聂泽东 男 研究员 博士生导师 中国科学院深圳先进技术研究院
深圳市首批青年创新创业人才,深圳市高层次人才
深圳市主动健康与智慧诊疗技术概念验证中心主任
人体感知与主动健康实验室负责人
广东省基层医疗工程中心和深圳发改委医疗电子平台副主任
中国卫生信息与健康医疗大数据学会糖尿病专业委员会常务委员中国指挥与控制学会智能可穿戴技术专业委员会委员;
中国人工智能学会智慧医疗专业委会委员;
中国生物医学工程学会健康工程分会专委会委员
长期从事人体感知、智能计算与主动健康研究,聚焦无创代谢监测、多模态生理信号分析、可穿戴生物电子、物理—生理耦合建模及人工智能在健康管理中的融合应用,致力于构建“感知—智能—干预”一体化主动健康技术体系。
主持国家重大/重点研发计划课题、国家自然科学基金项目、国防科技创新特区项目等10余项
以第一/通信作者在IEEE TNNLS, IEEE JBHI, IEEE TIM, ARTIFICIAL INTELLIGENCE REVIEW,EXPERT SYST APPL等期刊上发表论文70余篇
申请发明专利90余项,PCT 15项,授权发明专利50余项,美国专利2项,转化发明专利6项,交付重大横向和委托技术与原型系统10余项
获得第十二届中国创造学会创造成果奖一等奖,广东省技术发明二等奖和深圳市技术发明奖二等奖
电子邮件: zd.nie@siat.ac.cn
通信地址: 广东省深圳市南山区西丽大学城学苑大道1068号
研究领域
1、射频人体感知传感器设计
2、人体通信技术、健康物联网(IOT)
3、深度学习/机器学习、数字信号处理、慢病管理算法模型
4、穿戴医疗设备、无创血糖/无创代谢数字标志物监测 高性能穿戴POCT医疗器械
实验室招生信息及报考专业代码
人体感知与主动健康实验室成立于2007年,长期面向人体感知、智能计算与主动健康等方向开展研究。经过多年发展,实验室已形成从可穿戴与近场感知、人体生理信号采集与分析,到智能算法、风险评估与闭环干预的较完整研究体系。实验室始终坚持面向国家需求与真实场景应用,聚焦人体自身状态感知以及人与物、人与机器人的交互问题,致力于发展低成本、低负担、可持续的人体感知与智能技术。历经持续积累,实验室在多模态生理信号分析、无创/低负担监测、物理—生理耦合建模、主动健康与智能交互等方面形成了鲜明特色,逐步发展成为集基础研究、技术创新、人才培养与应用转化于一体的交叉研究平台。
依托人体感知与主动健康实验室平台,欢迎海内外电子信息、计算机、人工智能、生物医学工程、自动化、材料、医学工程等背景的优秀学生加入:
中国科学大大学
博士研究生:
一级学科:计算机科学与技术0812,二级学科:计算机应用技术081203
硕士研究生:
- 学术型硕士,一级学科:计算机科学与技术081200
- 电子信息硕士,一级学科:电子信息085400,专业学位领域:计算机技术085404
海内外其他高校联培博士-硕士研究生计划,请关注招生发布信息。
报考学生需要计算机与电子信息相关专业,包括:
1,计算机专业;
2,电磁场与电磁波;
3,生物医学工程;
4,电子与信息工程;
5,数学等
招生方向
工作经历
2007.05-至今 中国科学院深圳先进技术研究院
专利与奖励
专利成果
主持项目
基于心电等多模态信息的无创血糖监测及穿戴式健康监测设备研发国家级 || 面向射频无创血糖监测机制的人体体素电磁传感模型研究 国家级 || 多模态无创CGM关键技术与系统研究 国家级 || 连续血糖监测中非均匀介质人体组织的射频动态响应机制研究 国家级 || 基于非均匀介质模型的人体通信动态信道传播特性研究 国家级 || 基于人体通信的人-车通信 国家级 || 基于人体通信的身份识别关键技术 国家级 || 基于人体通信技术的无创血糖检测系统研究与开发 省部级 || 用于穿戴式设备的人体通信动态信道传播机制的理论研究与建模分析 省部级 || 应用于普惠健康的人体通信技术的研究 省部级 || 一种基于人体通信的身份认证鉴别研究开发 省部级 || 基于射频的无创血糖检测影响机制及关键技术研究 省部级 || 基于HBC的媒体应用技术合作项目 企业委托
近期论文
[1]. Li J, Ali M, Liu Y, et al. Wearable Noninvasive Blood Glucose Monitoring via ECG: A Multi-Attention Hierarchical Feature Fusion and Fuzzy Integral Approach[J]. IEEE Transactions on Consumer Electronics, 2026: 1-1.
[2].Abdullahi S S, Ali M, Ubaidulah K, et al. RF-BreastNet: An Augmented Hierarchical Feature Extraction Framework for Breast Tumor Detection, Localization, and Size Classification from RF Microwave Signals[J]. IEEE Transactions on Antennas and Propagation, 2026: 1-1,
[3] F. Hassan, M. Ali, Z. Akbar, J. Li, Y. Liu, W. Wang, L. Guo and Z. Nie*, "MuFuBP-Net: A Multimodal Fusion Network for Cuffless Blood Pressure Estimation Using Dual-Feature Pipeline with Probabilistic Feature Encoder,", IEEE Journal of Biomedical and Health Informatics, vol. pp, Apr 23 2025.
[4] M. Gama, S. Abdullahi, M. Omer, Z. Yang, w. xuzhong, Y. Osman, Y. Liu, J. Li, Y. Li, X. Gao and Z. Nie*, "A Novel Manual Rotating Fluid Control Mechanism in a Microfluidic Device with a Finger-Actuated Pump for dual-mode sweat sampling," Lab on a Chip, vol. 25, 04/03 2025.
[5] M. Ali, J. Li, B. Fan and Z. Nie*, "PPG Based Noninvasive Blood Glucose Monitoring Using Multi-View Attention and Cascaded BiLSTM Hierarchical Feature Fusion Approach," IEEE Journal of Biomedical and Health Informatics, vol. 29, no. 7, pp. 4692-4702, 2025.
[6] T. Igbe, A. Kandwal, J. Li, F. Kulwa, O. W. Samuel and Z. Nie*, "Exploring EEG Signals for Noninvasive Blood Glucose Monitoring in Prediabetes Diagnosis," IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-8, 2024.
[7] S. Abdullahi, Z. Yang, M. I. Hassan Gama, M. O. Mohammed Omer, Q. Wang, A. Yakubu and Z. Nie*, "Enhancing the sensitivity and accuracy of wearable glucose biosensors: A systematic review on the prospects of mutarotase," Sensors and Actuators Reports, vol. 8, p. 100231, 2024/12/01/ 2024.
[8] J. Li, J. Ma, O. M. Omisore, Y. Liu, H. Tang, P. Ao, Y. Yan, L. Wang and Z. Nie*, "Noninvasive Blood Glucose Monitoring Using Spatiotemporal ECG and PPG Feature Fusion and Weight-Based Choquet Integral Multimodel Approach," IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 10, pp. 14491-14505, 2024.
[9] A. Kandwal, L. W. Liu, M. J. Deen, R. Jasrotia, B. K. Kanaujia and Z. Nie*, "Electromagnetic Wave Sensors for Noninvasive Blood Glucose Monitoring: Review and Recent Developments," IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-15, 2023.
[10] A. Kandwal, J. Li, T. Igbe, Y. Liu, R. Das, B. K. Kanaujia and Z. Nie*, "Young’s Double Slit Method-Based Higher Order Mode Surface Plasmon Microwave Antenna Sensor: Modeling, Measurements, and Application," IEEE Transactions on Instrumentation and Measurement, vol. 71, pp. 1-11, 2022.
[11] T. Igbe, J. Li, A. Kandwal, O. M. Omisore, E. Yetunde, L. Yuhang, L. Wang and Z. Nie*, "An absolute magnitude deviation of HRV for the prediction of prediabetes with combined artificial neural network and regression tree methods," Artificial Intelligence Review, vol. 55, no. 3, pp. 2221-2244, 2022/03/01 2022.
[12] J. Li, I. Tobore, Y. Liu, A. Kandwal, L. Wang and Z. Nie*, "Non-invasive Monitoring of Three Glucose Ranges Based On ECG By Using DBSCAN-CNN," IEEE Journal of Biomedical and Health Informatics, vol. 25, no. 9, pp. 3340-3350, 2021.
[13] A. Kandwal, Z. Nie*, T. Igbe, J. Li, Y. Liu, L. W. Liu and Y. Hao, "Surface plasmonic feature microwave sensor with highly confined fields for aqueous-glucose and blood-glucose measurements," IEEE Transactions on Instrumentation and Measurement, vol. 70, pp. 1-9, 2020.
[14] A. Kandwal, L. W. Liu, T. Igbe, J. Li, Y. Liu, R. Das, B. K. Kanaujia, L. Wang and Z. Nie*, "A Novel Method of Using Bifilar Spiral Resonator for Designing Thin Robust Flexible Glucose Sensors," IEEE Transactions on Instrumentation and Measurement, vol. 70, pp. 1-10, 2021.
[15] I. Tobore, A. Kandwal, J. Li, Y. Yan, O. M. Omisore, E. Enitan, L. Sinan, L. Yuhang, L. Wang and Z. Nie*, "Towards adequate prediction of prediabetes using spatiotemporal ECG and EEG feature analysis and weight-based multi-model approach," Knowledge-Based Systems, vol. 209, p. 106464, 2020/12/17/ 2020.
[16] J. Li, X. Ma, I. Tobore, Y. Liu, A. Kandwal, L. Wang, J. Lu, W. Lu, Y. Bao, J. Zhou and Z. Nie*, "A Novel CGM Metric-Gradient and Combining Mean Sensor Glucose Enable to Improve the Prediction of Nocturnal Hypoglycemic Events in Patients with Diabetes," (in eng), J Diabetes Res, vol. 2020, p. 8830774, 2020.
[17] I. Tobore, J. Li, L. Yuhang, Y. Al-Handarish, A. Kandwal, Z. Nie* and L. Wang, "Deep Learning Intervention for Health Care Challenges: Some Biomedical Domain Considerations," (in eng), JMIR Mhealth Uhealth, vol. 7, no. 8, p. e11966, Aug 2 2019.
[18] I. Tobore, J. Li, A. Kandwal, L. Yuhang, Z. Nie* and L. Wang, "Statistical and spectral analysis of ECG signal towards achieving non-invasive blood glucose monitoring," (in eng), BMC Med Inform Decis Mak, vol. 19, no. Suppl 6, p. 266, Dec 19 2019.
[19] J. Li, Z. Nie*, Y. Liu, L. Wang and Y. Hao, "Characterization of In-Body Radio Channels for Wireless Implants," IEEE Sensors Journal, vol. 17, no. 5, pp. 1528-1537, 2017.