This article assessed how surgical robot parameters influenced operator viewpoint during a simulated surgical procedure. Surgical robots are useful tools in minimally invasive surgery. However, even with robots, suturing is difficult because the needle is sometimes obscured by tissue or manipulators and is thus not always visible during the procedure. This is especially true in pediatric surgery, where the surgical environment is smaller than in adult surgery. Hence, surgeons must carefully track the instruments and tissues to understand and predict their current and expected situations. In this article, we used gaze-tracking techniques to analyze the location and timing of the gaze of participants while they manipulated a virtual robotic surgical simulation system. To differentiate between the ideal and actual viewpoint trajectories, we conducted experiments with and without obstacles (i.e., simulated tissue and the manipulator arm). In the obstacle condition, we modulated the wrist length of the manipulator to bring it into view. In the no-obstacle condition, the participants mostly watched the suture needle tip. In the with-obstacle condition, the participants spent less time watching the instruments and more time watching the target point. The amount of time spent watching the target point increased as wrist length increased. Given this tradeoff relationship, we examined the proportion of time the participants spent looking at the instruments or target points by wrist length. We calculated the Pareto solutions and clarified the relationship between wrist length and the watching parts.

Powered prosthetic hands are becoming increasingly functional through sensory feedback. However, when using electrical stimulation as sensory feedback for electromyographic (EMG) prosthetics, stimulation artifacts may cause EMG data noise. Electrical stimulation and EMG measurements are therefore performed using time-division methods in rehabilitation facilities. Under time-division methods, EMG levels cannot be acquired at the stimulation time. Highly functional prosthetic hands that can estimate grip force, however, use advanced signal processing and require detailed EMG information. EMG measuring cycle expansion may make grip force estimation unstable. We therefore developed a grip force estimation system using muscle stiffness and EMG as the estimation source signals. The estimation system consists of a muscle stiffness sensor, an EMG sensor and an estimation algorithm. We chose a tray holding task for the system evaluation. A weight is dropped on the tray and subjects are expected to control the tray's attitude. Grip force, EMG, and muscle stiffness are measured, and the measured and estimated grip forces are compared. The proposed algorithm estimates grip force with an error of just 18[N], which is 30% smaller than in EMG-only methods. The system response time is lower than human mechanical reaction time, validating the effectiveness of the proposed method.

Mechanical performance of a surgical robot can be evaluated and improved based on a working score; however, intuitive operability cannot be evaluated in this way. We propose a method that measures the user's brain activity for evaluating intuitive operability from the perspective of cognitive science. We hypothesized that hand-eye coordination, such as the slave configuration for the endoscope, has the greatest effect on intuitive operability, because it is the cause of physical differences between a human and a robot. The objective of this paper is to clarify the appropriate slave configuration for the endoscope to study hand-eye coordination using brain activity measurements. In the experiment, we used a brain imaging device, optical topography, to measure the users' brain activity while they controlled the hand-controller to position the tip of the virtual arm on the target. The experiment was carried out a number of times with the virtual arm position configured in a variety of ways. According to the results, some subjects showed peak performance with a specific slave configuration. We conclude that the slave configuration with the highest brain activity depends on the body image, which is a spatial symbol in the human brain from the perspective of cognitive science.

Robotic gait training has been introduced recently in rehabilitation, and the related researches have been conducted to propose more effective mechanism and control. To automate gait training, position control with reference trajectory has been adopted in many researches. However, there remain problems such as enhancing self-dominated gait or adapting to asymmetry or individual difference to apply robotic gait training to moderately affected hemiplegia patient. To solve this problem, we quantified the manual pelvic assistance (handling) provided by physical therapy, which can enhance patient's self dominated gait individually. In this paper, the physical model of handling was proposed based on the measurement and verified by multiple regression analysis.

This paper outlines a new conceptual framework for freight transportation modeling by incorporating more detailed logistics choices into an operational large-scale freight transportation modeling system named FAME (Freight Activity Micro-simulation Estimator). FAME is a micro-simulation model for freight transportation in the U. S. Despite many previous freight transportation models the model simulates commodity movements at the disaggregate level of firm-to-firm, but it also makes certain simplifying assumptions concerning logistics choices such as the use of intermediate handling facilities. This paper deals with issues related to incorporating the new logistics elements in the FAME framework and proposing a new conceptual framework named FAME II.

Recently, increased attention has been focused on single port endoscopic surgery (SPS). We have developed a robotic system for SPS with two surgical manipulators: an endoscopic manipulator and a positioning manipulator that moves the endoscope. The robot can manipulate both the position and orientation of the endoscope to achieve the desirable endoscopic field of view. Two methods can be used to operate the endoscopic view: “control corresponding to position” mode and “control corresponding to velocity” mode. Although both are widely used for moving the visual field, the operability of each method has not been examined quantitatively. Thus, we compare the operability of the two methods for adjusting the endoscopic view, and present the results and suitable applications of each method. The results of the quantitative evaluation experiments show that the “control corresponding to position” mode is suitable for short-distance or precise adjustment of the endoscope, whereas the “control corresponding to velocity” mode is better suited to long-distance movement.

In this paper, by means of a statistical method, we use sole pressure on each part, angle of joint, femoral and crural muscle activities to produce a new foot muscle activity model for use in the design of ankle-foot orthoses. We built a Bayesian network model[1] by examining the normal gait of a nondisabled subject. We measured the activity of the lower foot muscles using electromyography, joint angles and the pressure on different parts of the sole. From these data, we built three models, representing the stance phase, the control phase and the propulsive phase. The accuracy of these models was confirmed. The largest feature of this model is making every 10% level nodes of each measurement data. Normal Bayesian network can estimate only muscle active or not active. But this method can estimate activity level of muscle. From this feature this method has three advantages. First, our use of 10% increments in the levels of the measured factors enabled changes in these factors during gait to be reflected in the model. Second, variations in the influence of factors that differ between low and high muscle activity are represented. Third, it is easier to use than physical models; three-dimensional motion analysis is not required and the method is convenient for clinical use. In an evaluation of this model, we confirmed that this model can estimate all muscular activity level with an accuracy rate greater than 95%.

Needle insertion treatments require accurate placement of the needle tip into the target cancer. However, it is difficult to insert the needle accurately because of cancer displacement caused by organ deformation. Therefore, a path planning using numerical simulation to analyze the deformation of the organ is important for accurate needle insertion. The problem in developing a planning method is that puncture conditions, such as the force applied to the needle, is difficult to be decided deterministically, because the experimental data of puncture conditions have variations. Therefore, the purpose of this research was to develop a novel planning method to decide the robust paths of straight needle insertion for various puncture points. The basic idea of this planning method is to consider the puncture condition probabilistic and to evaluate the expected value of needle placement accuracy. First, a probability-based puncture condition was introduced, and then the expected value of needle placement accuracy was defined. Next, the optimization method was developed to search the insertion path in a way that minimizes the expected values of needle placement accuracy. Then, a numerical simulation and evaluation of the planning method was conducted, using a liver-shaped 2D model. Furthermore, an in-vitro experiment was carried out to measure needle placement accuracy from the optimized path. Experimental results show that the planning method realizes needle insertion with a mean accuracy of 1.5 mm.

We describe a control method, for a surgical robot, which prevents the overload at fragile tissues. In particular, we focused on the control parameter setting method to ensure the robustness of the performance relative to the variation of the organ stiffness parameter. Firstly, we present Position/ Limited Stress control to achieving both precise positioning and prevention of overload. FEM based organ model was used to estimate the stress in this control method. Secondly, we describe the control parameter setting method. The control parameter was set to realize sufficient performance within the range of stiffness variation. Finally, we carried out a numerical simulation and an in vitro experiment. The simulation result suggests that our control method and parameter setting method helps prevent stress overload, not depending on the stiffness of organ model. The in vitro experimental result suggests that our method helps prevent stress overload of the in vitro-liver, the stiffness parameter of which is unknown.

Needle insertion treatments require accurate placement of the needle tip into the target cancer. However, it is difficult to insert the needle into the cancer because of cancer displacement due to the organ deformation. Then, a path planning using numerical simulation to analyze the deformation of the organ and the timing of puncture is important for the accurate needle insertion. In this study, we have explained the modeling of conditions where the puncture occurs. Firstly, this paper shows needle insertion experiments for the hog liver in order to measure the needle force and displacement where the puncture occurs. According to the experimental results, significant variations in puncture force were observed. Accordingly, we proposed a novel condition of the force causing a puncture considering probability distribution. We summarized variations of the puncture force in the experimental data and represented conditions where a puncture occurs with probability distribution models where the force is random variable. In addition, the boundary conditions and liver shapes are considered by analyzing the stress status near the needle. Then, we derived the conditions of the puncture with probability distribution models where the stress is random variable.

Organs have many vulnerable tissues such as blood vessels and nerves which must never be damaged. This paper shows a control method which prevents the overload of vulnerable tissues. Firstly, the force control method, which prevents overload, is shown. Secondly, a FEM-based stress observer using the organ model is described. Finally, a control method incorporating the first and second steps, and which prevents overload at vulnerable tissue, is shown. Based on the experimental result of positional and stress data; it is shown that the stress at vulnerable tissues didn't widely exceed limit stress, in the event that a target position potentially resulting in damage to vulnerable tissue was ordered.

This paper shows the viscoelastic and nonlinear organ deformation model for organ model-based control of needle insertion, in which the deformation of an organ is calculated intraoperatively and the needle is manipulated with organ deformation taken into consideration. An organ model including such detailed material characteristics is important to achieve the control method in question. Firstly, the material properties of the liver are modeled from the measured data and its viscoelastic characteristics are represented by differential equations, including the term of the fractional derivative. Nonlinearity in terms of the fractional derivative was measured, and modeled using the quadratic function of strain. Next, a solution of an FE model using such material properties is shown. We use sampling time scaling property as the solution for the viscoelastic system. The solution for a nonlinear system using the Modified Newton-Raphson method is also shown. Finally, the organ deformation, assuming the needle is inserted, is simulated using an organ model and the overall deformation and distribution of the strain is computed in these simulations.