职称:博士、讲师
院系:工业设计系
邮箱:liuxiangyu@usst.edu.cn
研究方向:多模态人机自然交互设计、可穿戴设计(健康监护方向)、智慧假肢/外骨骼设 计、真实触觉反馈与感知设计
教育经历:
2010-2014华东理工大学 产品设计 学士
2014-2017华东理工大学 工业设计 硕士
2017-2021华东理工大学 工业设计 博士
研究课题:
2021.01-2023.12 基于肌群间串扰消除模型实现手部智能假肢多自由度运动同步实时控制的研究, 国家青年自然科学基金,参与。
2020.07-2023.06 基于非侵入式运动神经元解码实现智能仿生手灵巧运动控制的研究,上海市自然科学基金,参与。
2020.07-2023.06智能人机系统控制,上海市海外高端人才项目,参与
2019.10-2021.01具有真实触觉的手部智能假肢闭环回路控制的研究,上海市浦江人才计划,参与,结题。
科研项目:
2020.09-2021.06 多自由度灵巧假肢手虚拟人机协同康复系统(项目来源:国家青年自然科学基金(子课题),负责人)
2020.09-2021.02前臂肌电假肢真实触觉诱发系统(项目来源:上海市自然科学基金(子课题),负责人)
2020.02-2020.07智能人机交互数据库(肌电-真实力)采集与发布(项目来源:上海市自然科学基金(子课题),负责人)
2019.12-2020.05肌电假肢泛化控制研究(项目来源:上海市海外高端人才项目(子课题),负责人)
学术论文:
SCI:
1.Liu X, Zhou M, Geng Y, et al. Changes in synchronization of the motor unit in muscle fatigue condition during the dynamic and isometric contraction in the Biceps Brachii muscle[J]. Neuroscience Letters, 2021, 761: 136101.
2.Liu X, Zhou M, Dai C, et al. Generalized Finger Motion Classification Model Based on Motor Unit Voting[J]. Motor Control, 2020, 1(aop): 1-17.
3.Guo Y#, Liu X#, Peng S#, et al. A review of wearable and unobtrusive sensing technologies for chronic disease management[J]. Computers in Biology and Medicine, 2020: 104163.(#共一)
4.Jiang X†, Liu X†, Fan J†, et al. Open Access Dataset, Toolbox and Benchmark Processing Results of High-Density Surface Electromyogram Recordings[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2021, 29: 1035-1046. (†共一)
5.Jiang X, Liu X, Fan J, et al. Enhancing IoT Security via Cancelable HD-sEMG-based Biometric Authentication Password, Encoded by Gesture[J]. IEEE Internet of Things Journal, 2021.
Jiang X, Xu K, Liu X, et al. Neuromuscular password-based user authentication[J]. IEEE Transactions on Industrial Informatics, 2020, 17(4): 2641-2652.
EI:
1.Liu X, Zhou M, Li C, et al. Study on the Morphological Sensitivity of Children’s Companion Robot[C]//International Conference on Human-Computer Interaction. Springer, Cham, 2019: 241-252.(Best Paper Award)
2.Liu X, Wang X, Duan H, et al. Wireless aerobic exercise monitoring system Based on Multimodal Sensors[C]//International Conference on Human-Computer Interaction. Springer, Cham, 2020: 313-324.
3.Liu X, Zhou M. Muscle Fatigue Monitoring: Using HD-sEMG Techniques[C]//International Conference on Human Interaction and Emerging Technologies. Springer, Cham, 2020: 551-556.