Cameron N. Riviere

Adaptive cancelling of physiological tremor for improved precision in microsurgery

Physiological hand tremor impedes microsurgery. We present both a novel adaptive algorithm for tremor estimation and a new technique for active real-time cancelling of physiological tremor. Tremor is modeled online using the weighted-frequency Fourier linear combiner (WFLC). This adaptive algorithm models tremor as a modulating sinusoid, and tracks its frequency, amplitude and phase. Piezoelectric actuators move the surgical instrument tip in opposition to the motion of tremor, effectively subtracting the tremor from the total motion. We demonstrate the technique in 1D using a cantilever apparatus as a benchtop simulation of the surgical instrument. Actual hand motion, prerecorded during simulated surgery, is used as input. In 25 tests, WFLC tremor compensation reduces the RMS tip motion in the 6-16 Hz tremor band by 67%, and reduces the RMS error with respect to an a posteriori estimate of voluntary motion by 30%. The technique can be implemented in a hand-held microsurgical instrument.

Feedforward Controller With Inverse Rate-Dependent Model for Piezoelectric Actuators in Trajectory-Tracking Applications

Effective employment of piezoelectric actuators in microscale dynamic trajectory-tracking applications is limited by two factors: 1) the intrinsic hysteretic behavior of piezoelectric ceramic and 2) structural vibration as a result of the actuators own mass, stiffness, and damping properties. While hysteresis is rate-independent, structural vibration increases as the piezoelectric actuator is driven closer to its resonant frequency. Instead of separately modeling the two interacting dynamic effects, this work treats their combined effect phenomenologically and proposes a rate-dependent modified Prandtl-Ishlinskii operator to account for the hysteretic nonlinearity of a piezoelectric actuator at varying actuation frequency. It is shown experimentally that the relationship between the slope of the hysteretic loading curve and the rate of control input can be modeled by a linear function up to a driving frequency of 40 Hz

Toward active tremor canceling in handheld microsurgical instruments

This paper describes research in active instruments for enhanced accuracy in microsurgery. The aim is to make accuracy enhancement as transparent to the surgeon as possible. Rather than using a robotic arm, we have taken the novel approach of developing a handheld instrument that senses its own movement, distinguishes between desired and undesired motion, and deflects its tip to perform active compensation of the undesired component. The research has therefore required work in quantification and modeling of instrument motion, filtering algorithms for tremor and other erroneous movements, and development of handheld electromechanical systems to perform active error compensation. The paper introduces the systems developed in this research and presents preliminary results.

Design of all-accelerometer inertial measurement unit for tremor sensing in hand-held microsurgical instrument

We present the design of an all-accelerometer inertial measurement unit (IMU). The IMU forms part of an intelligent hand-held microsurgical instrument that senses its own motion, distinguishes between hand tremor and intended motion, and compensates in real-time the erroneous motion. The new IMU design consists of three miniature dual-axis accelerometers, two of which are housed in a sensor suite at the distal end of the instrument handle, and one located at the proximal end close to the instrument tip. By taking the difference between the accelerometer readings, we decouple the inertial and gravitational accelerations from the rotation-induced (centripetal and tangential) accelerations, hence simplifies the kinematic computation of angular motions. We have shown that the error variance of the Euler orientation parameters /spl theta//sub x/, /spl theta//sub y/ and /spl theta//sub z/ is inversely proportional to the square of the distance between the three sensor locations. Comparing with a conventional three gyros and three accelerometers IMU, the proposed design reduces the standard deviation of the estimates of translational displacements by 29.3% in each principal axis and those of the Euler orientation parameters /spl theta//sub x/, /spl theta//sub y/ and /spl theta//sub z/ by 99.1%, 99.1% and 92.8% respectively.

Micron: An Actively Stabilized Handheld Tool for Microsurgery

We describe the design and performance of a handheld actively stabilized tool to increase accuracy in microsurgery or other precision manipulation. It removes involuntary motion, such as tremor, by the actuation of the tip to counteract the effect of the undesired handle motion. The key components are a 3-degree-of-freedom (DOF) piezoelectric manipulator that has a 400-μm range of motion, 1-N force capability, and bandwidth over 100 Hz, and an optical position-measurement subsystem that acquires the tool pose with 4-μm resolution at 2000 samples/s. A control system using these components attenuates hand motion by at least 15 dB (a fivefold reduction). By the consideration of the effect of the frequency response of Micron on the human visual feedback loop, we have developed a filter that reduces unintentional motion, yet preserves the intuitive eye-hand coordination. We evaluated the effectiveness of Micron by measuring the accuracy of the human/machine system in three simple manipulation tasks. Handheld testing by three eye surgeons and three nonsurgeons showed a reduction in the position error of between 32% and 52%, depending on the error metric.

Modeling and canceling tremor in human-machine interfaces

Zero-phase modeling and canceling of tremor can improve precision in human-machine control applications. Past methods of tremor suppression have been hindered by feedback delays due to phase lag and by the inability to track tremor frequency over time. The weighted-frequency Fourier linear combiner (WFLC) is an adaptive noise canceller that precisely models tremor with zero phase lag. This article briefly presents the WFLC algorithm and describes its application to computer input filtering, clinical tremor quantification, and active tremor canceling for microsurgery.

Modeling of Needle Steering via Duty-Cycled Spinning

As flexible bevel tip needles are inserted into tissue, a deflection force causes the needle to bend with a curvature dependent on relative stiffness and bevel angle. By constantly spinning the needle during insertion, the bevel angle is essentially negated and a straight trajectory can be achieved. Incorporating duty-cycled spinning during needle insertion provides proportional control of the curvature of the needle trajectory through tissue. This paper proposes a kinematic model for needle steering via duty-cycled spinning. Validation using experimental results is also presented.

Robotic Compensation of Biological Motion to Enhance Surgical Accuracy

Robotic technologies provide new ways to compensate quasi-periodic biological motion, enabling higher surgical accuracy without invasive measures such as cardiopulmonary bypass. This paper describes current research in robotic compensation of hand tremor, respiratory motion, and heartbeat during surgical procedures. An analysis of each physiological motion pattern is provided, as well as a description of novel compensation techniques

Physical model of a MEMS accelerometer for low-g motion tracking applications

This paper develops a physical model of a MEMS capacitive accelerometer in order to use the accelerometer effectively in low-g motion tracking applications. The proposed physical model includes common physical parameters used to rate an accelerometer: scale factor, bias, and misalignment. Simple experiments used to reveal the behavior and characteristics of these parameters are described. A phenomenological modeling method is used to establish mathematical representations of these parameters in relation to errors such as nonlinearity, hysteresis, cross-axis effect, and temperature effect, without requiring a complete understanding of the underlying physics. Experimental results are presented, in which the physical model reduces RMSE by 93.1% in comparison with the manufacturers recommended method.

Modeling rate-dependent hysteresis in piezoelectric actuators

Hysteresis of a piezoelectric actuator is rate dependent. Most hysteresis models are based on elementary rate independent operators and are not suitable for modeling actuator behavior across a wide frequency band. This work proposes a rate dependent modified Prandtl-Ishlinskii (PI) operator to account for the hysteresis of a piezoelectric actuator at varying frequency. We have shown experimentally that the relationship between the slope of the hysteretic loading curve and the rate of control input can be modeled by a linear function. The proposed rate-dependent hysteresis model is implemented for open-loop control of a piezoelectric actuator. In experiments tracking multi-frequency nonstationary motion profiles, it consistently outperforms its rate-independent counterpart by a factor of two in maximum error and a factor of three in rms error.