In this paper we investigate the transient behavior of a simple active catheter: a central tube actuated by a single nitinol tendon enclosed by an outer sleeve. Dynamic models are developed to characterize the transient behavior and optimize the design of an experimental prototype. The bending mechanics are derived using a circular arc model and are experimentally validated. Nitinol actuation is described using the Seelecke-Muller-Achenbach model for single-crystal shape memory alloys using experimentally determined parameters. The dynamic characteristics of this active catheter system are simulated and compared with experimental results. Joule heating is used to generate tip deflections, which are computed in real time using a dual-camera imaging system. The effects of outer sleeve thickness on heat transfer and transient response characteristics are studied.

This paper introduces a novel recurrent neural network, the hysteretic recurrent neural network (HRNN), that is ideally suited to modeling hysteretic materials and systems. This network incorporates a hysteretic neuron consisting of conjoined sigmoid activation functions. Although similar hysteretic neurons have been explored previously, the HRNN is unique in its utilization of simple recurrence to 'self-select' relevant activation functions. Furthermore, training is facilitated by placing the network weights on the output side, allowing standard backpropagation of error training algorithms to be used. We present two-and three-phase versions of the HRNN for modeling hysteretic materials with distinct phases. These models are experimentally validated using data collected from shape memory alloys and ferromagnetic materials. The results demonstrate the HRNN's ability to accurately generalize hysteretic behavior with a relatively small number of neurons. Additional benefits lie in the network's ability to identify statistical information concerning the macroscopic material by analyzing the weights of the individual neurons.

A novel robotic tool is proposed to enable the surgical removal of tissue from inside the beating heart. The tool is manufactured using a unique metal MEMS process that provides the means to fabricate fully assembled devices that incorporate micron-scale features in a millimeter scale tool. The tool is integrated with a steerable curved concentric tube robot that can enter the heart percutaneously through peripheral vessels. Incorporating both irrigation and aspiration, the tissue removal system is capable of extracting substantial amounts of tissue under teleoperated control by first morselizing it and then transporting the debris out of the heart through the lumen of the robot. Tool design and robotic integration are described, and ex vivo and in vivo large animal experimental results are presented.

A novel robotic tool is proposed to enable the surgical removal of tissue from inside the beating heart. The tool is manufactured using a unique metal MEMS process that provides the means to fabricate fully assembled devices that incorporate micron-scale features in a millimeter scale tool. The tool is integrated with a steerable curved concentric tube robot that can enter the heart through the vasculature. Incorporating both irrigation and aspiration, the tissue removal system is capable of extracting substantial amounts of tissue under teleoperated control by first morselizing it and then transporting the debris out of the heart through the lumen of the robot. Tool design and robotic integration are described and ex vivo experimental results are presented.

Objectives Intracorporeal suturing and knot tying can complicate, prolong or preclude minimally invasive surgical procedures, reducing their advantages over conventional approaches. An automated knot-tying device has been developed to speed suture fixation during minimally invasive cardiac surgery while retaining the desirable characteristics of conventional hand-tied surgeon's knots: holding strength and visual and haptic feedback. A rotating slotted disk (at the instrument's distal end) automates overhand throws, thereby eliminating the need to manually pass one suture end through a loop in the opposing end. Electronic actuation of this disk produces left or right overhand knots as desired by the operator. Methods To evaluate the effectiveness of this technology, 7 surgeons with varying laparoscopic experience tied knots within a simulated minimally invasive setting, using both the automated knot-tying tool and conventional laparoscopic tools. Suture types were 2-0 braided and 4-0 monofilament. Results Mean knot-tying times were 246 ±116 seconds and 102 ±46 seconds for conventional and automated methods, respectively, showing an average 56% reduction in time per surgeon (p=0.003, paired t-test). The peak holding strength of each knot (the force required to break the suture or loosen the knot) was measured using tensile testing equipment. These peak holding strengths were normalized by the ultimate tensile strength of each suture type (57.5 N and 22.1 N for 2-0 braided and 4-0 monofilament, respectively). Mean normalized holding strengths for all knots were 68.2% and 71.8% of ultimate tensile strength for conventional and automated methods, respectively (p= 0.914, paired t-test). Conclusions Experimental data reveal that the automated suturing device has great potential for advancing minimally invasive surgery: it significantly reduced knot-tying times while providing equivalent or greater holding strength than conventionally tied knots.

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This paper details the development of a Neural Network (NN) controller for a Shape Memory Alloy (SMA) actuated catheter, with potential application to tele-operated cardiac ablation procedures. The robotic catheter prototype consists of a central tubular structure actuated by four SMA tendons. A dual-camera imaging system provides position feedback of the catheter tip. Open loop bending responses are obtained and associated nonlinearities are identified. A NN controller is designed using time-shifted input-output maps generated from randomized open loop measurements. The tracking performance of this NN controller is compared with PI/PID controllers for various reference trajectories.