th ed.) Citation

MS, Ghafourian, Noori A, Taghipour S, and Ramezani A. "Multimodal Apnea Detection: Advancements Through Convolutional Neural Networks and STFT Analysis of EEG, ECG, and Nasal Signals to Tackle Key Challenges in Innovation." Computer Methods in Biomechanics and Biomedical Engineering 29, no. 13 (2026): 3225. https://doi.org/10.1080/10255842.2025.2510367.

MLA (9th ed.) Citation

MS, Ghafourian, et al. "Multimodal Apnea Detection: Advancements Through Convolutional Neural Networks and STFT Analysis of EEG, ECG, and Nasal Signals to Tackle Key Challenges in Innovation." Computer Methods in Biomechanics and Biomedical Engineering, vol. 29, no. 13, 2026, p. 3225, https://doi.org/10.1080/10255842.2025.2510367.