近期论文
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期刊论文：
[1] P. S. Sun, D. Xu, J. Mai, Z. Zhou, S. K. Agrawal, Q. Wang: Inertial sensors-based torso motion mode recognition for an active postural support brace. Adv. Robotics, vol. 34, no. 1, pp. 57-67, 2020
[2] X. Liu, Z. Zhou, J. Mai, Q. Wang, Real-time mode recognition based assistive torque control of bionic knee exoskeleton for sit-to-stand and stand-to-sit transitions. Robotics Auton. Syst. Vol. 119,pp. 209-220, 2019
[3] G. Huang, M. Ceccarelli, Q. Huang, W. Zhang, Z. Yu, X. Chen, J. Mai, Design and Feasibility Study of a Leg-exoskeleton Assistive Wheelchair Robot with Tests on Gluteus Medius Muscles. Sensors, vol. 19, no. 3, 548, 2019
[4] S. Crea, S. Manca, A. Parri, E. Zheng, J. Mai, R. M. Lova, N. Vitiello, Q. Wang, Noncontact capacitive sensors are effective for controlling a robotic hip exoskeleton for gait assistance, IEEE/ASME Transactions on Mechatronics, vol. 24, no. 5, pp. 2227-2235, 2019
[5] X. Liu, Z. Zhou, J. Mai, Q. Wang*, Real-time mode recognition based assistive torque control of bionic knee exoskeleton for sit-to-stand and stand-to-sit transitions, Robotics and Autonomous Systems, vol. 119, pp. 209-220, 2019
[6] E. Zheng, J. Mai, Y. Liu, Q. Wang, Forearm motion recognition with noncontact capacitive sensing, Frontiers in Neurorobotics, vol.12, no. 47, pp. 1-13, 2018
[7] D. Xu, Y. Feng, J. Mai, Q. Wang, Real-time on-board recognition of continuous locomotion modes for amputees with robotic transtibial prostheses, IEEE Transactions on Neural Systems & Rehabilitation Engineering, vol. 26, no. 10, pp. 1-11, 2018
[8] Z. Guan, T. Cai, Z. Liu, Y. Dou, X. Hu, P. Zhang, X. Sun, H. Li, Y. Kuang, Q. Zhai, H. Ruan, X. Li, Z. Li, Q. Zhu, J. Mai, Q. Wang, L. Lai, J. Ji, H. Liu, B. Xia, T. Jiang, S. Luo, H. Wang, C. Xie, Origin of the reflectin gene and hierarchical assembly of its protein, Current Biology, vol. 27, no. 18, pp. 2833-2842, 2017
[9] J. Mai, L. Zhang, F. Tao, L. Ren, Customized production based on distributed 3D printing services in cloud manufacturing, International Journal of Advanced Manufacturing Technology, vol. 84, pp. 71-83, 2016
[10] 王启宁, 郑恩昊, 许东方, 麦金耿, 基于非接触式电容传感的人体运动意图识别, 机械工程学报, vol. 55, no. 11, pp. 19-27, 2019
[11] 许东方, 冯仰刚, 麦金耿, 王启宁, 面向速度适应的动力小腿假肢蹬地时刻在线识别, 中国科学:技术科学, vol. 48, no. 12, pp.1321-1330, 2018
[12] 王启宁, 郑恩昊, 陈保君, 麦金耿, 面向人机融合的智能动力下肢假肢研究现状与挑战, 自动化学报, vol. 42, no. 12, pp. 1780-1793, 2016
会议论文：
[1] S. Gao, C. Wang, J. Zhu, J. Mai, Q. Wang, Hydraulic damping adaptation and swing assistance control of a robotic electrohydraulic transfemoral prosthesis: Preliminary results, Proc. of the IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO), Beijing, China, 2019, pp. 365-368.
[2] E. Zheng, Z. Zhang, J. Mai, Q. Wang, H. Qiao, A pilot study on continuous breaststroke phase recognition with fast training based on lower-limb inertial signals, Proc. of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019, pp. 1228-1232.
[3] D. Xu, Y. Yang, J. Mai, Q. Wang, Capacitive sensing based recognition of ankle movement imagery in patients after amputation surgery, Proc. of the IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, Suzhou, China, 2019, pp. 998-1001.
[4] Z. Zhou, X. Liu, Y. Jiang, J. Mai, Q. Wang*, Real-time onboard SVM-based human locomotion recognition for a bionic knee exoskeleton on different terrains, Proc. of the WearRAcon Conference, Arizona, USA, 2019, pp. 34-39.
[5] J. Mai, D. Xu, H. Li, S. Zhang, J. Tan, Q. Wang. Implementing a SoC-FPGA based acceleration system for on-board SVM training for robotic transtibial prostheses, Proc. of the IEEE International Conference on Real-time Computing and Robotics (RCAR), Maldives, 2018, pp. 150-155.
[6] J. Mai, W. Chen, S. Zhang, D. Xu, Q. Wang, Performance analysis of hardware acceleration for locomotion mode recognition in robotic prosthetic control, Proc. of the IEEE International Conference on Cyborg and Bionic Systems (CBS), Shenzhen, China, 2018, pp. 607-611.
[7] P. Sun, J. Mai, Z. Zhou, S. Agrawal, Q. Wang, Upper-body motion mode recognition based on IMUs for a dynamic spine brace, Proc. of the IEEE International Conference on Cyborg and Bionic Systems (CBS), Shenzhen, China, 2018, pp. 167-170.
[8] Z. Zhang, Z. Zhou, E. Zheng, Y. Zhou, S. Zhang, J. Mai, Q. Wang*, Concept and prototype design of an underwater soft exoskeleton, Proc. of the IEEE International Conference on Cyborg and Bionic Systems (CBS), Shenzhen, China, 2018, pp. 139-143.
[9] Y. Lou, R. Wang, J. Mai, N. Wang, Q. Wang, IMU-based gait phase recognition for stroke survivors: preliminary results, Proc. of the IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), Tianjin, China, 2018, pp. 802-806.
[10] D. Xu, Y. Yang, J. Mai, Q. Wang, Muscle redistribution surgery based capacitive sensing for upper-limb motion recognition: Preliminary results, 2017 IEEE International Conference on Cyborg and Bionic Systems (CBS), Beijing, China, 2017, pp. 125-129.
[11] J. Mai, Z. Zhang, Q. Wang, A real-time intent recognition system based on SoC-FPGA for robotic transtibial prosthesis, Proc. of the International Conference on Intelligent Robotics and Applications (ICIRA), Wuhan, China, 2017, pp.280-289.
[12] X. Liu, Z. Zhou, J. Mai, Q. Wang, Multi-class SVM based real-time recognition of sit-to-stand and stand-to-sit transitions for a bionic knee exoskeleton in transparent mode, Proc. of the International Conference on Intelligent Robotics and Applications (ICIRA), Wuhan, China, 2017, pp. 262-272.
[13] D. Xu, Y. Yang, J. Mai, Q. Wang, Muscle redistribution surgery based capacitive sensing for upper-limb motion recognition: Preliminary results, 2017 IEEE International Conference on Cyborg and Bionic Systems (CBS), Beijing, China, 2017, pp. 125-129.
[14] Z. Zhang, D. Xu, Z. Zhou, J. Mai, Z. He, Q. Wang, IMU-based underwater sensing system for swimming stroke classification and motion analysis, Proc. of the IEEE International Conference on Cyborg and Bionic Systems (CBS), Beijing, China, 2017, pp. 268-272.
[15] Z. Zhou, C. Wang, Z. Zhang, J. Mai, S. Yan, Z. Huang, N. Wang, Q. Wang, Mechatronic design of an ankle-foot rehabilitation robot for children with cerebral palsy and preliminary clinical trial, Proc. of the 18th IEEE International Conference on Industrial Technology (ICIT), Toronto, Canada, 2017, pp. 825-830.
[16] J. Mai, L. Zhang, Q. Wang, Z. Fu, Y. He, F. Tao, 3D atmospheric environment monitoring architecture and voronoi diagrams-based concentration estimation model, Proc. of the IEEE/SICE International Symposium on System Integration (SII), Tokyo, Japan, 2014, pp. 690-694.
[17] E. Zheng, J. Mai, Q. Wang, On the design and implementation of a tri-ellipsoid unmanned autonomous blimp, Proc. of the IEEE/SICE International Symposium on System Integration, Tokyo, Japan, 2014, pp. 724-729.
[18] L. Zhang, J. Mai, F. Tao, Y. Luo, L. Ren, Development status of cloud manufacturing in China, ASME 2014 International Manufacturing Science and Engineering Conference, Detroit, USA, 2014, pp. V001T04A013.
[19] Y. Song, J. Mai, S. Yang, J. Tan, Y. Huang, Q. Wang, An unconventional unmanned autonomous blimp: design, modeling and simulation, Proc. of the Asia Simulation Conference, Springer Communications in Computer and Information Science, 2014, pp. 356-367.
[20] Y. He, J. Mai, F. Tao, L. Zhang. Research and Implementation of Smoke Diffusion Parallel Rendering Based on Memory Mapping and Billboard, Proc. of the International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, Ypsilanti, USA, 2014, pp. 235-243.
[21] H. Wang, J. Mai, Y. Song, C. Wang, L. Zhang, F. Tao, Q. Wang, A 3D visualization framework for real-time distribution and situation forecast of atmospheric chemical pollution, Proc. of the Asia Simulation Conference (AsiaSim), Singapore, 2013, pp. 415-420.
[22] J. Mai, L. Zhang, F. Tao, L. Ren, Architecture of hybrid cloud for manufacturing enterprise, Proc. of the Asia Simulation Conference (AsiaSim), Shanghai, China, 2012, pp. 365-372.
[23] J. Mai, Y. Gao, Y. Huang, Q. Wang, L. Zhang, Analyzing effects of ankle-foot parameters on passive bipeds based on dynamic walking modeling, Proc. of the Asia Simulation Conference (AsiaSim), Shanghai, China, 2012, pp. 135-143.
[24] J. Mai, Q. Wang, L. Wang, FPGA-based gait control system for passive bipedal robot, Proc. of the IEEE/RAS 7th International Conference on Humanoid Robots, Pittsburgh, USA, 2007, pp.341-345.
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