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Dive into the research topics where Kaspar Althoefer is active.

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Featured researches published by Kaspar Althoefer.


IEEE Sensors Journal | 2008

State-of-the-Art in Force and Tactile Sensing for Minimally Invasive Surgery

Pinyo Puangmali; Kaspar Althoefer; Lakmal D. Seneviratne; Declan Murphy; Prokar Dasgupta

Haptic perception plays a very important role in surgery. It enables the surgeon to feel organic tissue hardness, measure tissue properties, evaluate anatomical structures, and allows him/her to commit appropriate force control actions for safe tissue manipulation. However, in minimally invasive surgery, the surgeons ability of perceiving valuable haptic information through surgical instruments is severely impaired. Performing the surgery without such sensory information could lead to increase of tissue trauma and vital organic tissue damage. In order to restore the surgeons perceptual capability, methods of force and tactile sensing have been applied with attempts to develop instruments that can be used to detect tissue contact forces and generate haptic feedback to the surgeon. This paper reviews the state-of-the-art in force and tactile sensing technologies applied in minimally invasive surgery. Several sensing strategies including displacement-based, current-based, pressure-based, resistive-based, capacitive-based, piezoelectric-based, vibration-based, and optical-based sensing are discussed.


IEEE Transactions on Industrial Electronics | 2014

Control Design for Interval Type-2 Fuzzy Systems Under Imperfect Premise Matching

Hak-Keung Lam; Hongyi Li; Christian Deters; Emanuele Lindo Secco; Helge A. Wurdemann; Kaspar Althoefer

This paper focuses on designing interval type-2 (IT2) control for nonlinear systems subject to parameter uncertainties. To facilitate the stability analysis and control synthesis, an IT2 Takagi-Sugeno (T-S) fuzzy model is employed to represent the dynamics of nonlinear systems of which the parameter uncertainties are captured by IT2 membership functions characterized by the lower and upper membership functions. A novel IT2 fuzzy controller is proposed to perform the control process, where the membership functions and number of rules can be freely chosen and different from those of the IT2 T-S fuzzy model. Consequently, the IT2 fuzzy-model-based (FMB) control system is with imperfectly matched membership functions, which hinders the stability analysis. To relax the stability analysis for this class of IT2 FMB control systems, the information of footprint of uncertainties and the lower and upper membership functions are taken into account for the stability analysis. Based on the Lyapunov stability theory, some stability conditions in terms of linear matrix inequalities are obtained to determine the system stability and achieve the control design. Finally, simulation and experimental examples are provided to demonstrate the effectiveness and the merit of the proposed approach.


IEEE Sensors Journal | 2002

State of the art in sensor technologies for sewer inspection

Olga Duran; Kaspar Althoefer; Lakmal D. Seneviratne

This paper reviews the state of the art in sensors and automated inspection devices for enhanced sewer inspection. Efficiency, safety, environmental, and legislative concerns have made inspection and assessment of communal sewers a central issue to water and sewerage companies. Nowadays, the standard sewer inspection system is based on a wheeled platform on which a closed circuit television (CCTV) camera is mounted. One of the disadvantages of camera inspection systems is that they can only detect a small proportion of all possible damage in a sewer. The inspection outcome of such systems relies not only on the quality of the acquired images, but also on the off-line. recognition and classification conducted by human operators. In consequence, CCTV-based platforms are frequently not effective. Infrared, microwave, optical, and ultrasonic-based sensors have been proposed to complement the existing CCTV-based approach and to improve inspection results. New inspection devices employing multiple sensors and being capable of carrying out remote sewer inspection tasks are under research.


IEEE Transactions on Biomedical Engineering | 2010

Rolling Mechanical Imaging for Tissue Abnormality Localization During Minimally Invasive Surgery

Hongbin Liu; David P. Noonan; Benjamin Challacombe; Prokar Dasgupta; Lakmal D. Seneviratne; Kaspar Althoefer

We describe a novel approach for the localization of tissue abnormalities during minimally invasive surgery using a force-sensitive wheeled probe. The concept is to fuse the kinaesthetic information from the wheel-tissue rolling interaction into a pseudocolor rolling mechanical image (RMI) to visualize the spatial variation of stiffness within the internal tissue structure. Since tissue abnormalities are often firmer than the surrounding organ or parenchyma, a surgeon then can localize abnormalities by analyzing the image. Initially, a testing facility for validating the concept in an ex vivo setting was developed and used to investigate rolling ¿wheel-tissue¿ interaction. A silicone soft-tissue phantom with embedded hard nodules was constructed to allow for experimental comparison between an RMI and a known soft-tissue structure. Tests have also been performed on excised porcine organs to show the efficacy of the method when applied to biological soft tissues. Results indicate that the RMI technique is particularly suited to identifying the stiffness distribution within a tissue sample, as the continuous force measurement along a given rolling trajectory provides repeatable information regarding relative variations in the normal tissue response. When compared to multiple discrete uniaxial indentations, the continuous measurement approach of RMI is shown to be more sensitive and facilitates coverage of a large area in a short period of time. Furthermore, if parametric classification of tissue properties based on a uniaxial tissue indentation model is desirable, the rolling indentation probe can be easily employed as a uniaxial indenter.


IEEE Sensors Journal | 2010

MRI-Compatible Fiber-Optic Force Sensors for Catheterization Procedures

Panagiotis Polygerinos; Dinusha Zbyszewski; Tobias Schaeffter; Reza Razavi; Lakmal D. Seneviratne; Kaspar Althoefer

Cardiac catheterization is an interventional procedure that is usually carried out without the use of force sensors. During such procedures the physician mainly relies on visual feedback provided by an imaging modality, like X-ray fluoroscopy, Computed Tomography (CT) or Magnetic Resonance Imaging (MRI). Hence, the physician it is not always able to predict the forces between the catheter and blood vessel walls. Sometimes, tasks such as moving a catheter through delicate blood vessel networks and through the heart chambers become difficult. This paper provides an overview of fiber-optic pressure and force sensors for cardiac catheters with potential for providing haptic feedback. In conjunction with an MRI scanner the overall cardiac catheterization procedure could be enhanced. The paper focuses on fiber-optic sensors due to their very good MRI compatibility. Background information on manual and robotic catheterization approaches is provided together with an analytic discussion of the current state-of-the-art in fiber-optic force and pressure sensors for catheters, which can provide haptic information.


intelligent robots and systems | 2012

Design of a variable stiffness flexible manipulator with composite granular jamming and membrane coupling

Allen Jiang; Georgios Xynogalas; Prokar Dasgupta; Kaspar Althoefer; Thrishantha Nanayakkara

Robotic manipulators for minimally invasive surgeries have traditionally been rigid, with a steerable end effector. While the rigidity of manipulators improve precision and controllability, it limits reachability and dexterity in constrained environments. Soft manipulators with controllable stiffness on the other hand, can be deployed in single port or natural orifice surgical applications to reach a wide range of areas inside the body, while being able to passively adapt to uncertain external forces, adapt the stiffness distribution to suit the kinematic and dynamic requirements of the task, and provide flexibility for configuration control. Here, we present the design of a snake-like laboratory made soft robot manipulator of 20 mm in average diameter, which can actuate, soften, or stiffen joints independently along the length of the manipulator by combining granular jamming with McKibben actuators. It presents a comprehensive study on the relative contributions of the granule size, material type, and membrane coupling on the range, profile, and variability of stiffness.


IEEE Transactions on Robotics | 2011

Rolling Indentation Probe for Tissue Abnormality Identification During Minimally Invasive Surgery

Hongbin Liu; Jichun Li; Xiaojing Song; Lakmal D. Seneviratne; Kaspar Althoefer

This paper presents a novel optical fiber-based rolling indentation probe designed to measure the stiffness distribution of a soft tissue while rolling over the tissue surface during minimally invasive surgery. By fusing the measurements along rolling paths, the probe can generalize a mechanical image to visualize the stiffness distribution within the internal tissue structure. Since tissue abnormalities are often firmer than the surrounding organ or parenchyma, a surgeon then can localize abnormalities by analyzing the image. The performance of the developed probe was validated using simulated soft tissues. Results show that the probe can measure both force and indentation depth accurately with different orientations when the probe approached and rolled on the tissue surface. In addition, experiments for tumor, identification through rolling indentation were conducted. The size and embedded depth of the tumor, as well as the stiffness ratio between the tumor and tissue, were varied during tests. Results demonstrate that the probe can effectively and accurately identify the embedded tumors.


IEEE-ASME Transactions on Mechatronics | 2003

Pipe inspection using a laser-based transducer and automated analysis techniques

Olga Duran; Kaspar Althoefer; Lakmal D. Seneviratne

This paper presents a new sensing methodology for the automated inspection of pipes. Standard inspection systems, as they are for example used in waste pipes and drains, are based on closed-circuit television cameras which are mounted on remotely controlled platforms and connected to remote video recording facilities. Two of the main disadvantages of such camera-based inspection systems are: 1) the poor quality of the acquired images due to difficult lighting conditions and 2) the susceptibility to error during the offline video assessment conducted by human operators. The objective of this research is to overcome these disadvantages and to create an intelligent sensing approach for improved and automated pipe-condition assessment. This approach makes use of a low-cost lighting profiler and a camera which acquires images of the light projections on the pipe wall. A novel method for extracting and analyzing intensity variations in the acquired images is introduced. The image data analysis is based on differential processing leading to highly-noise tolerant algorithms, particularly well suited for the detection of small faults in harsh environments. With the subsequent application of artificial neural networks, the system is capable of recognizing defective areas with a high success rate. Experiments in a range of waste pipes with different diameters and material properties have been conducted and test results are presented.


IEEE Transactions on Automation Science and Engineering | 2007

Automated Pipe Defect Detection and Categorization Using Camera/Laser-Based Profiler and Artificial Neural Network

Olga Duran; Kaspar Althoefer; Lakmal D. Seneviratne

Closed-circuit television (CCTV) is currently used in many inspection applications, such as the inspection of nonaccessible pipe surfaces. This human-oriented approach based on offline analysis of the raw images is highly subjective and prone to error because of the exorbitant amount of data to be assessed. Laser profilers have been recently proposed to project well-defined light patterns, improving the illumination of standard CCTV systems as well as enhancing the capability of automating the assessment process. This research shows that positional (geometrical) as well as intensity information, related to potential defects, can be extracted from the acquired laser projections. While most researchers focus on the analysis of positional information obtained from the acquired profiler signals, here the intensity information contained within the reflected light is also exploited for the purpose of defect classification and visualization. This paper describes novel strategies created for the automation of defect classification in tubular structures and explores new methods to fuse intensity and positional information, achieving improved multivariable defect classification. The acquired camera/laser images are processed in order to extract signal information for the purpose of visualization and map creation for further assessment. Then, a two-stage approach based on image processing and artificial neural networks is used to classify the images. First, a binary classifier identifies defective pipe sections, and then in a second stage, the defects are classified into different types, such as holes, cracks, and protruding obstacles. Experimental results are provided. Note to Practitioners-The method presented in this paper aims to automate the inspection of nonaccessible pipe surfaces. The method was thought to be employed in the inspection of sewers; however, it could be used in many other industrial applications and could also be extended to other shapes rather than tubular structures. A laser ring profiler, consisting, for instance, of a laser diode and a ring projector, can be easily integrated into existing closed-circuit television systems. The proposed algorithm identifies defective areas and categorizes the types of defects, analyzing the successive recorded camera images that will contain the reflected ring of light. The algorithm, that can be used online, makes use of the deformation of the reflected laser ring together with its changes in intensity. The fact of combining the two kinds of data using artificial-intelligent algorithms makes the method robust enough to work in harsh environments


IEEE Transactions on Instrumentation and Measurement | 2010

Mathematical Modeling of Intensity-Modulated Bent-Tip Optical Fiber Displacement Sensors

Pinyo Puangmali; Kaspar Althoefer; Lakmal D. Seneviratne

Intensity-modulated optical fiber displacement sensors have a potential to be used in a number of applications, including those in industry, military, aerospace, and medicine. Compared with other types of optical fiber sensors, intensity-modulated sensors offer distinctive advantages in that they are usually less complex, inexpensive, and less sensitive to thermal-induced strain. They are able to perform accurate contactless sensing while being of a small size and having a wide dynamic range. A common form of the intensity-modulated optical fiber sensor performs its measurement by making use of a pair of straight parallel optical fibers integrated with a moving reflector modulating the reflected optical signal intensity. Although such an optical modulation configuration exhibits good sensing ability, improvement on its performance could still be made to widen the extent of its application areas. This leads to the development of more effective intensity modulation mechanisms utilizing bent-tip optical fibers and a reflector that can either laterally slide or longitudinally move with reference to the central axis of the fibers. This paper describes such alternative sensing structures and demonstrates the derivations of mathematical models proposed for analyzing their sensing characteristics. Based on experimental studies, the models are verified and validated for the analysis of sensitivity and linearity.

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Lakmal D. Seneviratne

University of Science and Technology

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Yohan Noh

King's College London

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