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A Piezoelectric Tactile Sensor for Tissue Stiffness Detection with Arbitrary Contact Angle.
Zhang, Yingxuan; Ju, Feng; Wei, Xiaoyong; Wang, Dan; Wang, Yaoyao.
Afiliação
  • Zhang Y; College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
  • Ju F; College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
  • Wei X; College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
  • Wang D; College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
  • Wang Y; College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Sensors (Basel) ; 20(22)2020 Nov 18.
Article em En | MEDLINE | ID: mdl-33218118
In this paper, a piezoelectric tactile sensor for detecting tissue stiffness in robot-assisted minimally invasive surgery (RMIS) is proposed. It can detect the stiffness not only when the probe is normal to the tissue surface, but also when there is a contact angle between the probe and normal direction. It solves the problem that existing sensors can only detect in the normal direction to ensure accuracy when the degree of freedom (DOF) of surgical instruments is limited. The proposed senor can distinguish samples with different stiffness and recognize lump from normal tissue effectively when the contact angle varies within [0°, 45°]. These are achieved by establishing a new detection model and sensor optimization. It deduces the influence of contact angle on stiffness detection by sensor parameters design and optimization. The detection performance of the sensor is confirmed by simulation and experiment. Five samples with different stiffness (including lump and normal samples with close stiffness) are used. Through blind recognition test in simulation, the recognition rate is 100% when the contact angle is randomly selected within 30°, 94.1% within 45°, which is 38.7% higher than the unoptimized sensor. Through blind classification test and automatic k-means clustering in experiment, the correct rate is 92% when the contact angle is randomly selected within 45°. We can get the proposed sensor can easily recognize samples with different stiffness with high accuracy which has broad application prospects in the medical field.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Instrumentos Cirúrgicos / Tato / Procedimentos Cirúrgicos Robóticos Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Instrumentos Cirúrgicos / Tato / Procedimentos Cirúrgicos Robóticos Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article