A triple-jaw actuated and sensorized instrument for grasping large organs during minimally invasive robotic surgery

Human-Inspired Haptic Perception and Control in Robot-Assisted Milling Surgery

Bone milling is one of the most widely used and high-risk procedures in various types of surgeries, and it is important to be noted that the experienced surgeon can perform such an operation safely. The objective of this article is to enhance the safety of the robot-assisted milling operation with the inspiration of human haptic perception. The emergence, coding and perception of the human haptic are introduced. Following this, a single axis accelerometer that measures the vibration of the surgical power tool is mounted in the robot arm, and the recorded acceleration signal is encoded as parallel stream of binary data. The data are subsequently inputted to the Hopfield network so as to identify the milling state. Inspired by human inference procedure, the fuzzy logic controller is introduced to control the robot to track the desired state when performing bone milling operations. A real-time implementation of the proposed method on a digital signal processing is also described. The experimental results in milling porcine spines prove that the robot accurately discriminates different milling states even when the additive noise is serious, and the safe motion control of the robot is also realized.

An extended algorithm for autonomous grasping of soft tissues during robotic surgery

BACKGROUND

Autonomous grasping of soft tissues can facilitate the robotic surgery procedures. The previous attempts for implementing auto-grasping have been based on a simplistic representation of the actual surgery maneuvers.

METHOD

A generalized three-zone grasp model was introduced to consider the effect of the pull force angulation on the grasp mode, that is, damage, slip, or safe grasp. Also, an extended auto-grasping algorithm was proposed in which the trigger force is automatically controlled against the pull force magnitude and direction, to achieve a safe and secure grasp.

RESULTS

The autonomous grasping experiments against a varying pull force in a phantom study indicated a good agreement between the desired and actual pinch and trigger forces (root mean square errors lower than 0.168 N and 0.280 N, respectively) and no sign of tissue tear or slippage.

CONCLUSIONS

The proposed auto-grasping algorithm can help manipulating the soft tissues safely and effectively during robotic surgery procedures.

Real-Time Measurement of the Tool-Tissue Interaction in Minimally Invasive Abdominal Surgery: The First Step to Developing the Next Generation of Smart Laparoscopic Instruments

Introduction Analysis of force application in laparoscopic surgery is critical to understanding the nature of the tool-tissue interaction. The aim of this study is to provide real-time data about manipulations to abdominal organs. Methods An instrumented short fenestrated grasper was used in an in vivo porcine model, measuring force at the grasper handle. Grasping force and duration over 5 small bowel manipulation tasks were analyzed. Forces required to retract gallbladder, bladder, small bowel, large bowel, and rectum were measured over 30 seconds. Four parameters were calculated-T(hold), the grasp time; T(close), time taken for the jaws to close; F(max), maximum force reached; and F(rms), root mean square force (representing the average force across the grasp time). Results Mean F(max) to manipulate the small bowel was 20.5 N (±7.2) and F(rms) was 13.7 N (±5.4). Mean T(close) was 0.52 seconds (±0.26) and T(hold) was 3.87 seconds (±1.5). In individual organs, mean F(max) was 49 N (±15) to manipulate the rectum and 59 N (±13.4) for the colon. The mean F(max) for bladder and gallbladder retraction was 28.8 N (±7.4) and 50.7 N (±3.8), respectively. All organs exhibited force relaxation, the F(rms) reduced to below 25 N for all organs except the small bowel, with a mean F(rms) of less than 10 N. Conclusion This study has commenced the process of quantifying tool-tissue interaction. The static measurements discussed here should evolve to include dynamic measurements such as shear, torque, and retraction forces, and be correlated with evidence of histological damage to tissue.

A modular force-controlled robotic instrument for minimally invasive surgery - efficacy for being used in autonomous grasping against a variable pull force

BACKGROUND

Many deficiencies of minimally invasive robotic surgery systems can be eliminated by using automated laparoscopic tools with force measurement and control capability.

METHOD

A fully modular, automated laparoscopic instrument with a proximal force sensory system was designed and fabricated. The efficacy of the instrument was evaluated experimentally when functioning in an autonomous force-controlled grasping scheme.

RESULTS

The designed instrument was shown to work easily with standard laparoscopic tools, with the whole distal part detachable for autoclave sterilization. The root mean squared error (RMSE) of the actual pinch force from the target ramp was 0.318 N; it was 0.402 N for a sinusoidal pull force, which dropped by 21% using a static friction compensation. A secure grasping condition was achieved, in spite of this error, by applying a sufficiently large margin from the slip boundary.

CONCLUSIONS

With a simple and practical design, the instrument enjoys affordability, versatility and autoclave sterilizability for clinical usage, with an acceptable performance for being used in an auto-grasping control scheme. Copyright © 2016 John Wiley & Sons, Ltd.