Philippe Poignet

Soft tensegrity is a recent concept, which can be described as a prestressed assembly of soft cables in tension and bars in compression. In this paper, we investigate the impact of the bar behavior on the mechanical properties of a tensegrity. This is achieved through the change of bar material, from soft (e.g., silicone) to stiff (e.g., steel) materials. First, we show that it is possible to make a self-supporting tensegrity where both cables and bars are made of soft material. Second, we highlight that the bar material impacts the isotropy of the stiffness matrix of the tensegrity and the range of achievable stiffness. Lastly, we demonstrate that the bar material has a significant impact on the precision of stiffness variation, when active elements are integrated into the tensegrity. From these effects, we extract design guidelines for the choice of bar material in a soft tensegrity.

In Total Knee Arthroplasty (TKA), the collateral ligament tensioning stage cannot be standardised for all patients and relies heavily on the surgeon's experience and perception. Intraoperative inaccuracies are practically unavoidable and may give rise to severe postoperative complications, leading to the need for revision surgery already a few years after primary TKA. This work proposes a novel instrumented tibial component able to detect collateral ligament laxity conditions right after primary TKA and, if needed, to compensate for them in the postoperative period. A miniaturised actuation system, designed to be embedded in the tibial baseplate, was initially evaluated by means of 3D simulations and then fabricated as a full-scale prototype. Stability and force sensors tests carried out on a knee simulator allowed to assess the effectiveness of the proposed design under normal working conditions and provided valuable insights for future work and improvements.

Recently, model-based visual-tracking techniques have been developed for measuring physiological motion in robot-assisted minimally invasive surgery. However, the tracking of living tissue surfaces in 3-D space is very challenging. Linear models are difficult to fit complex tissue dynamics, while current nonlinear models generally suffer from complex implementation and excessive computational burden. Instrument occlusion is another challenging issue which often causes tracking failure. In this study, we propose a novel deformable model suitable for real-time 3-D tissue tracking based on a quasi-spherical triangle. The model is parameterized by three vertices of the triangle with a curving parameter so that the warped surface can be computed efficiently using matrix operations. An efficient second-order minimization technique is employed to estimate model parameters, and the Jacobian matrix associated with the proposed model is derived. To alleviate the effects of illumination, a triangle-based illumination model is incorporated into the tracking scheme. A new motion prediction algorithm is developed by exploring the peak-valley characteristics of motion signals to handle the occlusion problem. The performance of the proposed method is validated using phantom heart data and in vivo videos acquired by the daVinci surgical robotic platform.

Robotic assistance aims to make the surgical act more intuitive and safer. In the domain of cardiac minimally invasive surgery (MIS,) heartbeat and respiration represent two important sources of disturbances. Even though miniaturized versions of heart stabilizers have been conceived for the MIS scenario, residual motion is still considerable and has to be manually canceled by the surgeon. This work focuses on computer vision techniques for estimating the 3D motion of the heart relying solely on natural structures on the heart surface for active compensation of physiological motions. A visual tracking method for estimating the 3D deformation of a region of interest on the heart surface based on the visual feedback of a stereo endoscope has been developed. The method is robust to illumination variations and large tissue deformations.