Mechatronics in Medicine

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• Journal article
  Souipas S, Nguyen A, Laws SG, Davies B, Rodriguez y Baena Fet al., 2024,

  Real-time active constraint generation and enforcement for surgical tools using 3D detection and localisation network

  , Frontiers in Robotics and AI, Vol: 11, ISSN: 2296-9144

  Introduction: Collaborative robots, designed to work alongside humans for manipulating end-effectors, greatly benefit from the implementation of active constraints. This process comprises the definition of a boundary, followed by the enforcement of some control algorithm when the robot tooltip interacts with the generated boundary. Contact with the constraint boundary is communicated to the human operator through various potential forms of feedback. In fields like surgical robotics, where patient safety is paramount, implementing active constraints can prevent the robot from interacting with portions of the patient anatomy that shouldn’t be operated on. Despite improvements in orthopaedic surgical robots, however, there exists a gap between bulky systems with haptic feedback capabilities and miniaturised systems that only allow for boundary control, where interaction with the active constraint boundary interrupts robot functions. Generally, active constraint generation relies on optical tracking systems and preoperative imaging techniques.Methods: This paper presents a refined version of the Signature Robot, a three degrees-of-freedom, hands-on collaborative system for orthopaedic surgery. Additionally, it presents a method for generating and enforcing active constraints “on-the-fly” using our previously introduced monocular, RGB, camera-based network, SimPS-Net. The network was deployed in real-time for the purpose of boundary definition. This boundary was subsequently used for constraint enforcement testing. The robot was utilised to test two different active constraints: a safe region and a restricted region.Results: The network success rate, defined as the ratio of correct over total object localisation results, was calculated to be 54.7% ± 5.2%. In the safe region case, haptic feedback resisted tooltip manipulation beyond the active constraint boundary, with a mean distance from the boundary of 2.70 mm ± 0.37 mm and a mean exit d

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• Journal article
  Jianu T, Huang B, Nhat Vu M, Abdelaziz MEMK, Fichera S, Lee CY, Berthet-Rayne P, Rodriguez y Baena F, Nguyen Aet al., 2024,

  CathSim: An Open-Source Simulator for Endovascular Intervention

  , IEEE Transactions on Medical Robotics and Bionics, Vol: 6, Pages: 971-979

  Autonomous robots in endovascular operations have the potential to navigate circulatory systems safely and reliably while decreasing the susceptibility to human errors. However, there are numerous challenges involved with the process of training such robots, such as long training duration and safety issues arising from the interaction between the catheter and the aorta. Recently, endovascular simulators have been employed for medical training but generally do not conform to autonomous catheterization due to the lack of standardization and RL framework compliance. Furthermore, most current simulators are closed-source, which hinders the collaborative development of safe and reliable autonomous systems through shared learning and community-driven enhancements. In this work, we introduce CathSim, an open-source simulation environment that accelerates the development of machine learning algorithms for autonomous endovascular navigation. We first simulate the high-fidelity catheter and aorta with a state-of-the-art endovascular robot. We then provide the capability of real-time force sensing between the catheter and the aorta in simulation. Furthermore, we validate our simulator by conducting two different catheterization tasks using two popular reinforcement learning algorithms, namely SAC and PPO. The experimental results show that our open-source simulator can mimic the behavior of real-world endovascular robots and facilitate the development of different autonomous catheterization tasks. Our simulator is publicly available at https://github.com/airvlab/cathsim.

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• Journal article
  Hu X, Cutolo F, Iqbal H, Henckel J, Rodriguez y Baena Fet al., 2024,

  Artificial Intelligence-driven Framework for Augmented Reality Markerless Navigation in Knee Surgery

  , IEEE Transactions on Artificial Intelligence

  Conventional orthopaedic navigation systems depend on marker-based tracking, which may introduce additional skin incisions, increase the risk and discomfort for the patient, and entail increased workflow complexity. The guidance is conveyed via 2D monitors, which may distract the surgeon and increase the cognitive burden.</p> <p>This study presents an Artificial Intelligence (AI) - driven surgical navigation framework for knee replacement surgery. The system comprises an Augmented Reality (AR) interface that combines an occlusions-robust deep learning-based markerless bone tracking and registration algorithm with a commercial HoloLens 2 headset calibrated for the user&#x2019;s perspective on both eyes. The feasibility of such a system in navigating a bone drilling task is investigated with an experienced orthopaedic surgeon on three cadaveric knees under realistic operating room conditions. After registering an implant model to computed tomography (CT) scans, the preoperative plans are determined based on the location of the fixation pins. Navigation accuracy is quantified using a highly accurate optical tracking system.</p> <p>The achieved drilling error is 7.88&#x00B1;2.41mm in translation and 7.36&#x00B1;1.77&#x00B0; in orientation. The results demonstrate the viability of integrating AI and AR technology to navigate knee surgery.

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• Conference paper
  Zari E, Grillo D, Tan Z, Swiatek N, Linfoot JD, Borvorntanajanya K, Nasca L, Pierro E, Florea L, Dini D, Rodriguez Y Baena Fet al., 2024,

  A Reinforced Light-Responsive Hydrogel for Soft Robotics Actuation

  , Pages: 270-275

  Light-responsive hydrogels are intelligent materials that respond to external light stimuli. When exposed to light, they shrink by releasing water, enabling non-invasive, cost-effective, and remotely controllable actuation. Their adaptability to light parameters such as intensity, direction, wavelength, and irradiation time makes these materials ideal for developing soft robotic actuators. However, hydrogel-based actuators face several challenges due to poor mechanical properties, complex fabrication, and biocompatibility concerns. To address these limitations, this study presents a light-driven 3D-printed elastomer/hydrogel composite actuator. The soft photo-actuator combines TangoPlus, a flexible 3D printing material, with a poly(N-isopropylacrylamide) (PNIPAM) hydrogel copolymerized with the photochromic molecule spiropyran. The study's key contributions include an investigation into prototypes that demonstrate enhanced mechanical integrity, where hydrogel thickness and curing time are shown to affect the actuator's shrinkage response in a predictable manner. Furthermore, a proof-of-concept of a 3D gripping mechanism is proposed to demonstrate the actuator's potential applicability.

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• Journal article
  Ferrandy V, Indrawanto, Ferryanto F, Sugiharto A, Franco E, Garriga-Casanovas A, Mahyuddin AI, Baena FRY, Mihradi S, Virdyawan Vet al., 2023,

  Modeling of a two-degree-of-freedom fiber-reinforced soft pneumatic actuator

  , ROBOTICA, Vol: 41, Pages: 3608-3626, ISSN: 0263-5747
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• Journal article
  Cui Z, Cartucho J, Giannarou S, Baena FRYet al., 2023,

  Caveats on the First-Generation da Vinci Research Kit: Latent Technical Constraints and Essential Calibrations

  , IEEE ROBOTICS & AUTOMATION MAGAZINE, ISSN: 1070-9932
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• Journal article
  Souipas S, Nguyen A, Laws SG, Davies BL, Baena FRYet al., 2023,

  SimPS-Net: Simultaneous Pose and Segmentation Network of Surgical Tools

  , IEEE TRANSACTIONS ON MEDICAL ROBOTICS AND BIONICS, Vol: 5, Pages: 614-622
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• Journal article
  Hu ZJ, Wang Z, Huang Y, Sena A, Rodriguez y Baena F, Burdet Eet al., 2023,

  Towards human-robot collaborative surgery: trajectory and strategy learning in bimanual peg transfer

  , IEEE Robotics and Automation Letters, Vol: 8, Pages: 4553-4560, ISSN: 2377-3766

  While the traditional control of surgical robots relies on fully manual teleoperations, human-robot collaborative systems promise to address issues such as workspace constrains and laborious tasks. In particular, shared control can reduce the surgeon's workload and improve the overall surgical performance by supporting the surgeon effort during movements while keeping them in charge of complex control phases. In this letter, we propose a segmentation of the bimanual peg transfer task that alternates manual and autonomous control correspondingly. The authority allocation in this shared control framework considers both the limitation of learning-based methods and the higher dexterity of humans during physical interaction. The motion and strategies are transferred from an expert human to a da Vinci Research Kit (dVRK) using an epsilon-greedy on a maximum entropy inverse reinforcement learning algorithm. The model generated enables to train an intelligent agent that can skillfully collaborate with the human operator during the surgical task. The proposed shared control framework is verified both on a virtual platform and then on a real dVRK to assess its usability and robustness. The results show that, compared to traditional teleoperation, our method can achieve faster and more consistent peg transfers. An analysis of the participants' effort also reveals a significantly lower perception of the workload.

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• Journal article
  Aktas A, Demircali AA, Secoli R, Temelkuran B, Rodriguez y Baena Fet al., 2023,

  Towards a procedure-optimised steerable catheter for deep-seated neurosurgery

  , Biomedicines, Vol: 11, Pages: 1-17, ISSN: 2227-9059

  In recent years, steerable needles have attracted significant interest in relation to minimally invasive surgery (MIS). Specifically, the flexible, programmable bevel-tip needle (PBN) concept was successfully demonstrated in vivo in an evaluation of the feasibility of convection-enhanced delivery (CED) for chemotherapeutics within the ovine model with a 2.5 mm PBN prototype. However, further size reductions are necessary for other diagnostic and therapeutic procedures and drug delivery operations involving deep-seated tissue structures. Since PBNs have a complex cross-section geometry, standard production methods, such as extrusion, fail, as the outer diameter is reduced further. This paper presents our first attempt to demonstrate a new manufacturing method for PBNs that employs thermal drawing technology. Experimental characterisation tests were performed for the 2.5 mm PBN and the new 1.3 mm thermally drawn (TD) PBN prototype described here. The results show that thermal drawing presents a significant advantage in miniaturising complex needle structures. However, the steering behaviour was affected due to the choice of material in this first attempt, a limitation which will be addressed in future work.

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• Conference paper
  Franco E, Aktas A, Treratanakulchai S, Garriga Casanovas A, Donder A, Rodriguez y Baena Fet al., 2023,

  Discrete-time model based control of soft manipulator with FBG sensing

  , ICRA 2023, Publisher: IEEE, Pages: 567-572

  In this article we investigate the discrete-time model based control of a planar soft continuum manipulator with proprioceptive sensing provided by fiber Bragg gratings.A control algorithm is designed with a discrete-time energyshaping approach which is extended to account for control-related lag of digital nature. A discrete-time nonlinear observer is employed to estimate the uncertain bending stiffness of the manipulator and to compensate constant matched disturbances. Simulations and experiments demonstrate the effectiveness of the controller compared to a continuous time implementation.

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