Experimental evaluation of robot-assisted tactile sensing for minimally invasive surgery

Trejos, Ana Luisa; Jayender, Jagadeesan; Perri, Melissa T.; Naish, Michael D.; Patel, Rajni V.; Malthaner, Richard

doi:10.1109/biorob.2008.4762808

Cited by 18 publications

(9 citation statements)

References 20 publications

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“…A final challenge is determining the most effective means for relaying the tactile information to a human user (tactile display). Researchers have displayed tactile information both visually [25,29,34,41] and mechanically directly on the fingertips [15,28,29]. For the latter case, recreating the tactile sensations encountered during lump detection is hindered by the difficulty of designing appropriate electro-mechanical devices.…”

mentioning

confidence: 99%

Human vs. robotic tactile sensing: Detecting lumps in soft tissue

Gwilliam

Pezzementi

Jantho

et al. 2010

2010 IEEE Haptics Symposium

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Humans can localize lumps in soft tissue using the distributed tactile feedback and processing afforded by the fingers and brain. This task becomes extremely difficult when the fingers are not in direct contact with the tissue, such as in laparoscopic or robot-assisted procedures. Tactile sensors have been proposed to characterize and detect lumps in robot-assisted palpation. In this work, we compare the performance of a capacitive tactile sensor with that of the human finger. We evaluate the response of the sensor as it pertains to robot-assisted palpation and compare the sensor performance to that of human subjects performing an equivalent task on the same set of artificial tissue models. Furthermore, we investigate the effects of various tissue parameters (lump size, lump depth, and surrounding tissue stiffness) on the performance of both the human finger and the tactile sensor. Using signal detection theory for determining tactile sensor lump detection thresholds, the tactile sensor outperforms the human finger in a palpation task.

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mentioning

confidence: 99%

Human vs. robotic tactile sensing: Detecting lumps in soft tissue

Gwilliam

Pezzementi

Jantho

et al. 2010

2010 IEEE Haptics Symposium

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“…The PMI system was able to determine malignant nodules in 10 of 13 patients with biopsy-confirmed malignant inclusions. Trejos et al [54] and Perri et al [55], [56] developed and enhanced the Tactile Sensing Instrument (TSI) to a more advanced Tactile Sensing System (TSS) by adding a visualization interface (see Fig. 3).…”

Section: ) Non-grasping Palpationmentioning

confidence: 99%

Intra-operative tumour localisation in robot-assisted minimally invasive surgery: A review

Liu

Jiang

et al. 2014

Proc Inst Mech Eng H

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Robot-assisted minimally invasive surgery has many advantages compared to conventional open surgery and also certain drawbacks: it causes less operative trauma and faster recovery times but does not allow for direct tumour palpation as is the case in open surgery. This article reviews state-of-the-art intra-operative tumour localisation methods used in robot-assisted minimally invasive surgery and in particular methods that employ force-based sensing, tactile-based sensing, and medical imaging techniques. The limitations and challenges of these methods are discussed and future research directions are proposed.

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“…It should be pointed out that the applied force during palpation should be thresholded to a certain limit, as if too large a force is applied to the soft tissue, safety problems may arise. The average maximum force applied by surgeons when manually palpating soft tissue was proved to be around 4.4N from the in vivo experiments in [20]. Furthermore, in [21] it is also mentioned that autonomous robot palpation can reduce the maximum applied force on the soft tissue by more than 35% compared to manual palpation with similar tools.…”

Section: Introductionmentioning

confidence: 96%

Compensating Uncertainties in Force Sensing for Robotic-Assisted Palpation

2019

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Force sensing in robotic-assisted minimally invasive surgery (RMIS) is crucial for performing dedicated surgical procedures, such as bilateral teleoperation and palpation. Due to the bio-compatibility and sterilization requirements, a specially designed surgical tool/shaft is normally attached to the sensor while contacting the organ targets. Through this design, the measured force from the sensor usually contains uncertainties, such as noise, inertial force etc., and thus cannot reflect the actual interaction force with the tissue environment. Motivated to provide the authentic contact force between a robotic tool and soft tissue, we proposed a data-driven force compensation scheme without intricate modeling to reduce the effects of force measurement uncertainties. In this paper, a neural-network-based approach is utilized to automatically model the inertial force subject to noise during the robotic palpation procedure, then the exact contact force can be obtained through the force compensation method which cancels the noise and inertial force. Following this approach, the genuine interaction force during the palpation task can be achieved furthermore to improve the appraisal of the tumor surrounded by the soft tissue. Experiments are conducted with robotic-assisted palpation tasks on a silicone-based soft tissue phantom and the results verify the effectiveness of the suggested method.

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Experimental evaluation of robot-assisted tactile sensing for minimally invasive surgery

Cited by 18 publications

References 20 publications

Human vs. robotic tactile sensing: Detecting lumps in soft tissue

Human vs. robotic tactile sensing: Detecting lumps in soft tissue

Intra-operative tumour localisation in robot-assisted minimally invasive surgery: A review

Compensating Uncertainties in Force Sensing for Robotic-Assisted Palpation

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