Tactile sensor using acoustic reflection for lump detection in laparoscopic surgery

Tanaka, Yoshihiro; Fukuda, Tomohiro; Fujiwara, Michitaka; Sano, Akihito

doi:10.1007/s11548-014-1067-z

Cited by 27 publications

(14 citation statements)

References 19 publications

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“…We have developed a forceps‐type tactile sensor for laparoscopic tumor detection . The sensor has more surgically applicable properties such as having suitable dimensions, electrical safety for body tissue, simple structure, low cost and adaptability to sterilization.…”

Section: Introductionmentioning

confidence: 99%

Visual and tactile feedback for a direct‐manipulating tactile sensor in laparoscopic palpation

Fukuda

Tanaka

Kappers

et al. 2017

Robotics Computer Surgery

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Section: Introductionmentioning

confidence: 99%

Visual and tactile feedback for a direct‐manipulating tactile sensor in laparoscopic palpation

Fukuda

Tanaka

Kappers

et al. 2017

Robotics Computer Surgery

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“…The participants manipulated a long, thin tactile sensor that was previously developed (Tanaka et al, 2015). The sensor only detected a single force applied on the side of the sensor tip.…”

Section: Data Preparationmentioning

confidence: 99%

“…A major advantage of temporal information-based palpation systems is that they can be simple, as they use of a single sensing element. For our system, we developed a forcepstype tactile sensor using an acoustic sensing principle (Tanaka et al, 2015). This sensor has important advantages for surgical applications: there are no electrical elements within the portion inserted into the patient's body, it can be sterilized, and it is disposable.…”

mentioning

confidence: 99%

DNN-Based Assistant in Laparoscopic Computer-Aided Palpation

et al. 2018

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Tactile sensory input of surgeons is severely limited in minimally invasive surgery, therefore manual palpation cannot be performed for intraoperative tumor detection. Computer-aided palpation, in which tactile information is acquired by devices and relayed to the surgeon, is one solution for overcoming this limitation. An important design factor is the method by which the acquired information is fed back to the surgeon. However, currently there is no systematic method for achieving this aim, and it is possible that a badly implemented feedback mechanism could adversely affect the performance of the surgeon. In this study, we propose an assistance algorithm for intraoperative tumor detection in laparoscopic surgery. Our scenario is that the surgeon manipulates a sensor probe, makes a decision based on the feedback provided from the sensor, while simultaneously, the algorithm analyzes the time series of the sensor output. Thus, the algorithm assists the surgeon in making decisions by providing independent detection results. A deep neural network model with three hidden layers was used to analyze the sensor output. We propose methods to input the time series of the sensor output to the model for real-time analysis, and to determine the criterion for detection by the model. This study aims to validate the feasibility of the algorithm by using data acquired in our previous psychophysical experiment. There, novice participants were asked to detect a phantom of an early-stage gastric tumor through visual feedback from the tactile sensor. In addition to the analysis of the accuracy, signal detection theory was employed to assess the potential detection performance of the model. The detection performance was compared with that of human participants. We conducted two types of validation, and found that the detection performance of the model was not significantly different from that of the human participants if the data from a known user was included in the model construction. The result supports the feasibility of the proposed algorithm for detection assistance in computer-aided palpation.

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“…A tactile sensor that employs acoustic reflection was assembled for the forceps having a tactile sensing function in the above-mentioned system [35]. Figure 15.10 presents the overview and geometry of the sensor, the sensor output characteristic, and an example of the sensor output for a tumor phantom.…”

Section: Sensor System With Sensory Feedbackmentioning

confidence: 99%

Simple Tactile Technologies Utilizing Human Tactile and Haptic Characteristics

Tanaka¹,

Sano²

2016

Pervasive Haptics

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Human tactile and haptic characteristics promote the development of tactile devices that are simple and effective. In addition, issues and ideas for tactile devices can be found from present needs and conditions of manufacturing and medical fields. This chapter presents tactile technologies that are based on human tactile and haptic characteristics. First, wearable and hand-held tactile sensors, tactile enhancing devices without an electronic element, and tactile sensing with a human finger are introduced. They were developed for surface irregularity inspections and texture evaluations. Then, a palpation system with sensory feedback for laparoscopic surgery is introduced. Finally, tactile design based on tactile illusion is introduced. It can combine a hard material and soft feel. These tactile technologies utilize the human haptic ability and structural enhancing mechanism, and human tactile perception.

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Tactile sensor using acoustic reflection for lump detection in laparoscopic surgery

Abstract: The theoretical and experimental results show that the sensor is sensitive to the deformation due to contact with an object and has the potential to detect a lump in laparoscopic surgery.

Cited by 27 publications

References 19 publications

Visual and tactile feedback for a direct‐manipulating tactile sensor in laparoscopic palpation

Visual and tactile feedback for a direct‐manipulating tactile sensor in laparoscopic palpation

DNN-Based Assistant in Laparoscopic Computer-Aided Palpation

Simple Tactile Technologies Utilizing Human Tactile and Haptic Characteristics

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