A miniature piezoelectric spiral tactile sensor for tissue hardness palpation with catheter robot in minimally invasive surgery

2019 ◽  
Vol 28 (2) ◽  
pp. 025033 ◽  
Author(s):  
Feng Ju ◽  
Yaming Wang ◽  
Zhao Zhang ◽  
Yaoyao Wang ◽  
Yahui Yun ◽  
...  
Author(s):  
Yahui Yun ◽  
Yaming Wang ◽  
Hao Guo ◽  
Yaoyao Wang ◽  
Hongtao Wu ◽  
...  

A miniature resonant tactile sensor for tissue stiffness detection in robot-assisted minimally invasive surgery is proposed in this article. The proposed tactile sensor can detect tissue stiffness based on the principle of the resonant frequency shift when it contacts with tissue of different stiffness. A PZT (lead zirconate titanate) bimorph works simultaneously as the actuator and the sensing element, which is helpful for simplifying the structure. The resonant frequency shift can be deduced by measuring the electrical impedance of the PZT bimorph, since there will be an abrupt change of the impedance when resonance occurs. A unique structure of an Archimedean spiral metal sheet is introduced to restrict the outer size of the sensor within 10 mm and to keep the resonant frequency low. A theoretical model is established. Finite element method analyses are carried out to validate the working principle and it meets the theoretical model quite well. Several silicone samples are tested with the sensor and the results show that the proposed sensor is capable of measuring tissue stiffness within the range of 0–2 MPa, detecting and locating lumps inside tissue.


Author(s):  
Wei-Yu Tseng ◽  
Jefferey S. Fisher ◽  
Javier L. Prieto ◽  
Kentaro Rinaldi ◽  
Abraham P. Lee

Tactile sensors are the interfaces to detect the physical properties of objects and have extensive applications in robotic sensing, biomechanics, minimally invasive surgery and human prosthetics [1]. For human prosthetics applications, the current prosthetic hand can offer only the manipulation function. With the sensing being part of the prosthetic hand, the user can get feedback from the prosthetic. This feeling can help users decrease their dependency on visual information and have better body control on weight balancing and signal limb stance.


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