崔兴然

发布者:张怡茹发布时间:2017-10-26浏览次数:10062


  


崔兴然,博士,副教授。邮箱cuixr@seu.edu.cn

20163月,入职东南大学生物科学与医学工程学院。

20112月至201512月,博士与博士后期间,就读/任职于美国哈佛大学医学院。

2002-2013年,就读于武汉理工大学信息工程学院,获得工学学士、硕士、博士学位。


    长期从事生物医学工程跨领域交叉研究,通过分析多维生命体征信号(如脑电、心电、血糖、血压、脉搏、呼吸等),创新性地提出了一系列非线性动态量化指标。主持并参与多项国家自然科学基金和科技部重点专项,在国际重要学术期刊发表SCI论文20余篇,申请发明专利5项。担任江苏省研究型医院学会睡眠专委会常委委员。

    作为国内唯一参赛者和团队核心成员,参与哈佛大学Chung-Kang Peng教授领衔的动态生医指标团队(Dynamical Biomarkers Group)”,参加了由美国XPRIZE基金会主办,高通基金会赞助的人类史上奖金最高的世界医学竞赛Qualcomm Tricorder Xprize1000万美金,2012-2017年),从全球300多个参赛队伍中脱颖而出,于20174月获得大赛全球亚军。该Tricorder医疗诊断系统开发竞赛要求:设备总重量小于2.3千克,可连续实时记录5种基础生理信号:血压、心率、体温、呼吸、血氧浓度,可检测贫血、尿路感染、二型糖尿病、心房颤动、睡眠呼吸暂停、慢性阻塞性肺病、肺炎、中耳炎、白血球增多、高血压、黑色素瘤、带状疱疹13种指定疾病,该诊断系统使用者是无医疗专业背景的一般用户。


本课题组拥有国际著名学者共同参与学生指导:

 彭仲康 教授(Chung-Kang Peng

   https://dbiom.org/chung-kang-peng     

https://scholar.google.com/citations?user=Z0fBt9oAAAAJ&hl=en)

 黄锷 院士(Norden E. Huang

   https://baike.baidu.com/item/%E9%BB%84%E9%94%B7/5467567

   https://scholar.google.com/citations?user=ohK5A7EAAAAJ&hl=en

 

主要研究方向:

神经、生理信号分析;可穿戴技术;生理心理计算;睡眠;认知功能评测;音乐心理学

 

目前正在进行的科研项目:

1.   1.开发穿戴式脑电设备,研发精神心理疾病定量诊断和个性化精神健康防护、诊疗新技术;

2.   2. 基于神经、生理反馈的个性化音乐干预技术;

3.   3.个体化糖尿病健康管理体系及数据库构建;

4.儿童睡眠与认知功能评测;

5.   5.基于穿戴式生理信号监测的学生课堂学习状态评测研究


招生信息:

欢迎生物医学工程、电子信息、通信、计算机、统计物理学、自动化、应用数学、音乐心理学等相关专业的学生;

希望学生对医疗健康行业或者脑科学研究领域具有浓厚的兴趣,沟通能力强,团队协作能力强,与团队成员互助友爱,具有熟练的英语读写能力;

参与指导SRTP及本科毕业设计。


代表SCI论文(*为通讯作者):

1.       Zhilin Gao, Xingran Cui*, Wang Wan, Wenming Zheng, Zhongze Gu. Long-range correlation analysis of high frequency prefrontal electroencephalogram oscillations for dynamic emotion recognition. Biomedical Signal Processing and Control, 2021,72:103291.

2.       Yunxiao Wu, Leirong Tian, DanDi Ma, Panting Wu, Yufen Tang, Xingran Cui*, Zhifei Xu. Autonomic nervous function and low-grade inflammation in children with sleep - disordered breathing. Pediatric Research, 2021, 1-7.

3.       Zhilin Gao, Wang Wan, Zhongze Gu, Xingran Cui*. Application of Resting Brain Frontal Lobe Complexity in Depression Screening. International Conference on Bioengineering and Biomedical Signal and Image Processing, 2021.

4.       Wang Wan, Xingran Cui*, Zhilin Gao, Zhongze Gu. Frontal EEG-based multi-level attention states recognition using dynamical complexity and extreme gradient boosting, Frontiers in Human Neuroscience, 2021,15: 673955. 

5.       Zaozao Chen, Ning Ma, Xiaowei Sun, Qiwei Li, Yi Zeng, Fei Chen, Shiqi Sun, Jun Xu, Jing Zhang, Huan Ye, Jianjun Ge, Zheng Zhang, Xingran Cui, Kam Leong, Yang Chen, Zhongze Gu. Automated evaluation of tumor spheroid behavior in 3D culture using deep learning -based recognition. Biomaterials, 2021,272:120770.

6.       XingranCui*,Leirong Tian, Zhengwen Li, Zikai Ren, Keyang Zha, Xinruo Wei, Chung-Kang Peng. On the variability of heart rate variability- evidence from prospective study of healthy young college students. Entropy, 2020, 22(1302). 

7.       Shan Xue, Leirong Tian, Zhilin Gao, Xingran Cui*. A Novel Method for Extracting High-Quality RR Intervals from Noisy Single-Lead ECG Signals. International Conference on Bio-inspired Information and Communication Technologies, 2020.

8.       Zhilin Gao, Xingran Cui*, Wang Wan and Zhongze Gu. Recognition of Emotional States using Multiscale Information Analysis of High Frequency EEG Oscillations. Entropy, 2019, 21, 609; doi:10.3390/e21060609.

9.       Xingran Cui*, Hung-Chi Chang, Lian-Yu Lin, Chih-Chieh Yu, Wan-Hsin Hsieh, Weihui Li, Chung-Kang Peng, Jiunn-Lee Lin, Men-Tzung Lo. Prediction of atrial fibrillation recurrence before catheter ablation using an adaptive nonlinear and non-stationary surface ECG analysis. Physica A: Statistical Mechanics and its Applications, 2019,514,9-19. 

10.    Xingran Cui*, Emily Chang, Wen-Hung Yang , Bernard C. Jiang , Albert C. Yang, Chung-Kang Peng. Automated Detection of Paroxysmal Atrial Fibrillation Using an Information-Based Similarity Approach. Entropy, 2017, 19(12), 677-690. 

11.    Jing Wang, Pengjian Shang, Wenbin Shi, Xingran Cui*. Dissimilarity Measure Based on Ordinal Pattern for Physiological signals. Communications in Nonlinear Science and Numerical Simulation, 2016, 37:115-124. 

12.    Dongsheng Huang Yong Han, Shenyi Lian, Xingran Cui, Kexin Meng, Balázs Győrffy, Tao Jin. Potential options for managing LOX+ ER- breast cancer patients. Oncotarget, 2016,7,22:32893-901.

13.    Quan Liu, Xingran Cui#, Yuan-Chao Chou, Maysam F. Abbod, Jinn Lin, Jiann-Shing Shieh. Ensemble artificial neural networks applied to predict the key risk factors of hipbone fracture for elders. Biomedical Signal Processing and Control, 2015, 21: 146-156.

14.    Xingran Cui, Amir Abduljalil, Bradley Manor, Chung-Kang Peng,Vera Novak. Multi-Scale Glycemic Variability: A Link to Gray Matter Atrophy and Cognitive Decline in Type 2Diabetes. PLoS One, 2014,9(1) e86284. 

15.    Xingran Cui, Chung-Kang Peng, Madalena D. Costa, Aner Weiss, Ary L Goldberger, Jeffrey M. Hausdorff. Development of a New Approach to Quantifying Stepping Stability Using Ensemble Empirical Mode Decomposition. Gait &Posture, 2014, 39(1): 495-500. 

16.    Jing Wang, Pengjian Shang, Xingran Cui. Multiscale multifractal analysis of traffic signals to uncover richer structures. Physical Review E, 2014,89(3), 032916. 

17.    Xingran Cui, Andrew Galica, Brad Manor, Chung-Kang Peng, Vera Novak. Multiscale Glycemic Fluctuations and Functional Outcomes –A Novel Multimodal Approach. DIABETES, 2012,61:A220.

18.    Xingran Cui, Chung-Wu Lin, Maysam F. Abbod, Quan Liu, Jiann-Shing Shieh. Diffuse Large B-cell Lymphoma Classification Using Linguistic Analysis and Ensembled Artificial Neural Networks. Journal of the Taiwan Institute of Chemical Engineers, 2012, 43(1): 15-23. 

19.    Xingran Cui, Maysam F. Abbod, Quan Liu, Jiann-Shing Shieh, T.Y. Chao, C.Y.Hsieh, Y.C. Yang. Ensembled artificial neural networks to predict the fitness score for body composition analysis. Journal of Nutrition Health & Aging, 2011, 15 (5): 341-348. 

20.    Jiann-Shing Shieh, Maysam F. Abbod, Kai-YuanCheng, Xing-Ran Cui, Sheng-Jean Huang, Yin-Yi Han. Ensembled neural networks for brain death prediction for patients with severe head injury. Biomedical Signal Processing and Control, 2011, 6(4):414-421. 

21.  Quan Liu, Xingran Cui, Maysam F Abbod, Sheng-Jean Huang, Yin-Yi Han, Jiann-Shing Shieh. Brain death prediction based on ensembled artificial neural networks in neurosurgical intensive care unit. Journal of the Taiwan Institute of Chemical Engineers, 2011, 42(1):97-107.