Ahmad Abiri1,2, Yen-Yi Juo3, Anna Tao4, Syed J Askari4, Jake Pensa4, James W Bisley4,5, Erik P Dutson4,3, Warren S Grundfest4,6. 1. Center for Advanced Surgical and Interventional Technology (CASIT), UCLA, Los Angeles, CA, USA. aabiri@ucla.edu. 2. Henry Samueli School of Engineering and Applied Science, UCLA, Los Angeles, CA, USA. aabiri@ucla.edu. 3. Department of Surgery, UCLA, Los Angeles, CA, USA. 4. Center for Advanced Surgical and Interventional Technology (CASIT), UCLA, Los Angeles, CA, USA. 5. Brain Research Institute, UCLA, Los Angeles, CA, USA. 6. Henry Samueli School of Engineering and Applied Science, UCLA, Los Angeles, CA, USA.
Abstract
BACKGROUND: The loss of tactile feedback in minimally invasive robotic surgery remains a major challenge to the expanding field. With visual cue compensation alone, tissue characterization via palpation proves to be immensely difficult. This work evaluates a bimodal vibrotactile system as a means of conveying applied forces to simulate haptic feedback in two sets of studies simulating an artificial palpation task using the da Vinci surgical robot. METHODS: Subjects in the first study were tasked with localizing an embedded vessel in a soft tissue phantom using a single-sensor unit. In the second study, subjects localized tumor-like structures using a three-sensor array. In both sets of studies, subjects completed the task under three trial conditions: no feedback, normal force tactile feedback, and hybrid vibrotactile feedback. Recordings of correct localization, incorrect localization, and time-to-completion were used to evaluate performance outcomes. RESULTS: With the addition of vibrotactile and pneumatic feedback, significant improvements in the percentage of correct localization attempts were detected (p = 0.0001 and p = 0.0459, respectively) during the first experiment with phantom vessels. Similarly, significant improvements in correct localization were found with the addition of vibrotactile (p = 2.57E-5) and pneumatic significance (p = 8.54E-5) were observed in the second experiment involving tumor phantoms. CONCLUSIONS: This work demonstrates not only the superior benefits of a multi-modal feedback over traditional single-modality feedback, but also the effectiveness of vibration in providing haptic feedback to artificial palpation systems.
BACKGROUND: The loss of tactile feedback in minimally invasive robotic surgery remains a major challenge to the expanding field. With visual cue compensation alone, tissue characterization via palpation proves to be immensely difficult. This work evaluates a bimodal vibrotactile system as a means of conveying applied forces to simulate haptic feedback in two sets of studies simulating an artificial palpation task using the da Vinci surgical robot. METHODS: Subjects in the first study were tasked with localizing an embedded vessel in a soft tissue phantom using a single-sensor unit. In the second study, subjects localized tumor-like structures using a three-sensor array. In both sets of studies, subjects completed the task under three trial conditions: no feedback, normal force tactile feedback, and hybrid vibrotactile feedback. Recordings of correct localization, incorrect localization, and time-to-completion were used to evaluate performance outcomes. RESULTS: With the addition of vibrotactile and pneumatic feedback, significant improvements in the percentage of correct localization attempts were detected (p = 0.0001 and p = 0.0459, respectively) during the first experiment with phantom vessels. Similarly, significant improvements in correct localization were found with the addition of vibrotactile (p = 2.57E-5) and pneumatic significance (p = 8.54E-5) were observed in the second experiment involving tumor phantoms. CONCLUSIONS: This work demonstrates not only the superior benefits of a multi-modal feedback over traditional single-modality feedback, but also the effectiveness of vibration in providing haptic feedback to artificial palpation systems.
Authors: Chih-Hung King; Adrienne T Higa; Martin O Culjat; Soo Hwa Han; James W Bisley; Gregory P Carman; Erik Dutson; Warren S Grundfest Journal: Stud Health Technol Inform Date: 2007
Authors: Qiangqiang Ouyang; Juan Wu; Songping Sun; Jake Pensa; Ahmad Abiri; Erik Dutson; James Bisley Journal: IEEE Trans Biomed Eng Date: 2021-09-20 Impact factor: 4.756