Pub Date : 2024-09-23DOI: 10.1109/TMRB.2024.3464127
Christian Marzi;Maximilian Themistocli;Björn Hein;Franziska Mathis-Ullrich
Minimally invasive continuum robots face limitations in accessing environmental and spatial information on the situs. However, such information would often be necessary for control and automation features in surgical use. Centering an endoscopic system within a hollow organ can be such a feature, providing the benefit of reduced risk of injury and assistance for navigation. To leverage such an application, this work investigates a proximity servoed continuum robot. A sensorized tip combines capacitive electrodes, a camera, and illumination and uses capacitive proximity sensing to determine the enclosing environment’s center point. A controller is presented that uses this information to center the robot’s tip. The system is evaluated in a dynamic phantom, where an average accuracy of 10.0 mm could be demonstrated and contact to the phantom’s wall was avoided during 98% of the experiment time. In a second phantom experiment, it is demonstrated how this controller can be applied to follow the center line of a bent anatomical structure. Future work should focus on improving accuracy and versatility of the system, aiming for application in more challenging and irregular environments, such as ex vivo or in vivo organs.
{"title":"Proximity Servoed Minimally Invasive Continuum Robot for Endoscopic Interventions","authors":"Christian Marzi;Maximilian Themistocli;Björn Hein;Franziska Mathis-Ullrich","doi":"10.1109/TMRB.2024.3464127","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3464127","url":null,"abstract":"Minimally invasive continuum robots face limitations in accessing environmental and spatial information on the situs. However, such information would often be necessary for control and automation features in surgical use. Centering an endoscopic system within a hollow organ can be such a feature, providing the benefit of reduced risk of injury and assistance for navigation. To leverage such an application, this work investigates a proximity servoed continuum robot. A sensorized tip combines capacitive electrodes, a camera, and illumination and uses capacitive proximity sensing to determine the enclosing environment’s center point. A controller is presented that uses this information to center the robot’s tip. The system is evaluated in a dynamic phantom, where an average accuracy of 10.0 mm could be demonstrated and contact to the phantom’s wall was avoided during 98% of the experiment time. In a second phantom experiment, it is demonstrated how this controller can be applied to follow the center line of a bent anatomical structure. Future work should focus on improving accuracy and versatility of the system, aiming for application in more challenging and irregular environments, such as ex vivo or in vivo organs.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1738-1747"},"PeriodicalIF":3.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-23DOI: 10.1109/TMRB.2024.3464748
Lei Yang;Chenxu Zhai;Hongyong Wang;Yanhong Liu;Guibin Bian
Surgical robots have become integral to contemporary surgical procedures, with the precise segmentation of surgical instruments constituting a crucial prerequisite for ensuring their stable functionality. However, numerous factors continue to influence segmentation outcomes, including intricate surgical environments, varying viewpoints, diminished contrast between surgical instruments and surroundings, divergent sizes and shapes of instruments, and imbalanced categories. In this paper, a novel dual-branch fusion network, designated DBF-Net, is presented, which integrates both convolutional neural network (CNN) and Transformer architectures to facilitate automatic segmentation of surgical instruments. For addressing the deficiencies in feature extraction capacity in CNNs or Transformer architectures, a dual-path encoding unit is introduced to proficiently represent local detail features and global context. Meanwhile, to enhance the fusion of features extracted from the dual paths, a CNN-Transformer fusion (CTF) module is proposed, to efficiently merge features from the CNN and Transformer structures, contributing to the effective representation of both local detail features and global contextual features. Further refinement is pursued through an multi-scale feature aggregation (MFAG) module and a local feature enhancement (LFE) module, to refine local contextual features at each layer. In addition, an attention-guided enhancement (AGE) module is incorporated for feature refinement of local feature maps. Finally, an multi-scale global feature representation (MGFR) module is introduced, facilitating the extraction and aggregation of multi-scale features, and a progressive fusion module (PFM) culminates in the aggregation of full-scale features from the decoder. Experimental results underscore the superior segmentation performance of proposed network compared to other state-of-the-art (SOTA) segmentation models for surgical instruments, which have well validated the efficacy of proposed network architecture in advancing the field of surgical instrument segmentation.
{"title":"A Dual-Branch Fusion Network for Surgical Instrument Segmentation","authors":"Lei Yang;Chenxu Zhai;Hongyong Wang;Yanhong Liu;Guibin Bian","doi":"10.1109/TMRB.2024.3464748","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3464748","url":null,"abstract":"Surgical robots have become integral to contemporary surgical procedures, with the precise segmentation of surgical instruments constituting a crucial prerequisite for ensuring their stable functionality. However, numerous factors continue to influence segmentation outcomes, including intricate surgical environments, varying viewpoints, diminished contrast between surgical instruments and surroundings, divergent sizes and shapes of instruments, and imbalanced categories. In this paper, a novel dual-branch fusion network, designated DBF-Net, is presented, which integrates both convolutional neural network (CNN) and Transformer architectures to facilitate automatic segmentation of surgical instruments. For addressing the deficiencies in feature extraction capacity in CNNs or Transformer architectures, a dual-path encoding unit is introduced to proficiently represent local detail features and global context. Meanwhile, to enhance the fusion of features extracted from the dual paths, a CNN-Transformer fusion (CTF) module is proposed, to efficiently merge features from the CNN and Transformer structures, contributing to the effective representation of both local detail features and global contextual features. Further refinement is pursued through an multi-scale feature aggregation (MFAG) module and a local feature enhancement (LFE) module, to refine local contextual features at each layer. In addition, an attention-guided enhancement (AGE) module is incorporated for feature refinement of local feature maps. Finally, an multi-scale global feature representation (MGFR) module is introduced, facilitating the extraction and aggregation of multi-scale features, and a progressive fusion module (PFM) culminates in the aggregation of full-scale features from the decoder. Experimental results underscore the superior segmentation performance of proposed network compared to other state-of-the-art (SOTA) segmentation models for surgical instruments, which have well validated the efficacy of proposed network architecture in advancing the field of surgical instrument segmentation.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1542-1554"},"PeriodicalIF":3.4,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this work, we propose a framework enabling upper-limb rehabilitation exoskeletons to mimic the personalised haptic guidance of therapists. Current exoskeletons face acceptability issues as they limit physical interaction between clinicians and patients and offer only predefined levels of support that cannot be tuned during the movements, when needed. To increase acceptance, we first developed a method to estimate the therapist’s force contribution while manipulating a patient’s arm using an upper-limb exoskeleton. We achieved a precision of $0.31Nm$ without using direct sensors. Then, we exploited the Learning-by-demonstration paradigm to learn from the therapist’s interactions. Single-joint experiments on ANYexo demonstrate that our framework, applying the Vector-search approach, can record the joint-level therapist’s interaction forces during simple tasks, link them to the kinematics of the robot, and then provide support to the user’s limb. The support is coherent with what is learnt and changes with the real-time arm kinematic configuration of the robot, assisting whatever movement the patient executes in the end-effector space without the need for manual regulation. In this way, robotic therapy sessions can exploit therapists’ expertise while reducing their manual workload.
{"title":"Therapists’ Force-Profile Teach-and-Mimic Approach for Upper-Limb Rehabilitation Exoskeletons","authors":"Beatrice Luciani;Michael Sommerhalder;Marta Gandolla;Peter Wolf;Francesco Braghin;Robert Riener","doi":"10.1109/TMRB.2024.3464697","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3464697","url":null,"abstract":"In this work, we propose a framework enabling upper-limb rehabilitation exoskeletons to mimic the personalised haptic guidance of therapists. Current exoskeletons face acceptability issues as they limit physical interaction between clinicians and patients and offer only predefined levels of support that cannot be tuned during the movements, when needed. To increase acceptance, we first developed a method to estimate the therapist’s force contribution while manipulating a patient’s arm using an upper-limb exoskeleton. We achieved a precision of \u0000<inline-formula> <tex-math>$0.31Nm$ </tex-math></inline-formula>\u0000 without using direct sensors. Then, we exploited the Learning-by-demonstration paradigm to learn from the therapist’s interactions. Single-joint experiments on ANYexo demonstrate that our framework, applying the Vector-search approach, can record the joint-level therapist’s interaction forces during simple tasks, link them to the kinematics of the robot, and then provide support to the user’s limb. The support is coherent with what is learnt and changes with the real-time arm kinematic configuration of the robot, assisting whatever movement the patient executes in the end-effector space without the need for manual regulation. In this way, robotic therapy sessions can exploit therapists’ expertise while reducing their manual workload.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1658-1665"},"PeriodicalIF":3.4,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10684729","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the increasing adoption of robotic surgery systems, the need for automated surgical tasks has become more pressing. Recent learning-based approaches provide solutions to surgical automation but typically rely on low-dimensional observations. To further imitate the actions of surgeons in an end-to-end paradigm, this paper introduces a novel visual-based approach to automating surgical tasks using generative imitation learning for robotic systems. We develop a hybrid model integrating state space models transformer, and conditional variational autoencoders (CVAE) to enhance performance and generalization called ACMT. The proposed model, leveraging the Mamba block and multi-head cross-attention mechanisms for sequential modeling, achieves a 75-100% success rate with just 100 demonstrations for most of the tasks. This work significantly advances data-driven automation in surgical robotics, aiming to alleviate the burden on surgeons and improve surgical outcomes.
{"title":"Visuomotor Policy Learning for Task Automation of Surgical Robot","authors":"Junhui Huang;Qingxin Shi;Dongsheng Xie;Yiming Ma;Xiaoming Liu;Changsheng Li;Xingguang Duan","doi":"10.1109/TMRB.2024.3464090","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3464090","url":null,"abstract":"With the increasing adoption of robotic surgery systems, the need for automated surgical tasks has become more pressing. Recent learning-based approaches provide solutions to surgical automation but typically rely on low-dimensional observations. To further imitate the actions of surgeons in an end-to-end paradigm, this paper introduces a novel visual-based approach to automating surgical tasks using generative imitation learning for robotic systems. We develop a hybrid model integrating state space models transformer, and conditional variational autoencoders (CVAE) to enhance performance and generalization called ACMT. The proposed model, leveraging the Mamba block and multi-head cross-attention mechanisms for sequential modeling, achieves a 75-100% success rate with just 100 demonstrations for most of the tasks. This work significantly advances data-driven automation in surgical robotics, aiming to alleviate the burden on surgeons and improve surgical outcomes.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1448-1457"},"PeriodicalIF":3.4,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-20DOI: 10.1109/TMRB.2024.3464728
Kaan Esendag;Mark E. McAlindon;Daniela Rus;Shuhei Miyashita;Dana D. Damian
Robotic capsules provide an alternative route of entry to the gastrointestinal tract with minimal discomfort to patients. As capabilities of milli to micro robots progress, the potential of using robotic capsules not just for inspection, but for surgical procedures increase. To aid operations in the intestine, the capsule could be used to expand the site of surgery and anchoring to the intestinal walls to keep itself in place. This paper presents an untethered robotic capsule that can provide volumetric expansion using a chemical reaction without on-board electronic components. The expansion is based on the reaction between chemicals that are safe for ingestion, operated with magnetic fields and temperatures that are within safe limits. The capsule was able to expand greater than the diameter of the small intestine for 44 minutes and provided 0.27N of anchoring force. A theoretical model of the reaction process was built and simulated to predict the behavior of the capsule expansion and validated through the experiments. The design and the simulation presented in this paper can be used for fabricating capsules to specific clinical needs. The work also opens up the possibility of untethered technologies that are remotely and chemically programmed for in-vivo surgical applications.
{"title":"A Chemical Reaction-Driven Untethered Volume Changing Robotic Capsule for Tissue Dilation","authors":"Kaan Esendag;Mark E. McAlindon;Daniela Rus;Shuhei Miyashita;Dana D. Damian","doi":"10.1109/TMRB.2024.3464728","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3464728","url":null,"abstract":"Robotic capsules provide an alternative route of entry to the gastrointestinal tract with minimal discomfort to patients. As capabilities of milli to micro robots progress, the potential of using robotic capsules not just for inspection, but for surgical procedures increase. To aid operations in the intestine, the capsule could be used to expand the site of surgery and anchoring to the intestinal walls to keep itself in place. This paper presents an untethered robotic capsule that can provide volumetric expansion using a chemical reaction without on-board electronic components. The expansion is based on the reaction between chemicals that are safe for ingestion, operated with magnetic fields and temperatures that are within safe limits. The capsule was able to expand greater than the diameter of the small intestine for 44 minutes and provided 0.27N of anchoring force. A theoretical model of the reaction process was built and simulated to predict the behavior of the capsule expansion and validated through the experiments. The design and the simulation presented in this paper can be used for fabricating capsules to specific clinical needs. The work also opens up the possibility of untethered technologies that are remotely and chemically programmed for in-vivo surgical applications.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1300-1308"},"PeriodicalIF":3.4,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-20DOI: 10.1109/TMRB.2024.3464739
Elise Fu;Haoyin Zhou;Ángela Alarcón de la Lastra;Ruisi Zhang;Haripriya Ayyala;Justin Broyles;Bohdan Pomahac;Jayender Jagadeesan
Mastectomy is often coupled with breast reconstruction surgery (BRS) to reconstruct the breast mound. However, BRS is challenging and subject to the judgement of the surgeon in determining the amount of tissue to be harvested and the shape of reconstructed breast. To date, the existing tools aimed at maintaining symmetry and appearance of the reconstructed breast are costly. In this paper, we have developed an intuitive breast reconstruction system comprising a software application integrated with the simultaneous localization and mapping (SLAM) algorithm, and a low-cost RGB-D camera. Our SLAM-based breast reconstruction system will be used to scan and reconstruct the patient’s breast using our customized mesh-generating method prior to mastectomy. Using this reconstructed model, a patient-specific 3D printed mold is created to help shape the harvested tissue that is inserted into the mastectomy site during BRS. Validation experiments show that the mean repeatability and accuracy errors for the surface reconstruction are less than 1.5 mm. The software application has been tested on 20 patients under an IRB-approved protocol including intraoperative guidance for 4 patients. The results show the consistent and accurate reconstruction of the breasts including the inframammary fold for different breast shapes and skin tones.
{"title":"SLAM-Based Breast Reconstruction System for Surgical Guidance Using a Low-Cost Camera","authors":"Elise Fu;Haoyin Zhou;Ángela Alarcón de la Lastra;Ruisi Zhang;Haripriya Ayyala;Justin Broyles;Bohdan Pomahac;Jayender Jagadeesan","doi":"10.1109/TMRB.2024.3464739","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3464739","url":null,"abstract":"Mastectomy is often coupled with breast reconstruction surgery (BRS) to reconstruct the breast mound. However, BRS is challenging and subject to the judgement of the surgeon in determining the amount of tissue to be harvested and the shape of reconstructed breast. To date, the existing tools aimed at maintaining symmetry and appearance of the reconstructed breast are costly. In this paper, we have developed an intuitive breast reconstruction system comprising a software application integrated with the simultaneous localization and mapping (SLAM) algorithm, and a low-cost RGB-D camera. Our SLAM-based breast reconstruction system will be used to scan and reconstruct the patient’s breast using our customized mesh-generating method prior to mastectomy. Using this reconstructed model, a patient-specific 3D printed mold is created to help shape the harvested tissue that is inserted into the mastectomy site during BRS. Validation experiments show that the mean repeatability and accuracy errors for the surface reconstruction are less than 1.5 mm. The software application has been tested on 20 patients under an IRB-approved protocol including intraoperative guidance for 4 patients. The results show the consistent and accurate reconstruction of the breasts including the inframammary fold for different breast shapes and skin tones.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1345-1353"},"PeriodicalIF":3.4,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Different methods have been proposed to evaluate surgical skills from observer-based scoring to recent data-driven approaches. However, most of these methods assess the surgical performance considering the procedure as a whole, avoiding detailed performance insights. In this study, we focused on the most challenging phases of robotic-assisted hysterectomies to compare the performance of expert and intermediate surgeons using the surgical process model methodology. We recorded surgical video and kinematic data of fifty-two robotic-assisted laparoscopic hysterectomies performed by five experts and three intermediate surgeons. We annotated the video in eight phases. We computed twenty-five automated performance metrics (APMs); seven for each of the right, left, and endoscope robotic arms, and four global ones. For the global analysis, only four APMs differed significantly between experts and intermediates. However, interpreting these APMs was difficult. For local analysis, we observed that 23 APMs were significantly different for at least one phase. We found that the two most challenging phases had APMs that highlighted difficulty due to the presence of the uterus, lack of confidence in anatomical knowledge, and difficulty in moving the endoscope. Such results of the local analysis allow us to propose appropriate training for surgeons.
{"title":"Global Versus Local Kinematic Skills Assessment on Robotic-Assisted Hysterectomies","authors":"Arnaud Huaulmé;Krystel Nyangoh Timoh;Victor Jan;Sonia Guerin;Pierre Jannin","doi":"10.1109/TMRB.2024.3464669","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3464669","url":null,"abstract":"Different methods have been proposed to evaluate surgical skills from observer-based scoring to recent data-driven approaches. However, most of these methods assess the surgical performance considering the procedure as a whole, avoiding detailed performance insights. In this study, we focused on the most challenging phases of robotic-assisted hysterectomies to compare the performance of expert and intermediate surgeons using the surgical process model methodology. We recorded surgical video and kinematic data of fifty-two robotic-assisted laparoscopic hysterectomies performed by five experts and three intermediate surgeons. We annotated the video in eight phases. We computed twenty-five automated performance metrics (APMs); seven for each of the right, left, and endoscope robotic arms, and four global ones. For the global analysis, only four APMs differed significantly between experts and intermediates. However, interpreting these APMs was difficult. For local analysis, we observed that 23 APMs were significantly different for at least one phase. We found that the two most challenging phases had APMs that highlighted difficulty due to the presence of the uterus, lack of confidence in anatomical knowledge, and difficulty in moving the endoscope. Such results of the local analysis allow us to propose appropriate training for surgeons.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1382-1385"},"PeriodicalIF":3.4,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-20DOI: 10.1109/TMRB.2024.3464668
Simon Frieler;Sarthak Misra;Venkatasubramanian Kalpathy Venkiteswaran
Robotic manipulators are used across various surgical tasks, including endoscopic and laparoscopic procedures. Operating in small and constrained spaces during these procedures requires the manipulators to have high dexterity and control over the motion path but with a small footprint. In this work, we propose a modular design of a magnetically-guided small-sized robotic manipulator. The manipulator has discrete universal joints that allow ease of actuation. Variable stiffness is incorporated into the joints to allow the locking and unlocking of individual degrees of freedom (DOFs). The design is modular and allows extension to additional DOFs. The range of each DOF is 60° and is controlled by a pair of shape memory polymer flexures; four flexures comprise one joint. With rolling-contact elements, the design eliminates problems with buckling and pushability. A custom-designed heating element triggers the flexures to switch from a high (0.57Nmm/°) to a low stiffness (0.06Nmm/°) state within 14(±0.8)s. Ambient cooling secures shape-locking within 64(±3.7)s. In an experiment, a 6-DOF version of the manipulator navigates around obstacles in confined spaces and remains shape-locked for stable operation. Practical application is demonstrated through simulated gastroscopy and polypectomy using inserted surgical tools.
{"title":"Selectively Tunable Joints With Variable Stiffness for a Magnetically-Steerable 6-DOF Manipulator","authors":"Simon Frieler;Sarthak Misra;Venkatasubramanian Kalpathy Venkiteswaran","doi":"10.1109/TMRB.2024.3464668","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3464668","url":null,"abstract":"Robotic manipulators are used across various surgical tasks, including endoscopic and laparoscopic procedures. Operating in small and constrained spaces during these procedures requires the manipulators to have high dexterity and control over the motion path but with a small footprint. In this work, we propose a modular design of a magnetically-guided small-sized robotic manipulator. The manipulator has discrete universal joints that allow ease of actuation. Variable stiffness is incorporated into the joints to allow the locking and unlocking of individual degrees of freedom (DOFs). The design is modular and allows extension to additional DOFs. The range of each DOF is 60° and is controlled by a pair of shape memory polymer flexures; four flexures comprise one joint. With rolling-contact elements, the design eliminates problems with buckling and pushability. A custom-designed heating element triggers the flexures to switch from a high (0.57Nmm/°) to a low stiffness (0.06Nmm/°) state within 14(±0.8)s. Ambient cooling secures shape-locking within 64(±3.7)s. In an experiment, a 6-DOF version of the manipulator navigates around obstacles in confined spaces and remains shape-locked for stable operation. Practical application is demonstrated through simulated gastroscopy and polypectomy using inserted surgical tools.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1713-1725"},"PeriodicalIF":3.4,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-20DOI: 10.1109/TMRB.2024.3464676
Jialei Shi;Ge Shi;Yu Wu;Helge A. Wurdemann
Medical instruments made of compliant materials provide increased safety and dexterity when interacting with anatomical environments. Beyond the development of hardware, the maneuverability of these medical instruments presents significant challenges, especially in practical applications like minimally invasive surgery. Consequently, developing efficient and intuitive interfaces for operating these soft instruments is crucial. This study focuses on creating a flexible, soft robotic handheld laparoscopy device featuring a multi-cavity touch interface. The pneumatically driven soft robotic device has a continuum structure and an outermost diameter of 11.5 mm. The laparoscopy device is equipped with a silicone-cast touch interface that includes five air-filled cavities. Monitoring the pressure within these cavities facilitates the identification of user inputs, offering an intuitive and cost-effective way to operate the device. To evaluate the laparoscopy device’s performance, in vitro tests were conducted using a test rig and a phantom environment. The device’s usability was assessed by participants, providing valuable insights into its functionality and practicality in a controlled setting. These evaluations lay the groundwork for future advancements in soft robotic medical instruments for minimally invasive procedures.
{"title":"A Multi-Cavity Touch Interface for a Flexible Soft Laparoscopy Device: Design and Evaluation","authors":"Jialei Shi;Ge Shi;Yu Wu;Helge A. Wurdemann","doi":"10.1109/TMRB.2024.3464676","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3464676","url":null,"abstract":"Medical instruments made of compliant materials provide increased safety and dexterity when interacting with anatomical environments. Beyond the development of hardware, the maneuverability of these medical instruments presents significant challenges, especially in practical applications like minimally invasive surgery. Consequently, developing efficient and intuitive interfaces for operating these soft instruments is crucial. This study focuses on creating a flexible, soft robotic handheld laparoscopy device featuring a multi-cavity touch interface. The pneumatically driven soft robotic device has a continuum structure and an outermost diameter of 11.5 mm. The laparoscopy device is equipped with a silicone-cast touch interface that includes five air-filled cavities. Monitoring the pressure within these cavities facilitates the identification of user inputs, offering an intuitive and cost-effective way to operate the device. To evaluate the laparoscopy device’s performance, in vitro tests were conducted using a test rig and a phantom environment. The device’s usability was assessed by participants, providing valuable insights into its functionality and practicality in a controlled setting. These evaluations lay the groundwork for future advancements in soft robotic medical instruments for minimally invasive procedures.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1309-1321"},"PeriodicalIF":3.4,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-20DOI: 10.1109/TMRB.2024.3464672
Mostafa A. Atalla;Jeroen J. Tuijp;Michaël Wiertlewski;Aimée Sakes
Minimally invasive endovascular procedures use catheters that are guided through blood vessels to perform interventions, resulting in an inevitable frictional interaction between the catheter and the vessel walls. While this friction enhances stability during the intervention, it poses a risk of damaging the inner layer of the blood vessel wall during navigation, leading to post-operative complications including infectious diseases and thrombus formation. To mitigate the risk of adverse complications, we propose a new concept of a variable-friction catheter capable of transitioning from low friction during navigation to high friction for increased stability while performing the intervention. This variable-friction catheter leverages ultrasonic lubrication to actively control the frictional forces experienced by the catheter during the procedure. In this paper, we demonstrate a proof-of-concept for a friction control module, a pivotal component of the proposed catheter design. Our experiments demonstrate that the prototype effectively reduce friction by up to 11% and 60%, on average, on soft and rigid surfaces, representing its potential performance on healthy and calcified tissue, respectively. This result underscores the feasibility of the design and its potential to improve the safety and efficacy of minimally invasive endovascular procedures.
{"title":"Toward Variable-Friction Catheters Using Ultrasonic Lubrication","authors":"Mostafa A. Atalla;Jeroen J. Tuijp;Michaël Wiertlewski;Aimée Sakes","doi":"10.1109/TMRB.2024.3464672","DOIUrl":"https://doi.org/10.1109/TMRB.2024.3464672","url":null,"abstract":"Minimally invasive endovascular procedures use catheters that are guided through blood vessels to perform interventions, resulting in an inevitable frictional interaction between the catheter and the vessel walls. While this friction enhances stability during the intervention, it poses a risk of damaging the inner layer of the blood vessel wall during navigation, leading to post-operative complications including infectious diseases and thrombus formation. To mitigate the risk of adverse complications, we propose a new concept of a variable-friction catheter capable of transitioning from low friction during navigation to high friction for increased stability while performing the intervention. This variable-friction catheter leverages ultrasonic lubrication to actively control the frictional forces experienced by the catheter during the procedure. In this paper, we demonstrate a proof-of-concept for a friction control module, a pivotal component of the proposed catheter design. Our experiments demonstrate that the prototype effectively reduce friction by up to 11% and 60%, on average, on soft and rigid surfaces, representing its potential performance on healthy and calcified tissue, respectively. This result underscores the feasibility of the design and its potential to improve the safety and efficacy of minimally invasive endovascular procedures.","PeriodicalId":73318,"journal":{"name":"IEEE transactions on medical robotics and bionics","volume":"6 4","pages":"1375-1381"},"PeriodicalIF":3.4,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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