Table tennis players often execute one-step, side-step or cross-step to move to an appropriate position for topspin forehand. However, to our knowledge, no studies have investigated the footwork effects on lower-limb kinetics and kinematics, which are related to playing performance and injury prevention. This study examined the ground reaction forces, joint kinetics and in-shoe plantar pressure distribution during topspin forehand with three typical footwork patterns. Fifteen male table tennis players performed cross-court topspin forehands in one-step, side-step and cross-step. Force plate, motion capturing, and instrumented insole systems were used to measure ground reaction force, joint moments and plantar pressure variables. One-way ANONA with repeated measures was performed to determine any significant differences between footwork. Results indicated that participants exhibited significantly higher ground reaction force loadings, knee flexion angle, knee moment, ankle inversion and moment during side-step and cross-step compared with one-step footwork condition (p < .01). Plantar pressure data indicated that the significantly higher peak pressure were observed in the total foot, toe, 1st, 2nd and 5th metatarsal regions during side-step and cross-step (p < .01). Additionally, cross-step had induced higher peak pressure in medial midfoot and heel regions than one-step and higher peak pressure in total and 1st metatarsal regions than side-step (p < .01). These results suggest that foot orthotic designs should consider the stronger emphasis on those high-pressured areas and that the differential joint and plantar loadings in side-step and cross-step may provide useful insights to injury mechanism and training protocol development.

Effects of foot orthoses on dynamic balance and basketball free-Effects of foot orthoses on dynamic balance and basketball free-throw accuracy Effects of foot orthoses on dynamic balance and basketball free-throw accuracy before and after physical fatigue before and after physical fatigue

Context: As robot-assisted surgery is increasingly used in surgical care, the engineering research effort towards surgical automation has also increased significantly. Automation promises to enhance surgical outcomes, offload mundane or repetitive tasks, and improve workflow. However, we must ask an important question: should autonomous surgery be our long-term goal? Objective: To provide an overview of the engineering requirements for automating control systems, summarize technical challenges in automated robotic surgery, and review sensing and modeling techniques to capture real-time human behaviors for integration into the robotic control loop for enhanced shared or collaborative control. Evidence acquisition: We performed a nonsystematic search of the English language literature up to March 25, 2021. We included original studies related to automation in robot-assisted laparoscopic surgery and human-centered sensing and modeling. Evidence synthesis: We identified four comprehensive review papers that present techniques for automating portions of surgical tasks. Sixteen studies relate to human-centered sensing technologies and 23 to computer vision and/or advanced artificial intelligence or machine learning methods for skill assessment. Twenty-two studies evaluate or review the role of haptic or adaptive guidance during some learning task, with only a few applied to robotic surgery. Finally, only three studies discuss the role of some form of training in patient outcomes and none evaluated the effects of full or semi-autonomy on patient outcomes. Conclusions: Rather than focusing on autonomy, which eliminates the surgeon from the loop, research centered on more fully understanding the surgeon's behaviors, goals, and limitations could facilitate a superior class of collaborative surgical robots that could be more effective and intelligent than automation alone. Patient summary: We reviewed the literature for studies on automation in surgical robotics and on modeling of human behavior in human-machine interaction. The main application is to enhance the ability of surgical robotic systems to collaborate more effectively and intelligently with human surgeon operators.

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