Faculty

Share       

​Ang Wei Tech


​Ang Wei Tech
Associate Professor
Associate Chair (Research)
Tel: 6790 5521
Email: WTAng@ntu.edu.sg
Office: N3-02a-25 
   
Education
  • PhD(Robotics) Carnegie Mellon University 2004
  • MEng Nanyang Technological University 2000
  • BEng(Hons) Nanyang Technological University 1997

Biography
Prof Ang is an Associate Professor with the School of Mechanical & Aerospace Engineering since Nov 2004. He received the Ph.D. degree in Robotics from Carnegie Mellon University in 2004, and the M.Eng. and B.Eng degrees in Mechanical Engineering from Nanyang Technological University in 1999 and 1997 respectively. Dr Ang leads a multidisciplinary team focuses on robotic technology in biomedical applications. He is the PI of several projects funded by A*STAR SERC, A*STAR BMRC, NMRC, MOE, NTU & the French Embassy.

Research
  • Interest:
    Robot-Assisted Microsurgery, Rehabilitation Robotics & Mechatronics, Assistive Technology, Assisted-Living Technology.
  • Projects:
    Robot-Assisted Microsurgery & Micromanipulation
    Vision-Aided Active Handheld Instrument for Microsurgery
    We developed an active handheld instrument that detects its own motion, distinguish between undesired and intended motion, and deflects its tip for active compensation of physiological tremor. This project will extend the said capability with image-processing and computer vision techniques to create a handheld vision-aided microsurgical interventional device.
    [Robotics Research Centre , Robotics & Automation]
    Computer Vision Guided Automated Embryo Biopsy
    More details coming soon.
    [Robotics Research Centre , Robotics & Automation]
    Variable Stiffness Actuator
    More details coming soon.
    [Robotics Research Centre , Robotics & Automation]
    Micro-Motion Sensing System
    Detecting micro motion of a microsurgical instrument in real time to aid training of new surgeons and discover more findings about tremor nature of human's hand.
    [Robotics Research Centre , Robotics & Automation]
    Real-Time Image Stabilizer
    Design a zero-phase adaptive filter to accurately separate voluntary and involuntary camera movements in real-time. Filtering of erroneous motion allows to compensate for it while preserving the user's intentional movements.
    [Robotics Research Centre , Robotics & Automation]
    Intelligent Handheld Instrument for Active Error Compensation in Medical and Biotech Micromanipulation Applications
    To enhance human positioning tasks requiring micro level accuracy (e.g. microsurgery, cell micromanipulation). The intelligent instrument will detect motion, distinguish undesired and intended motion and provide real-time active error compensation by deflecting its tip to compensate physiological tremor and other erroneous movement components.
    [Robotics Research Centre , Robotics & Automation]
    Vision-guided Robotic Cell Micromanipulation
    A vision-guided robotic approach is proposed to replace human intervention. A 3 degree-of-freedom piezoelectric-driven robotic manipulator is used to hold a micropipette. A high speed camera captures images of the cells and the micropipette tip under a conventional microscope, processes the images, and controls the robotic manipulator in real-time to perform the intended task.
    [Robotics Research Centre , Robotics & Automation]
    Assessment and Training System for Micromanipulation Tasks in Surgery
    Human accuracy limitations due to physiological tremor restricts the types of feasible microsurgical procedures in microsurgery (e.g., eye, hand, neuro-surgery) making it necessary to train apprentice surgeons and assess their performances. This project investigates the causes of non-voluntary deviations hindering the quality of interventions and develop a virtual reality based training system for training microsurgeons to perform manipulation tasks under a microscope.
    [Robotics Research Centre , Robotics & Automation]

    Rehabilitation Robotics & Assistive Technology
    Adaptive Balance Assistant for Daily Living
    To study the balance problem focusing on problems related to motor tasks controlled by the synergy of control mechanisms allocated between the Central Nervous System (CNS), Peripheral Nervous System (PNS) and Muscle-skeletal system. The approach for balance rehabilitation is to focus more on training of the synergies rather than on single tasks of balance or gait. A device is being developed to bring such rehabilitation therapies into patients' everyday life activity.
    [Robotics Research Centre , Robotics & Automation]
    Pathological Tremor Modeling & Active Compensation via Functional Electrical Stimulations
    We use the sensed physical motion and EMG signals from the upper limb to attenuate the pathological tremor in real time manner. A filtering algorithm will be developed to differentiate the intended motion and the tremor.
    [Robotics Research Centre , Robotics & Automation]
    Pro-Balance
    A mechatronic system provides neuromuscular and vestibular training for rehabilitation patients to improve balancing. Has 5 adjustable level of difficulty, 3 modes of exercise and assessment – multi-axial balancing, anterior-posterior balancing and left-right balancing. Provides real-time visual performance feedback. Records important performance indicators in a session.
    [Robotics Research Centre , Robotics & Automation]
    DEFROST (DEvice for FROzen Shoulder Therapy)
    A mechatronic chain and sprocket trainer system that enhances the effectiveness and usability of the shoulder pulley kit for frozen shoulder therapy at the Singapore General Hospital (Department of Physiotherapy). More control over the plane and range of patients' arm motion during exercises. Provides real-time auditory and visual performance feedback. Records important performance indicators in an exercise session.
    [Robotics Research Centre , Robotics & Automation]
    Objective Assessment of Upper Extremity Function in Neurorehabilitation
    To develop a criterion-referenced approach to objectively assess upper extremity (UE) functions in neurorehabilitation.
    [Robotics Research Centre , Robotics & Automation]
    Soft Robotics
    More details coming soon.
    [Robotics Research Centre , Robotics & Automation]
    Motivation Driven Stroke Rehabilitation via Bio-Signal Control System
    Restore voluntary motor function by bridging gap in damaged/diseased parts of nervous system. A brain-computer interface senses surface electroencephalogram signals elicited by motor imagery & processes it into semantic signals to control functional electrical stimulation of skeletal muscles.
    [Robotics Research Centre , Robotics & Automation]
    Interactive Mixed Reality Rehabilitation System
    This project proposes to integrate advanced techniques in complex system modeling, sensing, biomechanics, interactive digital media and human factors engineering with rehabilitation medicine to develop an intelligent interactive system for post stroke rehabilitation of the upper extremities.
    [Robotics Research Centre , Robotics & Automation]
    Multi-Flexor
    A compact, modular and portable continuous passive motion (CPM) device for wrist and elbow therapy.
    [Robotics Research Centre , Robotics & Automation]

Research Staff and Students under supervision

Research Staff
Name Title Email
SHEE Cheng Yap Research Associate cyshee@ntu.edu.sg
Yan Niang Aye Research Associate YanNA@ntu.edu.sg

Research Students

PhD Students
Name Project​
Carlo Tieso Investigation and Modelling of Human Balance Postural during Standing Tasks for Designing a Robotic Balance Assistant
​Er Jie Kai ​Soft Robotics
​Jatesiktat Prayook ​Details coming soon
Lim Zheng Yi Variable Stiffness Actuator
Wang Zenan Computer Vision Guided Automated Embryo Biopsy
​Yang Niang Aye ​Real-Time High Performance Displacement Sensing in Handheld Instrument for Microsurgery

Selected Publications (click here for full publication list in PDF)
  • Y. N. Aye, S. Zhao, and W. T. Ang, “An enhanced intelligent handheld instrument with visual servo control for 2-dof hand motion error compensation,” Intl. J. Advanced Robotic Systems, vol. 10, no. 355, 2013.
  • K. H. Leo and W. T. Ang, “Nonlinear time normalisation for accurate characterization of normative upper extremity kinematics during reach-to-touch and reach-to-grasp activities,” J. Medical Imaging and Health Informatics, vol. 2, no. 4, pp. 411 – 418, 2012.
  • H. G. Tan, C. Y. Shee, K. H. Kong, C. Guan, and W. T. Ang, “EEG controlled neuromuscular electrical stimulation of the upper limb for stroke patients,” Front. Mech. Eng., vol. 6, no. 1, pp. 71 – 81, Mar. 2011.
  • F. Widjaja, C. Y. Shee, W. L. Au, P. Poignet, and W. T. Ang, “Sensing of pathological tremor using surface electromyography and accelerometer for real-time attenuation,” J. Mechanics in Medicine and Biology, vol. 11, no. 5, pp. 1347 – 1371, Dec. 2011.
  • K. C. Veluvolu, W. T. Latt, and W. T. Ang, “Double adaptive bandlimited multiple Fourier linear combiner for real-time estimation/filtering of tremor,” Biomedical Signal Processing and Control, vol. 5, no. 1, pp. 37 – 44, Jan. 2010.
  • U.-X. Tan, W. T. Latt, K. C. Veluvolu, C. Y. Shee, and W. T. Ang, “Feedforward controller of ill-conditioned hysteresis using singularity free Prandtl-Ishlinskii model,” IEEE/ASME Trans. Mechatronics, vol. 14, no. 5, pp. 598 – 605, Oct. 2009.
  • U.-X. Tan, W. T. Latt, F. Widjaja, C. Y. Shee, C. N. Riviere, and W. T. Ang, “Tracking control of hysteretic piezoelectric actuator using adaptive rate-dependent controller,” Sensors and Actuators A: Physical, vol. 150, no. 1, pp. 116 – 123, Mar. 2009.
  • U. X. Tan, W. T. Latt, C. Y. Shee, C. N. Riviere, and W. T. Ang, “Modeling and control of piezoelectric actuators for active physiological tremor compensation,” in Human-Robot Interaction. I-Tech Education and Publishing, 2007, pp. 369 – 394.
  • W. T. Ang, C. N. Riviere, and P. K. Khosla, “Feedforward controller with inverse rate-dependent model for piezoelectric actuators in trajectory tracking applications,” IEEE/ASME Trans. Mechatronics, vol. 12, no. 2, pp. 134 – 142, Apr. 2007.
  • W. T. Ang, C. N. Riviere, and P. K. Khosla, “Nonlinear regression model of a low-g MEMS accelerometer,” IEEE Sensors J., vol. 7, no. 1 & 2, pp. 81 – 88, Jan. 2007.

Teaching
  • Microprocessor Systems - Hardware
  • Mechanism Design - Analytical Synthesis
  • Surgical Assist Technology