A biomechanical analysis of surgeon’s gesture in a laparoscopic virtual scenario

Minimally invasive surgery (MIS) has become very common in recent years thanks to many advantages that patients can get. However, due to the difficulties surgeons encounter to learn and manage this technique, several training methods and metrics have been proposed in order to, respectively, improve surgeon's abilities and assess his/her surgical skills. In this context, this paper presents a biomechanical analysis method of the surgeon's movements, during exercise involving instrument tip positioning and depth perception in a laparoscopic virtual environment. Estimation of some biomechanical parameters enables us to assess the abilities of surgeons and to distinguish an expert surgeon from a novice. A segmentation algorithm has been defined to deeply investigate the surgeon's movements and to divide them into many sub-movements

A 3-D Mixed-Reality System for Stereoscopic Visualization of Medical Dataset

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Using the Waseda Bioinstrumentation System WB-1R to analyze Surgeon’s performance during laparoscopy - towards the development of a global performance index -

Minimally invasive surgery (MIS) has become very common in recent years, thanks to the many advantages it provides for patients. Since it is difficult for surgeons to learn and master this technique, several training methods and metrics have been proposed, both to improve the surgeon's abilities and also to assess his/her skills. This paper presents the use of the WB-1R (Waseda Bioinstrumentation system no.1. Refined), which was developed at Waseda University, Tokyo, to investigate and analyze a surgeon's movements and performance. Specifically, the system can measure the movements of the head, the arms, and the hands, as well as several physiological parameters. In this paper we present our experiment to evaluate a surgeon's ability to handle surgical instruments and his/her depth perception using a laparoscopic view. Our preliminary analysis of a subset of the acquired data (i.e. comfort of the subjects; the amount of time it took o complete each exercise; and respiration) clearly shows that the expert surgeon and the group of medical students perform very differently. Therefore, WB-1R (or, better, a newer version tailored specifically for use in the operating room) could provide important additional information to help assess the experience and performance of surgeons, thus leading to the development of a Global Performance Index for surgeons during MIS. These analyses and modeling, moreover, are an important step towards the automatization and the robotic assistance of the surgical gesture

Defining brain–machine interface applications by matching interface performance with device requirements

Interaction with machines is mediated by human-machine interfaces (HMIs). Brain-machine interfaces (BMIs) are a particular class of HMIs and have so far been studied as a communication means for people who have little or no voluntary control of muscle activity. In this context, low-performing interfaces can be considered as prosthetic applications. On the other hand, for able-bodied users, a BMI would only be practical if conceived as an augmenting interface. In this paper, a method is introduced for pointing out effective combinations of interfaces and devices for creating real-world applications. First, devices for domotics, rehabilitation and assistive robotics, and their requirements, in terms of throughput and latency, are described. Second, HMIs are classified and their performance described, still in terms of throughput and latency. Then device requirements are matched with performance of available interfaces. Simple rehabilitation and domotics devices can be easily controlled by means of BMI technology. Prosthetic hands and wheelchairs are suitable applications but do not attain optimal interactivity. Regarding humanoid robotics, the head and the trunk can be controlled by means of BMIs, while other parts require too much throughput. Robotic arms, which have been controlled by means of cortical invasive interfaces in animal studies, could be the next frontier for non-invasive BMIs. Combining smart controllers with BMIs could improve interactivity and boost BMI applications. © 2007 Elsevier B.V. All rights reserved