34 research outputs found
Implementation of a Surgical Robot Dynamical Simulation and Motion Planning Framework
The daVinci Research Kit (dVRK) is a research platform that consists of the clinical daVinci surgical robot, provided by Intuitive Surgical to Academic Institutions. It provides an open source software and hardware platform for researchers to study and analyze the current architecture and expand the capabilities of the existing technology. The line between general purpose robotics and medical robotics has segregated the two fields. A significant part of the segregation lies at the software end, where new tools and methods developed in general purpose robotics cannot make it to medical robotics in a short amount of time. This research focuses on the integration of a widely used software architecture for general purpose robotics with the dVRK with the hope of utilizing the research and development from one field to the other. As a first step towards this bridging, a motion planning framework and a dynamic simulator has been developed for the dVRK using ROS. The motion planning framework is aimed to assist the surgeon in performing task with additional safety and machine intelligence. A few use cases have been proposed as well. Lastly, a Matlab Interface has been developed that is standalone in terms of usage and provides capabilities to interact with dVRK
An Asynchronous Simulation Framework for Multi-User Interactive Collaboration: Application to Robot-Assisted Surgery
The field of surgery is continually evolving as there is always room for improvement in the post-operative health of the patient as well as the comfort of the Operating Room (OR) team. While the success of surgery is contingent upon the skills of the surgeon and the OR team, the use of specialized robots has shown to improve surgery-related outcomes in some cases. These outcomes are currently measured using a wide variety of metrics that include patient pain and recovery, surgeon’s comfort, duration of the operation and the cost of the procedure. There is a need for additional research to better understand the optimal criteria for benchmarking surgical performance. Presently, surgeons are trained to perform robot-assisted surgeries using interactive simulators. However, in the absence of well-defined performance standards, these simulators focus primarily on the simulation of the operative scene and not the complexities associated with multiple inputs to a real-world surgical procedure. Because interactive simulators are typically designed for specific robots that perform a small number of tasks controlled by a single user, they are inflexible in terms of their portability to different robots and the inclusion of multiple operators (e.g., nurses, medical assistants). Additionally, while most simulators provide high-quality visuals, simplification techniques are often employed to avoid stability issues for physics computation, contact dynamics and multi-manual interaction. This study addresses the limitations of existing simulators by outlining various specifications required to develop techniques that mimic real-world interactions and collaboration. Moreover, this study focuses on the inclusion of distributed control, shared task allocation and assistive feedback -- through machine learning, secondary and tertiary operators -- alongside the primary human operator
Ethyl 3-(3-oxo-3,4-dihydroquinoxalin-2-yl)propanoate
In the title compound, C13H14N2O3, the fused ring system is almost planar (r.m.s. deviation = 0.015 Å). The r.m.s. deviation for all the non-H atoms of the molecule is 0.065Å. In the crystal, N—H⋯O and C—H⋯O hydrogen bonds generate polymeric chains along the b axis containing alternating centrsymmetric R
2
2(8) and R
2
2(20) loops
Fuzzy heuristics and decision tree for classification of statistical feature-based control chart patterns
Monitoring manufacturing process variation remains challenging, especially within a rapid and automated manufacturing environment. Problematic and unstable processes may produce distinct time series patterns that could be associated with assignable causes for diagnosis purpose. Various machine learning classification techniques such as artificial neural network (ANN), classification and regression tree (CART), and fuzzy inference system have been proposed to enhance the capability of traditional Shewhart control chart for process monitoring and diagnosis. ANN classifiers are often opaque to the user with limited interpretability on the classification procedures. However, fuzzy inference system and CART are more transparent, and the internal steps are more comprehensible to users. There have been limited works comparing these two techniques in the control chart pattern recognition (CCPR) domain. As such, the aim of this paper is to demonstrate the development of fuzzy heuristics and CART technique for CCPR and compare their classification performance. The results show the heuristics Mamdani fuzzy classifier performed well in classification accuracy (95.76%) but slightly lower compared to CART classifier (98.58%). This study opens opportunities for deeper investigation and provides a useful revisit to promote more studies into explainable artificial intelligence (XAI)
4-[2-(Benzylsulfanyl)acetyl]-3,4-dihydroquinoxalin-2(1H)-one
In the title compound, C17H16N2O2S, the pyrazinone ring is non-planar (r.m.s. deviation = 0.1595 Å), with maximum deviations for the 4-position N atom and the adjacent non-fused-ring C atom of 0.2557 (15) and −0.2118 (16) Å, respectively. The dihedral angle between the benzyl ring and pyrazinone rings is 30.45 (18)°. Intermolecular N—H⋯O hydrogen-bonding interactions forms inversion dimers which lead to eight-membered R
2
2(8) ring motifs. The dimers are further connected by C—H⋯O interactions
Fully Immersive Virtual Reality for Skull-base Surgery: Surgical Training and Beyond
Purpose: A virtual reality (VR) system, where surgeons can practice
procedures on virtual anatomies, is a scalable and cost-effective alternative
to cadaveric training. The fully digitized virtual surgeries can also be used
to assess the surgeon's skills using measurements that are otherwise hard to
collect in reality. Thus, we present the Fully Immersive Virtual Reality System
(FIVRS) for skull-base surgery, which combines surgical simulation software
with a high-fidelity hardware setup.
Methods: FIVRS allows surgeons to follow normal clinical workflows inside the
VR environment. FIVRS uses advanced rendering designs and drilling algorithms
for realistic bone ablation. A head-mounted display with ergonomics similar to
that of surgical microscopes is used to improve immersiveness. Extensive
multi-modal data is recorded for post-analysis, including eye gaze, motion,
force, and video of the surgery. A user-friendly interface is also designed to
ease the learning curve of using FIVRS.
Results: We present results from a user study involving surgeons with various
levels of expertise. The preliminary data recorded by FIVRS differentiates
between participants with different levels of expertise, promising future
research on automatic skill assessment. Furthermore, informal feedback from the
study participants about the system's intuitiveness and immersiveness was
positive.
Conclusion: We present FIVRS, a fully immersive VR system for skull-base
surgery. FIVRS features a realistic software simulation coupled with modern
hardware for improved realism. The system is completely open-source and
provides feature-rich data in an industry-standard format.Comment: IPCAI/IJCARS 202
A Data-Driven Model with Hysteresis Compensation for I2RIS Robot
Retinal microsurgery is a high-precision surgery performed on an exceedingly
delicate tissue. It now requires extensively trained and highly skilled
surgeons. Given the restricted range of instrument motion in the confined
intraocular space, and also potentially restricting instrument contact with the
sclera, snake-like robots may prove to be a promising technology to provide
surgeons with greater flexibility, dexterity, space access, and positioning
accuracy during retinal procedures requiring high precision and advantageous
tooltip approach angles, such as retinal vein cannulation and epiretinal
membrane peeling. Kinematics modeling of these robots is an essential step
toward accurate position control, however, as opposed to conventional
manipulators, modeling of these robots does not follow a straightforward method
due to their complex mechanical structure and actuation mechanisms. Especially,
in wire-driven snake-like robots, the hysteresis problem due to the wire
tension condition can have a significant impact on the positioning accuracy of
these robots. In this paper, we proposed an experimental kinematics model with
a hysteresis compensation algorithm using the probabilistic Gaussian mixture
models (GMM) Gaussian mixture regression (GMR) approach. Experimental results
on the two-degree-of-freedom (DOF) integrated robotic intraocular snake (I2RIS)
show that the proposed model provides 0.4 deg accuracy, which is an overall 60%
and 70% of improvement for yaw and pitch degrees of freedom, respectively,
compared to a previous model of this robot
Improving Surgical Situational Awareness with Signed Distance Field: A Pilot Study in Virtual Reality
The introduction of image-guided surgical navigation (IGSN) has greatly
benefited technically demanding surgical procedures by providing real-time
support and guidance to the surgeon during surgery. \hi{To develop effective
IGSN, a careful selection of the surgical information and the medium to present
this information to the surgeon is needed. However, this is not a trivial task
due to the broad array of available options.} To address this problem, we have
developed an open-source library that facilitates the development of multimodal
navigation systems in a wide range of surgical procedures relying on medical
imaging data. To provide guidance, our system calculates the minimum distance
between the surgical instrument and the anatomy and then presents this
information to the user through different mechanisms. The real-time performance
of our approach is achieved by calculating Signed Distance Fields at
initialization from segmented anatomical volumes. Using this framework, we
developed a multimodal surgical navigation system to help surgeons navigate
anatomical variability in a skull base surgery simulation environment. Three
different feedback modalities were explored: visual, auditory, and haptic. To
evaluate the proposed system, a pilot user study was conducted in which four
clinicians performed mastoidectomy procedures with and without guidance. Each
condition was assessed using objective performance and subjective workload
metrics. This pilot user study showed improvements in procedural safety without
additional time or workload. These results demonstrate our pipeline's
successful use case in the context of mastoidectomy.Comment: First two authors contributed equally. 6 page