Lump detection with a gelsight sensor

A GelSight sensor is a tactile sensing device comprising a clear elastomeric pad covered with a reflective membrane, coupled with optics to measure the membrane's deformations. When the pad is pressed against an object's surface, the membrane changes shape in accord with mechanical and geometrical properties of the object. Since soft tissue is more compliant than hard tissue, one can detect an embedded lump by pressing the GelSight pad against the tissue surface and observing the hump that forms over the lump. We tested this system's sensitivity by constructing phantoms of soft rubber with hard embedded lumps. The system is quite sensitive; for example it could detect a 2mm lump at a depth of 5mm. The sensor was more sensitive than previous tactile lump detectors. It was also better than human observers using their fingertips. Such a capability could help in tumor screening, and could augment the sensory information available in telemedicine or minimally invasive surgery.National Science Foundation (U.S.) (Grant 6922551

Haptic assessment of tissue stiffness in locating and identifying gynaecological cancer in human tissue

Gynaecological surgeons are not able to gather adequate tissue feedback during minimal access surgery for cancer treatment. This can result in failure to locate tumour boundaries and to ensure these are completely resected within tumour-free resection margins. Surgeons achieve significantly better surgical and oncological outcomes if they can identify the precise location of a gynaecological tumour. Indeed, the true nature of tumour, whether benign or cancerous, is often not known prior to surgery. If more details were available in relation to the characteristics that differentiate gynaecological cancer in tumours, this would enable more accurate diagnosis and help in the planning of surgery. HYPOTHESIS: Haptic technology has the potential to enhance the surgeon’s degree of perception during minimal access surgery. Alteration in tissue stiffness in gynaecological tumours, thought to be associated with the accelerated multiplication of cancer cells, should allow their location to be identified and help in determining the likelihood of malignancy. METHOD: Setting: (i) Guy's & St Thomas' Hospital (ii) Dept of Informatics (King's College London).Permission from the National Research Ethics Committee and Research & Development (R&D) approval were sought from the National Health Service. The Phantom Omni, capable of 3D motion tracking, attached to a nano-17 force sensor, was used to capture real-time position data and force data. Uniaxial indentation palpation behaviour was used. The indentation depth was calculated using the displacement of the probe from the surface to the deepest point for each contact. The tissue stiffness (TS) was then calculated.The haptic probe was tested first on silicone models with embedded nodules mimicking tumour(s). This was followed by assessing TS ex-vivo using a haptic probe on fresh human gynaecological organs that had been removed in surgery. Tissue stiffness maps were generated in real time using the haptic device by converting stiffness values into RGB values. Surgeons also manually palpated and recorded the site of the tumour. Histology was used as the gold standard for location and cancer diagnosis. Manual palpation and haptic data were compared for accuracy on tumour location. The tissue stiffness calculated by the haptic probe was compared in cancer and control specimens. Several data analysis techniques were applied to derive results.CONTRIBUTIONS: Haptic indentation probe was tested for the first time on fresh human gynaecological organs to locate cancer in a clinical setting. We are the first one to evaluate the accuracy of cancer diagnosis in human gynaecological organs with a force sensing haptic indentation probe measuring tissue stiffness

ESPRESS.0: Eustachian Tube-Inspired Tactile Sensor Exploiting Pneumatics for Range Extension and SenSitivity Tuning

Optimising the sensitivity of a tactile sensor to a specific range of stimuli magnitude usually compromises the sensor’s widespread usage. This paper presents a novel soft tactile sensor capable of dynamically tuning its stiffness for enhanced sensitivity across a range of applied forces, taking inspiration from the Eustachian tube in the mammalian ear. The sensor exploits an adjustable pneumatic back pressure to control the effective stiffness of its 20 mm diameter elastomer interface. An internally translocated fluid is coupled to the membrane and optically tracked to measure physical interactions at the interface. The sensor can be actuated by pneumatic pressure to dynamically adjust its stiffness. It is demonstrated to detect forces as small as 0.012 N, and to be sensitive to a difference of 0.006 N in the force range of 35 to 40 N. The sensor is demonstrated to be capable of detecting tactile cues on the surface of objects in the sub-millimetre scale. It is able to adapt its compliance to increase its ability for distinguishing between stimuli with similar stiffnesses (0.181 N/mm difference) over a large range (0.1 to 1.1 N/mm) from only a 0.6 mm deep palpation. The sensor is intended to interact comfortably with skin, and the feasibility of its use in palpating tissue in search of hard inclusions is demonstrated by locating and estimating the size of a synthetic hard node embedded 20 mm deep in a soft silicone sample. The results suggest that the sensor is a good candidate for tactile tasks involving unpredictable or unknown stimuli

An Affordable and Portable Palpable System for Sensing Breast Tissue Abnormalities

Due to the high cost of equipment and lack of trained personnel, manual palpation is a preferred alternative breast examination technique over mammography. The process involves a thorough search pattern using trained fingers and applying adequate pressure, with the objective of identifying solid masses from the surrounding breast tissue. However, palpation requires skills that must be obtained through adequate training in order to ensure proper diagnosis. Consequently, palpation performance and reporting techniques have been inconsistent. Automating the palpation technique would optimize the performance of self-breast examination, optimize clinical breast examinations (CBE), and enable the visualization of breast abnormalities as well as assessing their mechanical properties. Various methods of reconstructing the internal mechanical properties of breast tissue abnormalities have been explored. However, all systems that have been reported are bulky and rely on complex electronic systems. Hence, they are both expensive and require trained medical professionals. The methods also do not involve palpation, a key element in CBE. This research aims in developing a portable and inexpensive automated palpable system that mimics CBE to quantitatively image breast lumps. The method uses a piezoresistive sensor equipped probe consisting of an electronic circuit for collecting deformation-induced electrical signals. The piezoresistive sensor is made by spraying microwave exfoliated graphite/latex blend on a latex sheet. Lumps can be detected by monitoring a change in electrical resistance caused by the deformation of the sensor which is induced by abnormalities in the breast tissue. The electrical signals are collected using a microcontroller and a pixelated image of the breast can be reconstructed. The research is still in progress, and this report serves as proof of concept testing by pressing the probe with hand pressure and reconstructing the electrical signals using Microsoft Excel. Four maps were created for qualitatively analyzing the result. The pressure maps clearly display areas where pressure was applied, indicating the potential of the probe in detecting breast tissue abnormalities. The pressure maps show the feasibility for using such a sensor for the application in CBE. Furthermore, a sensor such as this is also possible of detecting the depth and size of masses within breast tissue, which, may lead to a more accurate diagnosis. Better manufacturing, accuracy, precision, and real-time data feeds are areas of future consideration for this project. This project involves knowledge and applications from mechanical, electrical, computational, and materials engineering

An Experimental and Numerical Study on Tactile Neuroimaging: A Novel Minimally Invasive Technique for Intraoperative Brain Imaging

This is the peer reviewed version of the following article: Moslem Sadeghi-Goughari, Yanjun Qian, Soo Jeon, Sohrab Sadeghi and Hyock-Ju Kwon, “An Experimental and Numerical Study on Tactile Neuroimaging: A Novel Minimally Invasive Technique for Intraoperative Brain Imaging,” accepted to The International Journal of Medical Robotics and Computer Assisted Surgery which has been published in final form at: https://doi.org/10.1002/rcs.1893. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Background The success of tumor neurosurgery is highly dependent on the ability to accurately localize the operative target, which may be shifted during the operation. Performing an intraoperative brain imaging is crucial in minimally invasive neurosurgery to detect the effect of brain shift on the tumor’s location, and to maximize the efficiency of tumor resection. Method The major objective of this research is to introduce the tactile neuroimaging as a novel minimally invasive technique for intraoperative brain imaging. To investigate the feasibility of the proposed method, an experimental and numerical study was first performed on silicone phantoms mimicking the brain tissue with a tumor. Then the study was extended to a clinical model with the meningioma tumor. Results The stress distribution on the brain surface has high potential to intraoperatively localize the tumor. Conclusion Results suggest that tactile neuroimaging can be used to provide a non-invasive, and real-time intraoperative data on tumor’s features.Natural Sciences and Engineering Research Council || RGPIN/2015-05273, RGPIN/2015-04118, RGPAS/354703-201

Robotic simulators for tissue examination training with multimodal sensory feedback

Tissue examination by hand remains an essential technique in clinical practice. The effective application depends on skills in sensorimotor coordination, mainly involving haptic, visual, and auditory feedback. The skills clinicians have to learn can be as subtle as regulating finger pressure with breathing, choosing palpation action, monitoring involuntary facial and vocal expressions in response to palpation, and using pain expressions both as a source of information and as a constraint on physical examination. Patient simulators can provide a safe learning platform to novice physicians before trying real patients. This paper reviews state-of-the-art medical simulators for the training for the first time with a consideration of providing multimodal feedback to learn as many manual examination techniques as possible. The study summarizes current advances in tissue examination training devices simulating different medical conditions and providing different types of feedback modalities. Opportunities with the development of pain expression, tissue modeling, actuation, and sensing are also analyzed to support the future design of effective tissue examination simulators

Tactile sensing using elastomeric sensors

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 99-111).GelSight, namely, elastomeric sensor, is a novel tactile sensor to get the 3D information of contacting surfaces. Using GelSight, some tactile properties, such as softness and roughness, could be gained through image processing techniques. In this thesis, I implemented GelSight principle to reconstruct surface geometry of tested surfaces, based on which, the roughness comparison and lump detection experiment are conducted. Roughness of five different types of sandpapers are successfully compared using GelSight Ra value. In the lump detection experiment, a visual display for tactile information is presented. To get binary feedback of lump presence or not, a simple threshold method is introduced in this thesis. To evaluate the performance of GelSight sensor, human psychological experiments are conducted. In similar tasks, GelSight sensor outperforms humans in lump detection.by Xiaodan (Stella) Jia.S.M