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In this paper, we design, develop, and validate a surgical robotic system, entitled Robossis, to assist long-bone fracture reduction, i.e., alignment, surgeries. Unlike traditional long-bone fracture surgeries, Robossis enables the surgeon to precisely align the fractured bone in the presence of large traction forces and torques. The proposed surgical system includes a novel 3-armed robot, a bone-gripping mechanism, and a master controller. The 6-DOF 3-armed wide-open parallel robot has a unique architecture, which facilitates positioning the bone inside the robot, providing a large workspace for surgical maneuvers. Kinematic analysis shows that the symmetric 3-armed mechanism provides a significant advantage over the Gough-Stewart platform, i.e., 15 times larger rotational workspace, which is a vital advantage for fracture alignment. Theoretical and experimental testing are performed to demonstrate Robossis performance, including high accuracy and force insertion capabilities. A successful cadaver test was performed using a Robossis prototype, which shows that guided by intraoperative X-ray imaging, Robossis is able to manipulate bone in all translational and rotational directions while encountering the muscle payload surrounding the femur. Robossis is designed to balance accuracy, payload, and workspace, and its innovative design presents major advantages over the existing robot designs for the reduction of long-bone fractures.

This paper presents the experimental position and force testing of a 3-armed 6-DOF Parallel Robot, Robossis, that is specifically designed for the application of long-bone femur fracture surgery. Current surgical techniques require a significant amount of time and effort to restore the fractured femur fragments’ length, alignment and rotation. To address these issues, the Robossis system will facilitate the femur fracture surgical procedure and oppose the large traction forces/torques of the muscle groups surrounding the femur. As such, Robossis would subsequently improve patient outcomes by eliminating intraoperative injuries, reducing radiation exposure from X-rays during surgery and decreasing the likelihood of follow-up operations. Specifically, in this paper, we study the accuracy of the Robossis system while moving in the operational workspace under free and simulated traction loads of ([Formula: see text]–1100[Formula: see text]N). Experimental testing in this study demonstrates that Robossis can reach the most extreme points in the workspace, as defined by the theoretical workspace, while maintaining minimal deviation from those points with an average deviation of 0.324[Formula: see text]mm. Furthermore, the force testing experiment shows that Robossis can counteract loads that are clinically relevant to restoring the fractured femur fragments’ length, alignment and rotation. In addition, we study the accuracy of Robossis motion while coupled with the master controller Sigma 7. The results show that Robossis can follow the desired trajectory in real-time with an average error of less than 1[Formula: see text]mm. To conclude, these results further establish the ability of the Robossis system to facilitate the femur fracture surgical procedure and eliminate limitations faced with the current surgical techniques.

Recent years have witnessed a growing interest in interactive narrative-based serious games for education and training. A key challenge posed by educational serious games is the balance of fun and learning, so that players are motivated enough to unfold the narrative stories on their own pace while getting sufficient learning materials across. In this chapter, various design strategies that aim to tackle this challenge are presented through the development of Sustain City, an educational serious game system that engages students, particularly prospective and beginning science and engineering students, in a series of engineering design. Besides narrative-learning synthesis, supplementing the player's actions with feedback, and the development of a sufficient guidance system, the chapter also discusses the integration of rigorous assessment and personalized scaffolding. The evaluation of Sustain City deployment confirms the values of the serious games in promoting students' interests and learning in science, technology, engineering, and mathematics (STEM) fields.

Femur fractures due to traumatic forces often require surgical intervention. Such surgeries require alignment of the femur in the presence of large muscular forces up to 500 N. Currently, orthopedic surgeons perform this alignment manually before fixation, leading to extra soft tissue damage and inaccurate alignment. One of the limitations of femoral fracture surgery is the limited vision and two-dimensional nature of X-ray images, which typically guide the surgeon in diagnosing the position of the femur. Other limitations include the lack of precise intraoperative planning and the process of trial-and-error alignment. To alleviate the issues discussed, we develop a marker-based approach for detecting the position of femur fragments using two X-ray images. The relative spatial position of the femur fragments plays a key role in guiding an innovative robotic system, named Robossis, for femur fracture alignment surgeries. Using the derived three-dimensional data, we simulate pre-programmed movements to visualize the proposed steps of the alignment method, while the bone fragments are attached to the robot. Ultimately, Robossis aims to improve the accuracy of femur alignment, which results in improved patient outcomes.

Alignment of femur fractures requires high precision in the presence of a huge traction force which is very arduous. The difficulties are mainly due to the bone’s elongated anatomy and its strong counteracting muscles, which necessitate a high traction force to be exerted by the surgeon and the medical team. Robossis eliminates the need for the surgeon to apply this force, and significantly improves the precision of the procedure. This platform will balance the accuracy, payload, and workspace for the surgeon, resulting in more efficient, successful surgeries. The experimental tests on a phantom reveal that the mechanism is well capable of applying the desired reduction steps against the large muscular payloads with high accuracy.

In this paper, a new highly convergent, efficient, and fast response control technique entitled as fuzzy-Pade control method is introduced. It provides a simple methodology to exploit the heuristic knowledge in controlling a system. Fuzzy–Pade controllers originate from a unification of heuristic knowledge expressed as the rule base, and Pade approximants. In this method, fuzzy singleton rules are used to generate the rule base. Accordingly, unknown parameters in the Pade approximant are determined using these rules. The fuzzy-Pade controllers possess certain advantages over fuzzy controllers, and they can be applied in situations where fuzzy controllers previously failed. To demonstrate the effectiveness and robustness of the method, the simulation results for three case studies, the single inverted pendulum, ball and beam, and parallel double inverted pendulum systems are presented. In the case studies, it is shown that the fuzzy-Pade controller has greater convergence region, is quite faster, and its energy consumption is much lower than the fuzzy controller.