바이오닉스연구센터

LEE, JONG MIN   Senior Researcher

Phone

02-958-5669

Email

 ljm2293@kist.re.kr

Office

L7-415

Homepage

– Ph.D. Hanyang University, Precision Mechanical Engineering (2005)
– M.S. Hanyang University, Precision Mechanical Engineering (1992)
– B.S. Hanyang University, Precision Mechanical Engineering (1985)

– Researcher/Senior Researcher, Korea Institute of Science & Technology (KIST) (1992~)
– R&D Engineer, Pacific Controls Co., Ltd. (1988~1989)

– Bio-signal based motor intention recognition for manipulating a rehabilitation exoskeleton with top-down approach
– Bio-signal processing and pattern recognition
– Intelligent condition monitoring

– Noninvasive atrial activity extraction method in multilead surface electrocardiogram (Korean patent: 10-1498581, US patent: 10058261)

– Recognition method of human walking speed intention from surface electromyogram signals of plantar flexor and walking speed control method of a lower-limb exoskeleton robot (Korean patent: 10-1498581, US patent(pending): 15/001891)

– Human joint kinematics extraction method from multi-channel surface electromyography signal (Korean patent: 10-1666399)

– Method of monitoring machine condition (Korean patent: 10-1040926, US patent: 8,426,771)

– Technology transfer of monitoring machine condtion to InnoSignal Co. & ATSignal Co

– “Development of Gait Rehabilitation System Capable of Assisting Pelvic Movement of Normal Walking,” Acta Medica Okayama, vol. 72, no. 4, pp. 407-417, 2018.

– “Prediction Method of Walking Speed at Swing Phase using Soleus Electromyogram Signal at Previous Stance Phase,” in Proceedings of Annual International Conference of the IEEE EMBS (EMBC2018), Honolulu, USA, 2018, pp. 2308-2311.

– “Walking Speed Intention Model using Soleus Electromyogram Signal of Nondisabled and Post-stroke Hemiparetic Patients,” in Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR2017), London, UK, 2017, pp. 308-313.

– “Informative Sensor Selection and Learning for Prediction of Lower-limb Kinematics using Generative Stochastic Neural Networks,” in Proceedings of Annual International Conference of the IEEE EMBS (EMBC2017), Jeju, Korea, 2017, pp. 2043-2046.

– “Recognition of Patient’s Intention and Robotic Rehabilitation: Focusing on Gait Rehabilitation,” Robot and Human (Journal of Korea Robotic Society, vol. 13, no. 2, pp. 32-37, 2016 (in Korean).

– “Intention Recognition Method for Sit-to-Stand and Stand-to-Sit from Electromyogram Signals for Overground Lower-Limb Rehabilitation Robots,” in Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM2015), Busan, Korea, 2015, pp. 418-421.

– “Recognition Delay and Recognition Rate of Knee Motor Intention Recognized by Electromyogram and Continuous Hidden Markov Model,” in Proceedings of the International Conference on Control, Automation and System (ICCAS2014), Seoul, Korea, 2014, pp. 357-360.

– “A new machine condition monitoring method based on likelihood change of a stochastic model,” Mechanical Systems and Signal Processing, vol. 41, no. 1, pp. 357-365, 2013.