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Shadows, as all other objects that surround us, are incorporated into the body and extend the body mediating perceptual information. The current study investigates the hypothesis according to which the perception of object shadows would predict the perception of body shadows. 38 participants (19 males and 19 females) aged 23 years on average were immersed into a virtual reality environment and instructed to perceive and indicate the coincidence or non coincidence between the movement of a ball shadow with regard to ball movement on the one hand, and between their body shadow and their body position in space on the other. Their brain activity was recording via a 32-channel EEG system, in which beta (13.5-30 Hz) oscillations were analyzed. A series of Multiple Regression Analysis (MRA) revealed that the beta dynamic oscillations patterns of the bilateral occipito-parieto-frontal pathway associated with the perception of ball shadow appeared to be a significant predictor of the increase in beta oscillations across frontal areas related to the body shadow perception and the decrease in beta oscillations across frontal areas connected to the decision making of the body shadow. Taken together, the findings suggest that inferential thinking ability relative to body shadow would be reliably predicted from object shadows and that the bilateral beta oscillatory modulations would be indicative of the formation of predictive neural frontal assemblies, which encode and infer body shadow neural representation, that is, a substitution of the physical body. [ABSTRACT FROM AUTHOR]

In this article, an innovative technique to design a robust finite-time state feedback controller for a class of uncertain robotic manipulators is proposed. This controller aims to converge the state variables of the system to a small bound around the origin in a finite time. The main innovation of this article is transforming the model of an uncertain robotic manipulator into a new time-varying form to achieve the finite-time boundedness criteria using asymptotic stability methods. First, based on prior knowledge about the upper bound of uncertainties and disturbances, an innovative finite-time sliding mode controller is designed. Then, the innovative finite-time sliding mode controller is developed for finite-time tracking of time-varying reference signals by the outputs of the system. Finally, the efficiency of the proposed control laws is illustrated for serial robotic manipulators with any number of links through numerical simulations, and it is compared with the nonsingular terminal sliding mode control method as one of the most powerful finite-time techniques. [ABSTRACT FROM AUTHOR]

In conventional Minimally Invasive Surgery, the surgeon conducts the operation while a human or robot holds the laparoscope. Laparoscope control is returned to the surgeon in teleoperated camera holding robots, but simultaneously controlling the laparoscope and surgical tools might be cognitively demanding. On the other hand, fully automated camera holders are still limited in their performance. To help the surgeon to better focus on the main operation while maintaining their control authority, we propose an automatic laparoscope zoom factor control framework for Robot-Assisted Minimally Invasive Surgery. In this paper, we present the perception section of the framework. It extracts and uses the surgical tool's geometric characteristics to adjust the laparoscope's zoom factor, without any artificial markers. The acceptable range and tooltip's position frequency during operations are analysed based on the gallbladder removal surgery dataset (Cholec80). The common range and tooltip's heatmap are identified and presented quantitatively.

We have investigated how surgeons can use the foot to position a laparoscopic endoscope, a task that normally requires an extra assistant. Surgeons need to train in order to exploit the possibilities offered by this new technique and safely manipulate the endoscope together with the hands movements. A realistic abdominal cavity has been developed as training simulator to investigate this multi-arm manipulation. In this virtual environment, the surgeon's biological hands are modelled as laparoscopic graspers while the viewpoint is controlled by the dominant foot. 23 surgeons and medical students performed single-handed and bimanual manipulation in this environment. The results show that residents had superior performance compared to both medical students and more experienced surgeons, suggesting that residency is an ideal period for this training. Performing the single-handed task improves the performance in the bimanual task, whereas the converse was not true.

The meshless element-free Galerkin method was generalized and an algorithm was developed for 3D dynamic modeling of deformable bodies in real time. The efficacy of the algorithm was investigated in a 3D linear viscoelastic model of human spleen subjected to a time-varying compressive force exerted by a surgical grasper. The model remained stable in spite of the considerably large deformations occurred. There was a good agreement between the results and those of an equivalent finite element model. The computational cost, however, was much lower, enabling the proposed algorithm to be effectively used in real-time applications.