400399. Biomedical engineering not elsewhere classified
Title | 400399. Biomedical engineering not elsewhere classified |
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Parent | 4003. Biomedical engineering |
Latest research outputs
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3D convolutional neural network for schizophrenia detection using as EEG-based functional brain network
Shen, Mingkan, Wen, Peng, Song, Bo and Li, Yan. 2024. "3D convolutional neural network for schizophrenia detection using as EEG-based functional brain network." Biomedical Signal Processing and Control. 89. https://doi.org/10.1016/j.bspc.2023.105815Article
A Convolutional Long Short-Term Memory-Based Neural Network for Epilepsy Detection From EEG
Tawhid, Md. Nurul Ahad, Siuly, Siuly and Li, Tianning. 2022. "A Convolutional Long Short-Term Memory-Based Neural Network for Epilepsy Detection From EEG." IEEE Transactions on Instrumentation and Measurement. 71, pp. 1-11. https://doi.org/10.1109/TIM.2022.3217515Article
A Hand-Modeled Feature Extraction-Based Learning Network to Detect Grasps Using sEMG Signal
Baygin, Mehmet, Barua, Prabal Datta, Dogan, Sengul, Tuncer, Turker, Key, Sefa, Acharya, U. Rajendra and Cheong, Kang Hao. 2022. "A Hand-Modeled Feature Extraction-Based Learning Network to Detect Grasps Using sEMG Signal." Sensors. 22 (5). https://doi.org/10.3390/s22052007Article
A new design of mental state classification for subject independent BCI systems
Joadder, Md. A. M., Siuly, S., Kabir, E., Wang, H. and Zhang, Y.. 2019. "A new design of mental state classification for subject independent BCI systems." IRBM. 40 (5), pp. 297-305. https://doi.org/10.1016/j.irbm.2019.05.004Article
A New Way of Channel Selection in the Motor Imagery Classification for BCI Applications
Joadder, Md. A. Mannan, Siuly, Siuly and Kabir, Enamul. 2018. "A New Way of Channel Selection in the Motor Imagery Classification for BCI Applications ." Siuly, Siuly, Lee, Ickjai, Huang, Zhisheng, Zhou, Rui, Wang, Hua and Xiang, Wei (ed.) 7th International Conference on Health Information Science (HIS 2018). Cairns, Australia 05 - 07 Oct 2018 Switzerland. https://doi.org/10.1007/978-3-030-01078-2_10Conference or Workshop item
A novel epileptic seizure prediction method based on synchroextracting transform and 1-dimensional convolutional neural network
Ra, Jee Sook, Li, Tianning and Li, Yan. 2023. "A novel epileptic seizure prediction method based on synchroextracting transform and 1-dimensional convolutional neural network." Computer Methods and Programs in Biomedicine. 240. https://doi.org/10.1016/j.cmpb.2023.107678Article
A Novel Real-time Depth of Anaesthesia Monitoring Method using Detrended Fluctuation Analysis and ANN
Chen, Xing and Wen, Paul. 2020. "A Novel Real-time Depth of Anaesthesia Monitoring Method using Detrended Fluctuation Analysis and ANN." 2020 5th International Conference on Biomedical Signal and Image Processing (ICBIP 2020). Suzhou, China 21 - 23 Aug 2020 New York, United States. https://doi.org/10.1145/3417519.3419403Paper
A preliminary study about the distribution of temperature due to electrical stimulation in ECT
Menezes de Oliveira, Marilia, Wen, Peng, Ahfock, Tony and Shahid, Syed Salman. 2014. "A preliminary study about the distribution of temperature due to electrical stimulation in ECT." 2014 ICME International Conference on Complex Medical Engineering (ICME 2014). Taipei, Taiwan 26 - 29 Jun 2014 Piscataway, NJ. United States.Paper
A real-time epilepsy seizure detection approach based on EEG using short-time Fourier transform and Google-Net convolutional neural network
Shen, Mingkan, Yang, Fuwen, Wen, Peng, Song, Bo and Li, Yan. 2024. "A real-time epilepsy seizure detection approach based on EEG using short-time Fourier transform and Google-Net convolutional neural network." Heliyon. 10 (11). https://doi.org/10.1016/j.heliyon.2024.e31827Article
A study of white matter and skull inhomogeneous anisotropic tissue conductivities on EEG forward head modeling
Bashar, Md. Rezaul, Li, Yan and Wen, Peng. 2008. "A study of white matter and skull inhomogeneous anisotropic tissue conductivities on EEG forward head modeling." Karim, Mohammad (ed.) DMAI 2008: 1st IEEE International Workshop on Data Mining and Artificial Intelligence. Khulna, Bangladesh 24 - 27 Dec 2008 Bangladesh. https://doi.org/10.1109/ICCITECHN.2008.4803103Paper
Accurate depth of anesthesia monitoring based on EEG signal complexity and frequency features
Li, Tianning, Huang, Yi, Wen, Paul and Li, Yan. 2024. "Accurate depth of anesthesia monitoring based on EEG signal complexity and frequency features." Brain Informatics. 11. https://doi.org/10.1186/s40708-024-00241-yArticle
Accurately monitoring the depth of anaesthesia using an intelligent method
Li, Yingchun, Wang, Zicong, Wen, Peng and Meng, Max Q.-H.. 2007. "Accurately monitoring the depth of anaesthesia using an intelligent method." 2007 IEEE/ICM International Conference on Complex Medical Engineering (CME 2007). Beijing, China 23 - 27 May 2007 Beijing, China. https://doi.org/10.1109/ICCME.2007.4381761Paper
An efficient approach for EEG sleep spindles detection based on fractal dimension coupled with time frequency image
Al-Salman, Wessam, Li, Yan, Wen, Peng and Diykh, Mohammed. 2018. "An efficient approach for EEG sleep spindles detection based on fractal dimension coupled with time frequency image." Biomedical Signal Processing and Control. 41, pp. 210-221. https://doi.org/10.1016/j.bspc.2017.11.019Article
An efficient visibility graph similarity algorithm and its application for sleep stages classification
Zhu, Guohun, Li, Yan and Wen, Peng Paul. 2012. "An efficient visibility graph similarity algorithm and its application for sleep stages classification." Zanzotto, Fabio Massimo, Tsumoto, Shusaku, Taatgen, Niels and Yao, Yiyu (ed.) 2012 International Conference on Brain Informatics (BI 2012). Macau, China 04 - 07 Dec 2012 Heidelberg, Germany. Springer. https://doi.org/10.1007/978-3-642-35139-6_18Paper
An improved detrended moving-average method for monitoring the depth of anesthesia
Nguyen-Ky, T., Wen, Peng and Li, Yan. 2010. "An improved detrended moving-average method for monitoring the depth of anesthesia." IEEE Transactions on Biomedical Engineering. 57 (10), pp. 2369-2378. https://doi.org/10.1109/TBME.2010.2053929Article
Anaesthetic EEG signal denoise using improved nonlocal mean methods
Li, Tianning, Wen, Peng and Jayamaha, Sophie. 2014. "Anaesthetic EEG signal denoise using improved nonlocal mean methods." Physical and Engineering Sciences in Medicine. 37 (2), pp. 431-437. https://doi.org/10.1007/s13246-014-0263-zArticle
Analysing epileptic EEGs with a visibility graph algorithm
Zhu, Guohun, Li, Yan and Wen, Peng (Paul). 2012. "Analysing epileptic EEGs with a visibility graph algorithm." Chen, Qianbin, Huan, Jun (Luke), Xu, Yong, Zhang, Tianqi and Wang, Lipo (ed.) 5th International Conference on Biomedical Engineering and Informatics (BMEI 2012). Chongqing, China 16 - 18 Oct 2012 Piscataway, NJ. United States. https://doi.org/10.1109/BMEI.2012.6513212Paper
Analytic and numeric evaluation of EEG forward problem using spherical volume conductor models
Shahid, Salman and Wen, Peng. 2010. "Analytic and numeric evaluation of EEG forward problem using spherical volume conductor models." Li, Yan, Yang, Jiajia, Wen, Peng and Wu, Jinglong (ed.) 2010 IEEE/ICME International Conference on Complex Medical Engineering (ICME 2010). Gold Coast, Australia 13 - 15 Jul 2010 Piscataway, NJ. United States. https://doi.org/10.1109/ICCME.2010.5558878Paper
Automated accurate emotion classification using Clefia pattern-based features with EEG signals
Dogan, Abdullah, Barua, Prabal Datta, Baygin, Mehmet, Tuncer, Turker, Dogan, Sengul, Yaman, Orhan, Dogru, Ali Hikmet and Acharya, Rajendra U.. 2024. "Automated accurate emotion classification using Clefia pattern-based features with EEG signals." International Journal of Healthcare Management. 17 (1), pp. 32-45. https://doi.org/10.1080/20479700.2022.2141694Article
Automated classification of attention deficit hyperactivity disorder and conduct disorder using entropy features with ECG signals
Koh, Joel.E.W., Ooi, Chui Ping, Lim-Ashworth, Nikki SJ., Vicnesh, Jahmunah, Tor, Hui Tian, Oh, Oh Shu, Tan, Ru-San, Acharya, U.Rajendra and Fung, Daniel Shuen Sheng. 2022. "Automated classification of attention deficit hyperactivity disorder and conduct disorder using entropy features with ECG signals." Computers in Biology and Medicine. 140. https://doi.org/10.1016/j.compbiomed.2021.105120Article
Automated detection of cyclic alternating pattern and classification of sleep stages using deep neural network
Loh, Hui Wen, Ooi, Chui Ping, Dhok, Shivani G., Sharma, Manish, Bhurane, Ankit A. and Acharya, U. Rajendra. 2022. "Automated detection of cyclic alternating pattern and classification of sleep stages using deep neural network." Applied Intelligence. 52 (3), pp. 2903-2917. https://doi.org/10.1007/s10489-021-02597-8Article
Automatic identification of schizophrenia based on EEG signals using dynamic functional connectivity analysis and 3D convolutional neural network
Shen, Mingkan, Wen, Peng, Song, Bo and Li, Yan. 2023. "Automatic identification of schizophrenia based on EEG signals using dynamic functional connectivity analysis and 3D convolutional neural network." Computers in Biology and Medicine. 160. https://doi.org/10.1016/j.compbiomed.2023.107022Article
Automatically Predicting Severity of Parkinson's Disease Using Model Based on XGBoost from Speech
Zhu, Xuchen, Fang, Yong and Wen, Peng. 2019. "Automatically Predicting Severity of Parkinson's Disease Using Model Based on XGBoost from Speech." 2019 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). Dalian, China 20 - 22 Sep 2019 China. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICSPCC46631.2019.8960722Paper
Bayesian model for brain computation
Li, Yan and Wen, Peng. 2005. "Bayesian model for brain computation." Wu, Jinglong and Ito, Koji (ed.) 1st International Conference on Complex Medical Engineering (CME 2005). Takamatsu, Japan 15 - 18 May 2005 Kagawa, Japan.Paper
Biocorrosion behaviour of magnesium alloys under pseudo-physiological conditions
Wang, Hao, Zhang, M. X., Shi, Z. M. and Yang, Ke. 2006. "Biocorrosion behaviour of magnesium alloys under pseudo-physiological conditions." Tissue Engineering. 12 (4), pp. 1067-1067.Article
Chaos-modified detrended moving average methodology for monitoring the depth of anaesthesia
Nguyen-Ky, T., Wen, Peng and Li, Yan. 2013. "Chaos-modified detrended moving average methodology for monitoring the depth of anaesthesia." International Journal of Emerging Trends in Signal Processing. 1 (2), pp. 1-8.Article
Classification of alcoholic EEG signals using a deep learning method
Farsi, Leila, Siuly, Siuly, Kabir, Enamul and Wang, Hua. 2021. "Classification of alcoholic EEG signals using a deep learning method." IEEE Sensors Journal. 21 (3), pp. 3552 - 3560. https://doi.org/10.1109/JSEN.2020.3026830Article
Clustering technique-based least square support vector machine for EEG signal classification
Siuly, S., Li, Yan and Wen, Peng (Paul). 2011. "Clustering technique-based least square support vector machine for EEG signal classification." Computer Methods and Programs in Biomedicine. 104 (3), pp. 358-372. https://doi.org/10.1016/j.cmpb.2010.11.014Article
Comparisons between motor area EEG and all-channels EEG for two algorithms in motor imagery task classification
Li, Yan and Wen, Peng (Paul). 2014. "Comparisons between motor area EEG and all-channels EEG for two algorithms in motor imagery task classification." Biomedical Engineering: Applications, Basis and Communications. 26 (3), pp. 1-10. https://doi.org/10.4015/S1016237214500409Article
Consciousness and depth of anesthesia assessment based on Bayesian analysis of EEG signals
Nguyen-Ky, Tai, Wen, Peng (Paul) and Li, Yan. 2013. "Consciousness and depth of anesthesia assessment based on Bayesian analysis of EEG signals." IEEE Transactions on Biomedical Engineering. 60 (6), pp. 1488-1498. https://doi.org/10.1109/TBME.2012.2236649Article
De-noising a raw EEG signal and measuring depth of anaesthesia for general anaesthesia patients
Nguyen-Ky, T., Wen, Peng, Li, Yan and Gray, Robert. 2010. "De-noising a raw EEG signal and measuring depth of anaesthesia for general anaesthesia patients." Li, Yan, Yang, Jiajia, Wen, Peng and Wu, Jinglong (ed.) 2010 IEEE/ICME International Conference on Complex Medical Engineering (ICME 2010). Gold Coast, Australia 13 - 15 Jul 2010 Brisbane, Australia. https://doi.org/10.1109/ICCME.2010.5558834Paper
Decision support system for major depression detection using spectrogram and convolution neural network with EEG signals
Loh, Hui Wen, Ooi, Chui Ping, Aydemir, Emrah, Tuncer, Turker, Dogan, Sengul and Acharya, U. Rajendra. 2022. "Decision support system for major depression detection using spectrogram and convolution neural network with EEG signals." Expert Systems: the journal of knowledge engineering. 39 (3). https://doi.org/10.1111/exsy.12773Article
Depth of anaesthesia assessment based on adult electroencephalograph beta frequency band
Li, Tianning and Wen, Peng. 2016. "Depth of anaesthesia assessment based on adult electroencephalograph beta frequency band." Physical and Engineering Sciences in Medicine. 39 (3), pp. 773-781. https://doi.org/10.1007/s13246-016-0459-5Article
Depth of anaesthesia assessment using interval second-order difference plot and permutation entropy techniques
Li, Tianning and Wen, Peng. 2017. "Depth of anaesthesia assessment using interval second-order difference plot and permutation entropy techniques." IET Signal Processing. 11 (2), pp. 221-227. https://doi.org/10.1049/iet-spr.2015.0114Article
Depth of anaesthesia control techniques and human body models
Abdulla, Shahab Anna. 2012. Depth of anaesthesia control techniques and human body models. PhD Thesis Doctor of Philosophy. University of Southern Queensland.PhD Thesis
Detecting sleep spindles in EEGs using wavelet fourier analysis and statistical features
Al-Salman, Wessam, Li, Yan and Wen, Peng. 2019. "Detecting sleep spindles in EEGs using wavelet fourier analysis and statistical features." Biomedical Signal Processing and Control. 48, pp. 80-92. https://doi.org/10.1016/j.bspc.2018.10.004Article
Detection of alcoholic EEG signals based on whole brain connectivity and convolution neural networks
Shen, Mingkan, Wen, Peng, Song, Bo and Li, Yan. 2023. "Detection of alcoholic EEG signals based on whole brain connectivity and convolution neural networks." Biomedical Signal Processing and Control. 79 (Part 2). https://doi.org/10.1016/j.bspc.2022.104242Article
Developing a logistic regression model with cross-correlation for motor imagery signal recognition
Li, Yan, Wu, Jinglong and Yang, Jingjing. 2011. "Developing a logistic regression model with cross-correlation for motor imagery signal recognition." 2011 IEEE/ICME International Conference on Complex Medical Engineering (ICME 2011). Harbin, China 22 - 25 May 2011 Piscataway, NJ. United States. https://doi.org/10.1109/ICCME.2011.5876793Paper
Developing a tunable Q-factor wavelet transform based algorithm for epileptic EEG feature extraction
Al Ghayab, Hadi Ratham, Li, Yan, Siuly, Siuly, Abdulla, Shahab and Wen, Paul. 2017. "Developing a tunable Q-factor wavelet transform based algorithm for epileptic EEG feature extraction." Siuly, Siuly, Huang, Zhisheng, Aickelin, Uwe, Zhou, Rui, Wang, Hua, Zhang, Yanchun and Klimenko, Stanislav (ed.) 6th International Conference on Health Information Science (HIS 2017). Moscow, Russian Federation 07 - 09 Oct 2017 Germany. https://doi.org/10.1007/978-3-319-69182-4_6Paper
DKPNet41: Directed knight pattern network-based cough sound classification model for automatic disease diagnosis
Kuluozturk, Mutlu, Kobat, Mehmet Ali, Barua, Prabal Datta, Dogan, Sengul, Tuncer, Turker, Tan, Ru-San, Ciaccio, Edward J. and Acharya, U Rajendra. 2022. "DKPNet41: Directed knight pattern network-based cough sound classification model for automatic disease diagnosis." Medical Engineering and Physics. 110. https://doi.org/10.1016/j.medengphy.2022.103870Article