This experimental study aimed at evaluating the efficiency of robots in the learning of surgical techniques. We recruited 40 surgeons, divided them into 2 groups of 20, each of which used the robotic system. The first group consisted of experienced physicians, and the second group comprised physicians in training. Each surgeon was allowed to use the da Vinci robotic system for 30 minutes twice in the span of 24 hours. The practice time period was divided into 15 minutes for tying and placement of sutures and 15 minutes for incisions and vascular suturing. We recorded the times required for the performances, and a statistically significant outcome was obtained. With variance analysis (ANOVA), it has been shown that the time needed to perform the exercises depends in a statistically significant way on the kind of test to be performed (P<0.01), the experience of the surgeon (P<0.001), and the kind of operation (P<0.025). Robotic systems can be an optimal tool both for residents and experienced surgeons, for learning of basic surgical tasks and for perfection of clinical skills. The use of the system has great potential in surgical training, offering a reduction in the learning period, enabling checking for errors, and allowing an evaluation of the capabilities obtained. Final goals are a drastic reduction in the learning curve, a better technique, with a significant reduction in surgical errors and complications, with greater safety for the patient.
Background: Unicompartmental knee arthroplasty (UKA) procedures have become much more common in the United States in recent years, with >40,000 UKAs performed annually. However, it is estimated that 10% to 40% of UKAs fail and thus require conversion to total knee arthroplasty (TKA). In the field of total joint arthroplasty, robotic-assisted surgeries have demonstrated advantages such as better accuracy and precision of implant positioning and improved restoration of a neutral mechanical axis.
Aim: To evaluate the clinical efficacy and imaging outcomes of a domestically produced orthopedic surgical robot for total knee arthroplasty and to explore its applicability in patients with varying degrees of deformity.
Methods: This study retrospectively included 120 patients who underwent TKA at our hospital between February 2023 and June 2024. The patients were divided into a control group (conventional TKA surgery) and an observation group (robot-assisted TKA surgery), with 60 patients in each group.
Recently, social demands for a good quality of life have increased among the elderly and disabled people. So, biomedical engineers and robotic researchers aimed to fuse these techniques in a novel rehabilitation system. Moreover, these models utilized the biomedical signals acquired from the human body's particular organ, cells, or tissues.
Department of Mechanical Engineering, Institute of Advanced Machines and Design, Institute of Engineering Research, Seoul National University, Seoul, Republic of Korea.
Soft sensors integrated or attached to robots or human bodies enable rapid and accurate estimation of the physical states of the target systems, including position, orientation, and force. While the use of a number of sensors enhances precision and reliability in estimation, it may constrain the movement of the target system or make the entire system complex and bulky. This article proposes a rapid, efficient framework for determining where to place the sensors on the system given the limited number of available sensors.
