Bioengineering, augmented reality, and robotic surgery in vascular surgery: A literature review

Biomedical engineering integrates a variety of applied sciences with life sciences to improve human health and reduce the invasiveness of surgical procedures. Technological advances, achieved through biomedical engineering, have contributed to significant improvements in the field of vascular and endovascular surgery. This paper aims to review the most cutting-edge technologies of the last decade involving the use of augmented reality devices and robotic systems in vascular surgery, highlighting benefits and limitations. Accordingly, two distinct literature surveys were conducted through the PubMed database: the first review provides a comprehensive assessment of augmented reality technologies, including the different techniques available for the visualization of virtual content (11 papers revised); the second review collects studies with bioengineering content that highlight the research trend in robotic vascular surgery, excluding works focused only on the clinical use of commercially available robotic systems (15 papers revised). Technological flow is constant and further advances in imaging techniques and hardware components will inevitably bring new tools for a clinical translation of innovative therapeutic strategies in vascular surgery

Surgical Subtask Automation for Intraluminal Procedures using Deep Reinforcement Learning

Intraluminal procedures have opened up a new sub-field of minimally invasive surgery that use flexible instruments to navigate through complex luminal structures of the body, resulting in reduced invasiveness and improved patient benefits. One of the major challenges in this field is the accurate and precise control of the instrument inside the human body. Robotics has emerged as a promising solution to this problem. However, to achieve successful robotic intraluminal interventions, the control of the instrument needs to be automated to a large extent. The thesis first examines the state-of-the-art in intraluminal surgical robotics and identifies the key challenges in this field, which include the need for safe and effective tool manipulation, and the ability to adapt to unexpected changes in the luminal environment. To address these challenges, the thesis proposes several levels of autonomy that enable the robotic system to perform individual subtasks autonomously, while still allowing the surgeon to retain overall control of the procedure. The approach facilitates the development of specialized algorithms such as Deep Reinforcement Learning (DRL) for subtasks like navigation and tissue manipulation to produce robust surgical gestures. Additionally, the thesis proposes a safety framework that provides formal guarantees to prevent risky actions. The presented approaches are evaluated through a series of experiments using simulation and robotic platforms. The experiments demonstrate that subtask automation can improve the accuracy and efficiency of tool positioning and tissue manipulation, while also reducing the cognitive load on the surgeon. The results of this research have the potential to improve the reliability and safety of intraluminal surgical interventions, ultimately leading to better outcomes for patients and surgeons

Validazione di un dispositivo indossabile basato sulla realta aumentata per il riposizionamento del mascellare superiore

Aim: We present a newly designed, localiser-free, head-mounted system featuring augmented reality (AR) as an aid to maxillofacial bone surgery, and assess the potential utility of the device by conducting a feasibility study and validation. Also, we implement a novel and ergonomic strategy designed to present AR information to the operating surgeon (hPnP). Methods: The head-mounted wearable system was developed as a stand- alone, video-based, see-through device in which the visual features were adapted to facilitate maxillofacial bone surgery. The system is designed to exhibit virtual planning overlaying the details of a real patient. We implemented a method allowing performance of waferless, AR-assisted maxillary repositioning. In vitro testing was conducted on a physical replica of a human skull. Surgical accuracy was measured. The outcomes were compared with those expected to be achievable in a three-dimensional environment. Data were derived using three levels of surgical planning, of increasing complexity, and for nine different operators with varying levels of surgical skill. Results: The mean linear error was 1.70±0.51mm. The axial errors were 0.89±0.54mm on the sagittal axis, 0.60±0.20mm on the frontal axis, and 1.06±0.40mm on the craniocaudal axis. Mean angular errors were also computed. Pitch: 3.13°±1.89°; Roll: 1.99°±0.95°; Yaw: 3.25°±2.26°. No significant difference in terms of error was noticed among operators, despite variations in surgical experience. Feedback from surgeons was acceptable; all tests were completed within 15 min and the tool was considered to be both comfortable and usable in practice. Conclusion: Our device appears to be accurate when used to assist in waferless maxillary repositioning. Our results suggest that the method can potentially be extended for use with many surgical procedures on the facial skeleton. Further, it would be appropriate to proceed to in vivo testing to assess surgical accuracy under real clinical conditions.Obiettivo: Presentare un nuovo sistema indossabile, privo di sistema di tracciamento esterno, che utilizzi la realtà aumentata come ausilio alla chirurgia ossea maxillo-facciale. Abbiamo validato il dispositivo. Inoltre, abbiamo implementato un nuovo metodo per presentare le informazioni aumentate al chirurgo (hPnP). Metodi: Le caratteristiche di visualizzazione del sistema, basato sul paradigma video see-through, sono state sviluppate specificamente per la chirurgia ossea maxillo-facciale. Il dispositivo è progettato per mostrare la pianificazione virtuale della chirurgia sovrapponendola all’anatomia del paziente. Abbiamo implementato un metodo che consente una tecnica senza splint, basata sulla realtà aumentata, per il riposizionamento del mascellare superiore. Il test in vitro è stato condotto su una replica di un cranio umano. La precisione chirurgica è stata misurata confrontando i risultati reali con quelli attesi. Il test è stato condotto utilizzando tre pianificazioni chirurgiche di crescente complessità, per nove operatori con diversi livelli di abilità chirurgica. Risultati: L'errore lineare medio è stato di 1,70±0,51mm. Gli errori assiali erano: 0,89±0,54mm sull'asse sagittale, 0,60±0,20mm sull'asse frontale, e 1,06±0,40mm sull'asse craniocaudale. Anche gli errori angolari medi sono stati calcolati. Beccheggio: 3.13°±1,89°; Rollio: 1,99°±0,95°; Imbardata: 3.25°±2,26°. Nessuna differenza significativa in termini di errore è stata rilevata tra gli operatori. Il feedback dei chirurghi è stato soddisfacente; tutti i test sono stati completati entro 15 minuti e lo strumento è stato considerato comodo e utilizzabile nella pratica. Conclusione: Il nostro dispositivo sembra essersi dimostrato preciso se utilizzato per eseguire il riposizionamento del mascellare superiore senza splint. I nostri risultati suggeriscono che il metodo può potenzialmente essere esteso ad altre procedure chirurgiche sullo scheletro facciale. Inoltre, appare utile procedere ai test in vivo per valutare la precisione chirurgica in condizioni cliniche reali

Advanced Knowledge Application in Practice

The integration and interdependency of the world economy leads towards the creation of a global market that offers more opportunities, but is also more complex and competitive than ever before. Therefore widespread research activity is necessary if one is to remain successful on the market. This book is the result of research and development activities from a number of researchers worldwide, covering concrete fields of research

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp