Intelligent Handheld Instrument For Microsurgery & Biotech Micromanipulation

 

PROJECT DESCRIPTION:

The objective is to research in active handheld instruments to enhance human’s manual micromanipulation accuracy (e.g. in microsurgery and cell micromanipulation) and make the accuracy enhancement transparent to the user. The novel active handheld intelligent instrument will in real-time:

1. detect the user's motion
2. distinguish tremulous motion from intended motion
3. actively compensate tremulous motion by manipulating the instrument tip in an equal but opposite motion.

 

1. Overview

Humans have limited precise manual micromanipulation due to inherent erroneous involuntary movements that include:

1. Physiological tremor – generally sinusoidal 8 – 12Hz, up to 50 µm peak-to-peak ophthalmological microsurgery).
2. Non-tremulous motion (e.g., drift, jerk) – aperoidic, amplitude larger than physiological tremor.

Erroneous hand movements affect the quality of micromanipulation and restrict the types of micromanipulation possible in areas such as microsurgery and cell micromanipulation.

 

2. Challenges

Major challenges of realizing erroneous motion compensation in an active handheld instrument, unobtrusively, are:

1. µm accuracy requirement for motion sensing (bandwidth of >12Hz), trajectory tracking (bandwidth of >10Hz) and manipulation.
2. Real-time sensing / tracking, filtering, control and manipulation – time delay (phase shift) between input and output due to causality.
3. Miniaturize sensing and manipulator electromechanical sub-systems (of adequate bandwidth, tracking precision and actuation force) for unobtrusive use in a handheld instrument.

 

3. System Design

Developed a novel intelligent active handheld instrument for tremor compensation (ITrem):

• Senses its own motion.
• Distinguishes tremulous motion from intended motion via an adaptive zero-phase filter.
• Manipulates instrument tip in real-time for active compensation of tremulous motion.
• Less obtrusive and economical approach.

 

Sensing – Motion Quantification and Modeling:

Sensing system block diagram


• Angular motion derived from sensing kinematics algorithm has high resolution but accuracy is hindered by inherent numerical integration drift. Analytical integration is performed instead of numerical integration to obtain the displacement.

 

Filtering – Tremulous Motions Algorithms:

 

Manipulator – Tremulous Motion Active Electromechanical Compensation:

• Instrument tip is manipulated by a piezoelectric driven 3 DOF parallel manipulator for compactness in size, large operating bandwidth, high actuation force, rapid response and large workspace.
• Compensates tremulous motions by deflecting instrument tip in an equal but opposite motion.
• Flexure joints used to avoid backlash and provide better resolution.
• Rapid prototyping process is used to construct the manipulator for cost effectiveness.

• Piezoelectric actuator hysteretic non-linearity is modeled and linearized by a rate-dependent Prandtl-Ishlinskii operator. Using the dynamic hysteresis model, an open-loop inverse feedfoward controller is implemented to track dynamic motion profiles.

 

4. Results

5. Conclusion

An unobtrusive and compact all-accelerometer active handheld instrument to enhance human's manual micromanipulation accuracy in real-time was developed. This universal approach can be extended to other micromanipulation tasks.

Micromanipulation Evaluation System: An optical based motion tracking system – Micro Motion Sensing System was developed for evaluating micromanipulation tasks.

Successful implementation of this technology sees an immediate impact in numerous medical disciplines and biotech research where manual manipulation precision is a premium. These include plastic, neurological, vitreoretinal, otorhinolaryngological, and microvascular microsurgeries, intracytoplamic sperm injection, embryo cell dissection etc. Not only will the quality and consistency of many microsurgeries be raised and maintained, new doors are also opened to many potential treatments, procedures and research.

Future Work: Further enhance performance by research in active compensation of low frequency and aperiodic motion (e.g. drift, jerk), snap-to-target guidance aid, and improve manipulator operating bandwidth and workspace.

 

VIDEO:

 

GRANT:

• S$563,949, Agency for Science, Technology and Research (A*STAR), SERC Public Funding, Grant #052 101 0017.
  1 August 2005 - 31 July 2008.
• S$150,000, Seed Funding, College of Engineering, NTU.
  1 April 2005 - 31 March 2009.

 

PERSONNEL:

 

PUBLICATIONS:

Book Chapter:

1. 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," Human-Robot Interaction, Vienna, Austria, Advanced Robotic Systems, 2007.

 

Refereed Journal:

1. K. C. Veluvolu, U.-X. Tan, W. T. Latt, C. Y. Shee, and W. T. Ang, “Double adaptive bandlimited multiple Fourier linear combiner for real-time estimation/filtering of tremor,” Biomedical Signal Processing and Control Journal, 2009, (in press).
2. 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,” IEEE/ASME Trans. Mechatronics, 2009, (in press).
3. 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, 2009.
4. Y. L. Zhang, M. L. H. amd C. Y. Shee amd T. F. CHIA, and W. T. Ang, “Self-calibration method for vision-guided cell micromanipulation systems,” Journal of Microscopy, vol. 233, no. 2, pp. 340–345, 2009.
5. U.-X. Tan, K. C. Veluvolu, W. T. Latt, C. Y. Shee, C. N. Riviere, and W. T. Ang, “Estimating displacement of periodic motion with inertial sensors,” IEEE Sensors J., vol. 8, no. 8, pp. 1385–1388, 2008.
6. 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. 1–8, Apr. 2007.
7. 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, Feb. 2007.

 

Refereed Journal (under review/revision):

1. W. T. Latt, U.-X. Tan, K. C. Veluvolu, C. N. Riviere, and W. T. Ang, “Real-time estimation and prediction of physiological tremor from attenuated and phase-shifted sensed signals,” IEEE Trans. Biomed. Eng., (submitted).
2. W. T. Latt, U. X. Tan, C. Y. Shee, and W. T. Ang, “Design, implementation and calibration of an optical micro motion sensing system,” IEEE Sensors J., (review).
3. W. T. Latt, U. X. Tan, C. Y. Shee, and W. T. Ang, “Compact sensing design of a hand-held active tremor compensation instrument for better ergonomics,” IEEE Sensors J., (review).
4. K. C. Veluvolu, U. X. Tan, W. T. Latt, C. Y. Shee, and W. T. Ang, “Estimation and filtering of physiological tremor for surgical robotics applications,” IEEE Trans. Biomed. Eng., (review).

 

Refereed Conference:

1. W. T. Latt, U.-X. Tan, C. Y. Shee, and W. T. Ang, “Research, design, and development of a compact active hand-held physiological tremor compensation instrument,” in IEEE/ASME Intl. Conf. Advanced Intelligent Mechatronics, Singapore, Jul. 2009, (in press).
2. W. T. Latt, U.-X. Tan, C. Y. Shee, and W. T. Ang, “Real-time estimation and prediction of periodic signals from attenuated and phase-shifted sensed signals,” in IEEE/ASME Intl. Conf. Advanced Intelligent Mechatronics, Singapore, Jul. 2009, (in press).
3. W. T. Latt, U.-X. Tan, K. C. Veluvolu, C. Y. Shee, and W. T. Ang, “Identification of accelerometer orientation errors and compensation for acceleration estimation errors,” in Proc. IEEE Intl. Conf. Robotics and Automation, Kobe, Japan, May 2009, (in press).
4. U.-X. Tan, W. T. Latt, C. Y. Shee, and W. T. Ang, “Design and development of a low-cost flexure-based hand-held micromanipulator,” in Proc. IEEE Intl. Conf. Robotics and Automation, Kobe, Japan, May 2009, (in press).
5. W. T. Latt, U. X. Tan, F. Widjaja, and W. T. Ang, “Placement of accelerometers in a hand-held active tremor compensation instrument for high angular sensing resolution,” in 2008 IEEE Intl. Conf. Robotics and Biomimetics, Bangkok, Thailand, Feb. 2009, (in press).
6. W. T. Latt, U. X. Tan, K. C. Veluvolu, C. Y. Shee, and W. T. Ang, “Physiological tremor sensing using only accelerometers for real-time compensation,” in 2008 IEEE Intl. Conf. Robotics and Biomimetics, Bangkok, Thailand, Feb. 2009, (in press).
7. K. C. Veluvolu, U. X. Tan, W. T. Latt, C. Y. Shee, and W. T. Ang, “Double adaptive bandlimited multiple Fourier linear combiner for estimation of tremor,” in 2008 IEEE Intl. Conf. Robotics and Biomimetics, Bangkok, Thailand, Feb. 2009, (in press).
8. W. T. Latt, U. X. Tan, C. Y. Shee, and W. T. Ang, “Handling light disturbances in a micro motion sensing system and investigation of the system performance,” in Proc. 2nd IEEE RAS & EMBS Intl. Conf. Biomedical Robotics and Biomechatronics, Scottsdale, AZ, USA, Oct. 2008, pp. 463–468.
9. W. T. Latt, U. X. Tan, C. Y. Shee, and W. T. Ang, “Compact sensing design of a hand-held active tremor compensation instrument for better ergonomics,” in Proc. 2nd IEEE RAS & EMBS Intl. Conf. Biomedical Robotics and Biomechatronics, Scottsdale, AZ, USA, Oct. 2008, pp. 276–281.
10. M. Han, Y. Zhang, C. Y. Shee, and W. T. Ang, “Estimation of the cell deformation,” in Proc. 1st Intl. Conf. Intelligent Robotics and Applications, vol. 5315 LNAI, no. Part 2, Wuhan, China, Oct. 2008, pp. 217–223.
11. M. Han, Y. Zhang, C. Y. Shee, T. F. Chia, and W. T. Ang, “Plant cell injection based on autofocusing algorithm,” in IEEE Conf. Robotics, Automation and Mechatronics, Chengdu, China, Sep. 2008, pp. 439–443.
12. W. T. Latt, E. S. Ananda, S. C. L. Ong, K. C. Veluvolu, C. Y. Shee, and W. T. Ang, “Design and implementation of a two degree-offreedom micromanipulation assessment system,” in Proc. 30th Annual Intl. Conf. IEEE Engineering in Medicine and Biology Society, Vancouver, BC, Canada, Aug. 2008, pp. 5640–5643.
13. W. T. Latt, U. X. Tan, F. Widjaja, C. Y. Shee, and W. T. Ang, “A study of a hand-held instruments angular motion due to physiological tremor in micromanipulation tasks,” in Proc. 30th Annual Intl. Conf. IEEE Engineering in Medicine and Biology Society, Vancouver, BC, Canada, Aug. 2008, pp. 1952–1955.
14. Y. Zhang, M. Han, C. Y. Shee, and W. T. Ang, “Calibration of piezoelectric actuator-based vision guided cell microinjection system,” in IEEE/ASME Intl. Conf. Advanced Intelligent Mechatronics, Xi’an, China, Jul. 2008, pp. 808–812.
15. U. X. Tan, F. Widjaja, W. T. Latt, K. Veluvolu, C. Y. Shee, C. N. Riviere, and W. T. Ang, “Adaptive rate-dependent feedforward controller for hysteretic piezoelectric actuator,” in Proc. IEEE Intl. Conf. Robotics and Automation, Pasadena, CA, USA, May 2008, pp. 787–792.
16. M. L. Han, Y. Zhang, C. Y. Shee, and W. T. Ang, “Injection of microbiological cells using microscopic focus method,” in 3rd Asian Conf. Computer Aided Surgery, Singapore, Dec. 2007.
17. Y. Zhang, M. Han, C. Y. Shee, T. F. Chia, and W. T. Ang, “Automatic vision guided small cell injection: Feature detection, positioning, penetration and injection,” in Proc. IEEE Intl. Conf. Mechatronics and Automation, Harbin, China, Aug. 2007, pp. 2518–2523.
18. Y. Zhang, M. Han, C. Y. Shee, T. F. Chia, and W. T. Ang, “Position control using 2D-to-2D feature correspondences in vision guided cell micromanipulation,” in Proc. 29th Annual Intl. Conf. IEEE Engineering in Medicine and Biology Society, Lyon, France, Aug. 2007, pp. 1449–1452.
19. K. C. Veluvolu, U. X. Tan, W. T. Latt, C. Y. Shee, and W. T. Ang, “Bandlimited multiple Fourier linear combiner for real-time tremor compensation,” in Proc. 29th Annual Intl. Conf. IEEE Engineering in Medicine and Biology Society, Lyon, France, Aug. 2007, pp. 2847–2850.
20. W. T. Latt, U. X. Tan, K. C. Veluvolu, J. K. D. Lin, C. Y. Shee, and W. T. Ang, “System to assess accuracy of micromanipulation,” in Proc. 29th Annual Intl. Conf. IEEE Engineering in Medicine and Biology Society, Lyon, France, Aug. 2007, pp. 5743–5746.
21. U. X. Tan, T. L. Win, C. Y. Shee, and W. T. Ang, “Rate-dependent hysteresis model of piezoelectric using singularity free Prandtl-Ishlinskii model,” in Proc. IEEE Intl. Symposium Computational Intelligence in Robotics and Automation, Florida, USA, Jun. 2007, pp. 356–361.
22. U. X. Tan, W. T. Latt, M. Tanjaya, H. T. Wirawan, C. Y. Shee, and W. T. Ang, “Real-time disturbance compensation with accelerometers and piezoelectric-driven mechanism,” in Proc. IEEE Intl. Symposium Computational Intelligence in Robotics and Automation, Jacksonville, FL, USA, Jun. 2007, pp. 410–415.
23. T. L. Win, U. X. Tan, C. Y. Shee, and W. T. Ang, “Design and calibration of an optical micro motion sensing system for micromanipulation tasks,” in Proc. IEEE Intl. Conf. Robotics and Automation, Roma, Italy, Apr. 2007, pp. 3383–3388.
24. Y. Zhang, W. T. Ang, J. Jin, and Z. Man, “Non-linear sliding mode control for a rotary inverted pendulum,” in Proc. Intl. MultiConference Engineers and Computer Scientists, vol. 2, Hong Kong, Mar. 2007, pp. 1433–1438.
25. U. X. Tan, T. L. Win, and W. T. Ang, “Modeling piezoelectric actuator hysteresis with singularity free Prandtl-Ishlinskii model,” in IEEE Intl. Conf. Robotics and Biomimetics, Kunming, China, Dec. 2006, pp. 251–256.
26. W. T. Ang, M. Krichane, and T. Sim, “Zero phase filtering for active compensation of periodic physiological motion,” in Proc. 1st IEEE RAS & EMBS Intl. Conf. on Biomedical Robotics and Biomechatronics, Feb. 2006, pp. 182–187.