Email: tsung.hao.hsieh@ gmail.com
- Hsieh, T. H., Wu, K. Y., & Liang, S. F. (2018). Identification of Schizophrenic Patients and Healthy Controls Based on Musical Perception Using AEP Analysis. Neuropsychiatry. (Vol. 08).
- Kung, C. C., Hsieh, T. H., Liou, J. Y., Lin, K. J., Shaw, F. Z., & Liang, S. F. (2014). Musicians and non-musicians’ different reliance of features in consonance perception: A behavioral and ERP study. Clinical Neurophysiology, 125(5), 971-978.
- Hsieh, T.H., Ishibashi, A., Yasutake, M., Liang, S.F. (2019, October)., Using Tent-type Clean Unit System Platform for Sleep and non-contact Sleep Assessment. In 2019 3rd International Conference on Computational Biology and Bioinformatics (ICCBB 2019).
- Hsieh, T.H., Ishibashi, A., Yasutake, M., Liang, S.F. (2019, March)., The Feasibility of Using Tent-type Clean Unit System Platform for Sleep and non-contact Assessment. In 2019 2nd IERI International Conference on Medical Physics, Medical Engineering and Informatics (ICMMI 2019).
- Hsieh, T. H., Sun, M. J., & Liang, S. F. (2015, November). Musical perception scaling of AEPs from musicians, schizophrenia and normal people. In Technologies and Applications of Artificial Intelligence (TAAI), 2015 Conference on (pp. 358-362). IEEE.S. F. Liang, C. E. Kuo, Y. H Chen, Y. C. Hsu, “Eyeshade for Nap Sleep Wake-Up,” TW Patent # I500418, 2015.
- Hsieh, T. H., Sun, M. J., & Liang, S. F. (2014). Diagnosis of Schizophrenia patients based on brain network complexity analysis of resting-state fMRI. In The 15th International Conference on Biomedical Engineering (pp. 203-206). Springer, Cham.
- Liang, S. F., Hsieh, T. H., Chen, P. T., Wu, M. L., Kung, C. C., Lin, C. Y., & Shaw, F. Z. (2012, November). Differentiation between resting-state fMRI data from ADHD and normal subjects: based on functional connectivity and machine learning. In Fuzzy Theory and it's Applications (iFUZZY), 2012 International Conference on (pp. 294-298). IEEE.
- Kuo, C. E., Hsieh, T. H., & Liang, S. F. (2012). The Automatic Sleep Scoring Method Based on Multiscale Entropy Analysis of EOG Signals. In The 1st Annual Global Healthcare Conference (GHC).
- Liang, S. F., Hsieh, T. H., Chen, W. H., & Lin, K. J. (2011, June). Classification of EEG signals from musicians and non-musicians by neural networks. In Intelligent Control and Automation (WCICA), 2011 9th World Congress on (pp. 865-869). IEEE.