These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
230 related articles for article (PubMed ID: 25264954)
1. Mobile healthcare for automatic driving sleep-onset detection using wavelet-based EEG and respiration signals. Lee BG; Lee BL; Chung WY Sensors (Basel); 2014 Sep; 14(10):17915-36. PubMed ID: 25264954 [TBL] [Abstract][Full Text] [Related]
2. Automatic classification methods for detecting drowsiness using wavelet packet transform extracted time-domain features from single-channel EEG signal. B VP; Chinara S J Neurosci Methods; 2021 Jan; 347():108927. PubMed ID: 32941920 [TBL] [Abstract][Full Text] [Related]
3. Temporal correlation between two channels EEG of bipolar lead in the head midline is associated with sleep-wake stages. Li Y; Tang X; Xu Z; Liu W; Li J Australas Phys Eng Sci Med; 2016 Mar; 39(1):147-55. PubMed ID: 26934877 [TBL] [Abstract][Full Text] [Related]
4. Exploring the fatigue affecting electroencephalography based functional brain networks during real driving in young males. Chen J; Wang H; Wang Q; Hua C Neuropsychologia; 2019 Jun; 129():200-211. PubMed ID: 30995455 [TBL] [Abstract][Full Text] [Related]
5. Detection of k-complexes in EEG signals using a multi-domain feature extraction coupled with a least square support vector machine classifier. Al-Salman W; Li Y; Wen P Neurosci Res; 2021 Nov; 172():26-40. PubMed ID: 33965451 [TBL] [Abstract][Full Text] [Related]
6. Detection of driver drowsiness using wavelet analysis of heart rate variability and a support vector machine classifier. Li G; Chung WY Sensors (Basel); 2013 Dec; 13(12):16494-511. PubMed ID: 24316564 [TBL] [Abstract][Full Text] [Related]
7. VR motion sickness recognition by using EEG rhythm energy ratio based on wavelet packet transform. Li X; Zhu C; Xu C; Zhu J; Li Y; Wu S Comput Methods Programs Biomed; 2020 May; 188():105266. PubMed ID: 31865095 [TBL] [Abstract][Full Text] [Related]
8. [Automatic Sleep Staging Method Based on Energy Features and Least Squares Support Vector Machine Classifier]. Gao Q; Zhou J; Ye B; Wu X Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2015 Jun; 32(3):531-6. PubMed ID: 26485973 [TBL] [Abstract][Full Text] [Related]
9. Assessment of driver drowsiness using electroencephalogram signals based on multiple functional brain networks. Chen J; Wang H; Hua C Int J Psychophysiol; 2018 Nov; 133():120-130. PubMed ID: 30081067 [TBL] [Abstract][Full Text] [Related]
10. Fast Sleep Stage Classification Using Cascaded Support Vector Machines with Single-Channel EEG Signals. Li D; Ruan Y; Zheng F; Su Y; Lin Q Sensors (Basel); 2022 Dec; 22(24):. PubMed ID: 36560286 [TBL] [Abstract][Full Text] [Related]
11. Association of Visual-Based Signals with Electroencephalography Patterns in Enhancing the Drowsiness Detection in Drivers with Obstructive Sleep Apnea. Minhas R; Peker NY; Hakkoz MA; Arbatli S; Celik Y; Erdem CE; Semiz B; Peker Y Sensors (Basel); 2024 Apr; 24(8):. PubMed ID: 38676243 [TBL] [Abstract][Full Text] [Related]
12. An accurate sleep stages classification system using a new class of optimally time-frequency localized three-band wavelet filter bank. Sharma M; Goyal D; Achuth PV; Acharya UR Comput Biol Med; 2018 Jul; 98():58-75. PubMed ID: 29775912 [TBL] [Abstract][Full Text] [Related]
13. EEG Signal Analysis for Diagnosing Neurological Disorders Using Discrete Wavelet Transform and Intelligent Techniques. Alturki FA; AlSharabi K; Abdurraqeeb AM; Aljalal M Sensors (Basel); 2020 Apr; 20(9):. PubMed ID: 32354161 [TBL] [Abstract][Full Text] [Related]
14. Single-Channel Real-Time Drowsiness Detection Based on Electroencephalography. Albalawi H; Li X Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():98-101. PubMed ID: 30440350 [TBL] [Abstract][Full Text] [Related]
15. Real driving environment EEG-based detection of driving fatigue using the wavelet scattering network. Wang F; Chen D; Yao W; Fu R J Neurosci Methods; 2023 Dec; 400():109983. PubMed ID: 37838152 [TBL] [Abstract][Full Text] [Related]
16. A Novel Fatigue Driving State Recognition and Warning Method Based on EEG and EOG Signals. Liu L; Ji Y; Gao Y; Ping Z; Kuang L; Li T; Xu W J Healthc Eng; 2021; 2021():7799793. PubMed ID: 34853672 [TBL] [Abstract][Full Text] [Related]
17. A Hybrid Approach to Detect Driver Drowsiness Utilizing Physiological Signals to Improve System Performance and Wearability. Awais M; Badruddin N; Drieberg M Sensors (Basel); 2017 Aug; 17(9):. PubMed ID: 28858220 [TBL] [Abstract][Full Text] [Related]
18. A Novel Method for Sleep-Stage Classification Based on Sonification of Sleep Electroencephalogram Signals Using Wavelet Transform and Recurrent Neural Network. Moradi F; Mohammadi H; Rezaei M; Sariaslani P; Razazian N; Khazaie H; Adeli H Eur Neurol; 2020; 83(5):468-486. PubMed ID: 33120386 [TBL] [Abstract][Full Text] [Related]
19. K-complexes Detection in EEG Signals using Fractal and Frequency Features Coupled with an Ensemble Classification Model. Al-Salman W; Li Y; Wen P Neuroscience; 2019 Dec; 422():119-133. PubMed ID: 31682947 [TBL] [Abstract][Full Text] [Related]
20. A novel convolutional neural network method for subject-independent driver drowsiness detection based on single-channel data and EEG alpha spindles. Houshmand S; Kazemi R; Salmanzadeh H Proc Inst Mech Eng H; 2021 Sep; 235(9):1069-1078. PubMed ID: 34028321 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]