Wearable gait assistive devices have been im-proved by soft robotics in terms of safety and physical burden of the wearer. Currently, electrical sensors and computers around the wearer are bottlenecks in enhancing the wearer's activities. In this paper, we present a wearable gait assistive system using soft pneumatic system for all the actuation, sensing, and computation. Pneumatic artifical muscles (PAMs) on the thighs were used to generate assistance force, and thin PAMs on the whole legs were used for sensing the wearer's motion. All thin PAMs were connected to each other by tubes, and the pressure response in the tubes were exploited to compute the wearer's motion in manner of physical reservoir computing. The left thigh angular velocity estimated from the reservoir response was used for control the PAMs for actuation. Our experiment with the use of gait assistance showed that the system worked correctly. This paper shows that the pneumatic analog computation system for sensing soft body can help the functionality of soft wearable assistive devices.

In this paper, we discuss the issue of safety in robot-assisted fracture reduction. We define the hazards of robot-assisted fracture reduction and design safety control methods. Although a large reduction force is required to reduce femoral neck fractures, an unexpectedly large force produced by a robot may cause injury to the patient. We have designed two mechanical failsafe units and a software force limiter; this along with velocity control can guarantee a safe operation in reduction force. In addition, to reduce the movement of bone fragments as much as possible, we devised spatially constrained control methods for fracture-reduction robots. The fracture-reduction system was evaluated using simulated fracture reductions.

The increase of precision and minimal invasiveness is an important current issue in orthopedic surgery. The femur and the tibia must be shaped to fit an artificial joint for successful knee arthroplasty. The recent trend towards MIS (Minimally Invasive Surgery) to decrease the length of the required incision has increased surgical difficulty, since the open access area is small. In this paper, registration and cutting error were analyzed with a robotic surgery system being developed first as an example, and a method of active compensation of robot deformation by gravity and cutting force was proposed and tried based on the error map with the expectation that the precision will increase.

Adaptive control of the machining process in orthopedic surgery will increase not only productivity but also the safety issues of tool usage. The authors have developed a technology for an adaptive control system. The system has two modes, the "predictive mode" and the "adaptive mode." The predictive mode is used to shorten the air cutting time. In the adaptive mode, the system monitors the cutting force and the cutting temperature, and controls the feed override according to the difference between the real and the desired cutting force. The software is implemented on the robot controller and its effectiveness is evaluated with a urethane bone.

Toolpath generation and optimization is considered as a challenging problem in the minimally invasive orthopedic surgery with a milling robot. The objective of this paper is to minimize the collision of the cutting tool with the soft tissues. A novel approach of toolpath generation and optimization is proposed. A redundant axis is implemented to avoid the collision in the robot. Some important components are modeled based on the physical requirements. A geometric optimization approach based on the model is proposed to improve the toolpath. Case studies show the validity of this approach. Software is developed for this application and the effectiveness is evaluated with a cadaveric bone.

Two-dimensional (2-D)/three-dimensional (3-D) registration techniques using single-plane fluoroscopy are highly important for analyzing 3-D kinematics in applications such as total knee arthroplasty (TKA) implants. The accuracy of single-plane fluoroscopy-based techniques in the determination of translation perpendicular to the image plane (depth position), however, is relatively poor because a change in the depth position causes only small changes in the 2-D silhouette. Accuracies achieved in depth position using conventional 2-D/3-D registration techniques are insufficient for clinical applications. Therefore, we propose a technique for improving the accuracy of depth position determination in order to develop a system for analyzing knee kinematics over the full six degrees of freedom (6 DOF) using single-plane fluoroscopy. In preliminary experiments, the behaviors of errors for each free variable were quantified as evaluation curves by examining changes in cost function with variations in the free variable. The evaluation curve for depth position was more jagged, and the curve peak less pointy, compared to the evaluation curves of the other five variables, and the curve was found to behave differently. Depth position is therefore optimized independently of the other variables, using an approximate evaluation curve of depth position prepared after initial registration. Accuracy of the proposed technique was evaluated by computer simulation and in vitro tests, with validation of absolute position and orientation performed for each knee component. In computer simulation tests, root-mean-square error (RMSE) in depth position was improved from 2.6 mm (conventional) to 0.9 mm (proposed), whereas for in vitro tests, RMSE improved from 3.2 mm to 1.4 mm. Accuracy of the estimation of the remaining two translational and three rotational variables was found to be almost the same as that obtained by conventional techniques. Results of in vivo tests are also described in which the possibility of full 6 DOF kinematic analysis of TKA implants is shown.

This paper describes augmented reality visualization for the guidance of breast-conservative cancer surgery using ultrasonic images acquired in the operating room just before surgical resection. By combining an optical three-dimensional (3-D) position sensor, the position and orientation of each ultrasonic cross section are precisely measured to reconstruct geometrically accurate 3-D tumor models from the acquired ultrasonic images. Similarly, the 3-D position and orientation of a video camera are obtained to integrate video and ultrasonic images in a geometrically accurate manner. Superimposing the 3-D tumor models onto live video images of the patient's breast enables the surgeon to perceive the exact 3-D position of the tumor, including irregular cancer invasions which cannot be perceived by touch, as if it were visible through the breast skin. Using the resultant visualization, the surgeon can determine the region for surgical resection in a more objective and accurate manner, thereby minimizing the risk of a relapse and maximizing breast conservation. The system was shown to be effective in experiments using phantom and clinical data.

We propose a new model and new algorithm for acquiring symbolic description from a flow field. Our model is derived from physical data, and our algorithm is based on holomorphic complex function theory. Application of this method enables both qualitative and quantitative information to be obtained from a flow field. We also demonstrate the robustness of our method using a simulated flow field and a real image sequence.