scholarly journals Position Control and Force Estimation Method for Surgical Forceps Using SMA Actuators and Sensors

Materials ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5111
Author(s):  
Dennis Braun ◽  
David Weik ◽  
Sophia Elsner ◽  
Sandra Hunger ◽  
Michael Werner ◽  
...  
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Force Feedback ◽  
Haptic Feedback ◽  
Position Control ◽  
Force Measurement ◽  
Functional Model ◽  
Estimation Method ◽  
Force Estimation ◽  
Mechanical Coupling

Minimally invasive surgery is increasingly used in many medical operations because of the benefits for the patients. However, for the surgeons, accessing the situs through a small incision or natural orifice comes with a reduction of the degrees of freedom of the instrument. Due to friction of the mechanical coupling, the haptic feedback lacks sensitivity that could lead to damage of the tissue. The approach of this work to overcome these problems is to develop a control concept for position control and force estimation with shape memory alloys (SMA) which could offer haptic feedback in a novel handheld instrument. The concept aims to bridge the gap between manually actuated laparoscopic instruments and surgical robots. Nickel-titanium shape memory alloys are used for actuation because of their high specific energy density. The work includes the manufacturing of a functional model as a proof of concept comprising the development of a suitable forceps mechanism and electronic circuit for position control and gripping force measurement, as well as designing an ergonomic user interface with haptic force feedback.

Tool-Tissue Force Estimation for a 3-DOF Robotic Surgical Tool

2015 ◽  
Author(s):  
Baoliang Zhao ◽  
Carl A. Nelson
Keyword(s):  
Haptic Feedback ◽  
Estimation Method ◽  
Tissue Reaction ◽  
Limiting Factor ◽  
Haptic Interfaces ◽  
Force Estimation ◽  
Surgical Tools ◽  
Motor Current ◽  
Surgical Tool ◽  
Reaction Forces

Robotic minimally invasive surgery has achieved success in various procedures; however, the lack of haptic feedback is considered by some to be a limiting factor. The typical method to acquire tool-tissue reaction forces is attaching force sensors on surgical tools, but this complicates sterilization and makes the tool bulky. This paper explores the feasibility of using motor current to estimate tool-tissue forces, and demonstrates acceptable results in terms of time delay and accuracy. This sensorless force estimation method sheds new light on the possibility of equipping existing robotic surgical systems with haptic interfaces that require no sensors and are compatible with existing sterilization methods.

scholarly journals Experimental Investigation of the Mechanisms and Performance of Active Auxetic and Shearing Textiles

2019 ◽  
Author(s):  
Rachael Granberry ◽  
Brad Holschuh ◽  
Julianna Abel
Keyword(s):  
Experimental Investigation ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Haptic Feedback ◽  
Axial Stress ◽  
The Body ◽  
Strain Behavior ◽  
Biaxial Tensile Testing ◽  
And Performance

Abstract Anisotropic textiles are commonly used in wearable applications to achieve varied bi-axial stress-strain behavior around the body. Auxetic textiles, specifically those that exhibit a negative Poisson’s ratio (v), likewise exhibit intriguing behavior such as volume increase in response to impact or variable air permeability. Active textiles are traditional textile structures that integrate smart materials, such as shape memory alloys, shape memory polymers, or carbon nanotubes, to enable spatial actuation behavior, such as contraction for on-body compression or corrugation for haptic feedback. This research is a first experimental investigation into active auxetic and shearing textile structures. These textile structures leverage the bending- and torsional-deformations of the fibers/filaments within traditional textile structures as well as the shape memory effect of shape memory alloys to achieve novel, spatial performance. Five textile structures were fabricated from shape memory alloy wire deformed into needle lace and weft knit textile structures. All active structures exhibited anisotropic behavior and four of the five structures exhibited auxetic behavior upon free recovery, contracting in both x- and y-axes upon actuation (v = −0.3 to −1.5). One structure exhibited novel shearing behavior, with a mean free angle recovery of 7°. Temperature-controlled biaxial tensile testing was conducted to experimentally investigate actuation behavior and anisotropy of the designed structures. The presented design and performance of these active auxetic, anisotropic, and shearing textiles inspire new capabilities for applications, such as smart wearables, soft robotics, reconfigurable aerospace structures, and medical devices.

A Compact and Modular Laparoscopic Grasper With Tridirectional Force Measurement Capability

2008 ◽  
Vol 2 (3) ◽  
Author(s):  
Gregory Tholey ◽  
Jaydev P. Desai
Keyword(s):  
Tissue Characterization ◽  
Force Feedback ◽  
Haptic Feedback ◽  
Modular Design ◽  
Force Measurement ◽  
Robot Assisted ◽  
Measurement Capability ◽  
Laparoscopic Grasper ◽  
Grasping Force ◽  
Conventional Open Surgery

The introduction of minimally invasive surgery (MIS) into the operating room has led to significant advantages over conventional open surgery. Furthermore, the migration toward robot-assisted MIS over the past decade has provided additional advantages. However, the lack of haptic feedback in these tele-operated robotic surgical systems has inhibited the surgeon’s ability to diagnose tissue as healthy or unhealthy, thereby creating a need for force feedback in these systems. This paper presents the design and development of a compact and modular laparoscopic grasper with tridirectional force measurement capability for applications in robot-assisted MIS. The instrumented laparoscopic grasper is capable of measuring the normal grasping force, as well as the manipulation forces (horizontal and vertical) during grasping tasks. The grasper also has a modular design that allows for easy conversion between different surgical modalities, such as grasping, cutting, and dissecting. Preliminary tele-operative experiments with force feedback capability through a haptic feedback device for artificial tissue characterization as well as knot tightening experiments indicate the capability of this grasper.

scholarly journals Two-Fingered Haptic Device for Robot Hand Teleoperation

2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
Futoshi Kobayashi ◽  
George Ikai ◽  
Wataru Fukui ◽  
Fumio Kojima
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Force Feedback ◽  
Haptic Feedback ◽  
Reaction Force ◽  
Feedback System ◽  
Middle Finger ◽  
Distal Segment ◽  
Haptic Device ◽  
Robot Hand

A haptic feedback system is required to assist telerehabilitation with robot hand. The system should provide the reaction force measured in the robot hand to an operator. In this paper, we have developed a force feedback device that presents a reaction force to the distal segment of the operator's thumb, middle finger, and basipodite of the middle finger when the robot hand grasps an object. The device uses a shape memory alloy as an actuator, which affords a very compact, lightweight, and accurate device.

scholarly journals Generalization of spatio-temporal deep learning for vision-based force estimation

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Finn Behrendt ◽  
Nils Gessert ◽  
Alexander Schlaefer
Keyword(s):  
Deep Learning ◽  
Force Feedback ◽  
Haptic Feedback ◽  
Absolute Error ◽  
Estimation Methods ◽  
Temporal Data ◽  
Learning Models ◽  
Force Estimation ◽  
Tissue Samples ◽  
Spatio Temporal

AbstractRobot-assisted minimally-invasive surgery is increasingly used in clinical practice. Force feedback offers potential to develop haptic feedback for surgery systems. Forces can be estimated in a vision-based way by capturing deformation observed in 2D-image sequences with deep learning models. Variations in tissue appearance and mechanical properties likely influence force estimation methods’ generalization. In this work, we study the generalization capabilities of different spatial and spatio-temporal deep learning methods across different tissue samples. We acquire several data-sets using a clinical laparoscope and use both purely spatial and also spatio-temporal deep learning models. The results of this work show that generalization across different tissues is challenging. Nevertheless, we demonstrate that using spatio-temporal data instead of individual frames is valuable for force estimation. In particular, processing spatial and temporal data separately by a combination of a ResNet and GRU architecture shows promising results with a mean absolute error of 15.450 compared to 19.744 mN of a purely spatial CNN.

The Use of Shape Memory Alloy Wires in Actuators

2006 ◽  
Vol 113 ◽  
pp. 195-198 ◽  
Author(s):  
Florian Schiedeck ◽  
Tobias Hemsel ◽  
Jörg Wallaschek
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Position Control ◽  
Qualitative And Quantitative ◽  
Test Beds

Our contribution will describe the basic fundamentals of shape memory alloys. Emphasis will be given to specific characteristics for the use of shape memory wires in actuators. The investigation of shape memory wires in actuators includes qualitative and quantitative benchmarking based on measurements at different test beds. To display applicability of shape memory wires for different tasks, the main focus will be on the influence of different bias forces, the determination of performance, and the possibility of position control without position sensors.

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