Current pelvic fixation techniques rely on rigid drilling tools, which inherently constrain the placement of rigid medical screws in the complex anatomy of pelvis. These constraints prevent medical screws from following anatomically optimal pathways and force clinicians to fixate screws in linear trajectories. This suboptimal approach, combined with the unnatural placement of the excessively long screws, lead to complications such as screw misplacement, extended surgery times, and increased radiation exposure due to repeated X-ray images taken ensure to safety of procedure. To address these challenges, in this paper, we present the design and development of a unique 4-degree-of-freedom (DoF) pelvic concentric tube steerable drilling robot (pelvic CT-SDR). The pelvic CT-SDR is capable of creating long S-shaped drilling trajectories that follow the natural curvatures of the pelvic anatomy. The performance of the pelvic CT-SDR was thoroughly evaluated through several S-shape drilling experiments in simulated bone phantoms.

To address the screw loosening and pullout limitations of rigid pedicle screws in spinal fixation procedures, and to leverage our recently developed Concentric Tube Steerable Drilling Robot (CT-SDR) and Flexible Pedicle Screw (FPS), in this paper, we introduce the concept of Augmented Bridge Spinal Fixation (AB-SF). In this concept, two connecting J-shape tunnels are first drilled through pedicles of vertebra using the CT-SDR. Next, two FPSs are passed through this tunnel and bone cement is then injected through the cannulated region of the FPS to form an augmented bridge between two pedicles and reinforce strength of the fixated spine. To experimentally analyze and study the feasibility of AB-SF technique, we first used our robotic system (i.e., a CT-SDR integrated with a robotic arm) to create two different fixation scenarios in which two J-shape tunnels, forming a bridge, were drilled at different depth of a vertebral phantom. Next, we implanted two FPSs within the drilled tunnels and then successfully simulated the bone cement augmentation process.

Spinal fixation procedures rely on pedicle screws to stabilize the vertebral column, but conventional rigid pedicle screws (RPS) face challenges such as misplacement, pullout, and loosening, particularly in patients with low bone mineral density (BMD). To overcome these limitations, we recently proposed a flexible pedicle screw (FPS) inserted inside a J-shape trajectory drilled by a steerable drilling robot. Towards biomechanical evaluation of our proposed FPS for spinal fixation procedures, in this paper, we introduce the design, integration, calibration, and evaluation of an optical frequency domain reflectometry (OFDR) strain sensor into an FPS. This sensor-integrated FPS (Si-FPS) provides real-time strain and shape-sensing information, facilitating improved implant functionality assessment and optimization. To thoroughly evaluate the Si-FPS, we first additively manufacture a special FPS and integrate a OFDR shape sensing assembly within its structure. We then assess shape sensing performance of this sensorized FPS using static and dynamic FPS insertion experiments.

In this paper, we introduce S3D: A Spatial Steerable Surgical Drilling Framework for Robotic Spinal Fixation Procedures. S3D is designed to enable realistic steerable drilling while accounting for the anatomical constraints associated with vertebral access in spinal fixation (SF) procedures. To achieve this, we first enhanced our previously designed concentric tube Steerable Drilling Robot (CT-SDR) to facilitate steerable drilling across all vertebral levels of the spinal column. Additionally, we propose a four-Phase calibration, registration, and navigation procedure to perform realistic SF procedures on a spine holder phantom by integrating the CT-SDR with a seven-degree-of-freedom robotic manipulator. The functionality of this framework is validated through planar and out-of-plane steerable drilling experiments in vertebral phantoms.

In this study, we introduce a new concept for reconstruction of Volumetric Muscle Loss (VML) injuries and propose the spatial robotic embedded bioprinting technique. As opposed to the traditional layer-by-layer printing, we leverage the support-free nature of embedded bioprinting to print spatial and complex structures of fascicles in a fusiform muscle. To demonstrate feasibility of this concept, we first propose our robotic bioprinting framework including a robotic arm integrated with a custom-designed bioprinting injector. Complementary motion planning algorithms uniquely designed for this printing task are further proposed. Moreover, the effect of embedded bioprinting parameters, as well as the supporting bath and injecting materials compatibility on the uniformity and quality of the printed constructs has been analyzed. Finally, we perform a case study by printing a fusiform muscle-shape construct using the proposed concept and algorithms, and evaluate the quality of the printed structure.

In this paper, a novel mathematical framework is introduced for modeling deformation behavior of Tendon-Driven Continuum Manipulators (TD-CMs) featuring discontinuous cross-sectional geometries (i.e., having flexural patterns). Leveraging this framework, we also introduce the concept of design space by which the deformation-behavior space of a TD-CM can intuitively be analyzed via its geometrical design parameters. To thoroughly evaluate the performance of the proposed modeling framework, we have conducted various simulation studies and experiments.

In this paper, to collectively address the existing limitations on endoscopic diagnosis of Advanced Gastric Cancer (AGC) Tumors, for the first time, we propose (i) utilization and evaluation of our recently developed Vision-based Tactile Sensor (VTS), and (ii) a complementary Machine Learning (ML) algorithm for classifying tumors using their textural features. Leveraging a seven DoF robotic manipulator and unique custom-designed and additively-manufactured realistic AGC tumor phantoms, we demonstrated the advantages of automated data collection using the VTS addressing the problem of data scarcity and biases encountered in traditional ML-based approaches. Our synthetic-data-trained ML model was successfully evaluated and compared with traditional ML models utilizing various statistical metrics even under mixed morphological characteristics and partial sensor contact.

Spinal fixation procedures are currently limited by the rigidity of the existing instruments and pedicle screws leading to fixation failures and rigid pedicle screw pull out. Leveraging our recently developed Concentric Tube Steerable Drilling Robot (CT-SDR) in integration with a robotic manipulator, to address the aforementioned issue, here we introduce the transformative concept of Spatial Spinal Fixation (SSF) using a unique Flexible Pedicle Screw (FPS). The proposed SSF procedure enables planar and out-of-plane placement of the FPS throughout the full volume of the vertebral body. In other words, not only does our fixation system provide the option of drilling in-plane and out-of-plane trajectories, it also enables implanting the FPS inside linear (represented by an I-shape) and/or non-linear (represented by J-shape) trajectories. To thoroughly evaluate the functionality of our proposed robotic system and the SSF procedure, we have performed various experiments by drilling different I-J and J-J drilling trajectory pairs into our custom-designed L3 vertebral phantoms and analyzed the accuracy of the procedure using various metrics.