Akira Fukuhara

Optimization of retraction in neurosurgery to avoid damage caused by deformation of brain tissues

In neurosurgery, effects of deformation should be considered to avoid damaging brain tissues. The goal of this study is to develop an automatic path planner considering the deformation of brain tissues. This paper shows a scheme which combines FEM (Finite Element Method) and an optimization method for optimization of retraction in order to approach a deep part of a brain. Also, evaluations of two optimization results are discussed. One optimization is for retraction of a simple shape model for comparing two solvers, Pattern Search and Genetic Algorithm. Pattern Search Algorithm obtained maximum view size for the simple model when the principal stress of the tissue is not more than the threshold 500 (Pa). The other optimization is for retraction of a brain fissure model. Based on the result of the simple shape model, Pattern Search Algorithm is used for this optimization. It successfully generated optimal position and posture of a spatula for opening the fissure model which has same mechanical property with the human brain. These results show the effectiveness of the proposed scheme.

Leg Stiffness Control Based on “TEGOTAE” for Quadruped Locomotion

Quadrupeds exhibit adaptive limb coordination to achieve versatile and efficient locomotion. In particular, the leg-trajectory changes in response to locomotion speed. The goal of this study is to reproduce this modulation of leg-trajectory and to understand the control mechanism underlying quadruped locomotion. We focus primarily on the modulation of stiffness of the leg because the trajectory is a result of the interaction between the leg and the environment during locomotion. In this study, we present a “TEGOTAE”-based control scheme to modulate the leg stiffness. TEGOTAE is a Japanese concept describing the extent to which a perceived reaction matches the expected reaction. By using the presented scheme, foot-trajectories were modified and the locomotion speed increased correspondingly.

Minimal Model for Body-Limb Coordination in Quadruped High-Speed Running.

Cursorial quadrupeds exploit their limbs and bodies (i.e., body–limb coordination) to achieve faster locomotion speed when compared to that with only limbs. Extant studies examined various legged robots that utilize flexible spine bending. However, the control principle of body–limb coordination is not established to date. This study proposes a novel control scheme for body–limb coordination in which all degrees of freedom of the entire body aid each other in achieving higher performance. The 2D simulation results indicate that mutual sensory feedback between the limb and spine plays essential roles in generating their adaptive locomotion patterns in response to physical situations of the body parts and thereby in achieving faster locomotion speeds.

Spontaneous gait transition to high-speed galloping by reconciliation between body support and propulsion

ABSTRACT Quadrupeds change their gait patterns in response to locomotion speed to achieve low cost of transport over a wide range of speeds. Understanding the underlying control mechanism is essential to establish a design principle for legged robots that can adaptively generate energy-efficient locomotion patterns. Even decerebrate cats exhibit spontaneous gait transition, suggesting that adaptive gait patterns are generated via decentralized control systems, i.e. central pattern generators and reflexes. Several studies address this issue; however, the essential control mechanism that enables spontaneous transition from low- to high-speed gait is still poorly understood. To address this issue, this work reconsiders the interlimb coordination mechanism by focusing on two fundamental roles of limbs: body support and propulsion. To verify the proposed model, 2D simulations and 3D hardware experiments were conducted. The results indicate that the proposed model enables the robot to spontaneously exhibit gait transition to high-speed galloping and to achieve faster and more energy-efficient locomotion than a bounding gait in 3D hardware experiments. GRAPHICAL ABSTRACT

A simple body-limb coordination model that mimics primitive tetrapod walking

The coordination of body and limbs motions contributes to effective propulsion in limed locomotion. However, there is lack of understanding that characterizes the mechanism underlying the body-limb coordination. The aim of this study involves clarifying the mechanism through mathematical modeling and dynamic simulation. To this end, a body-limb coordination model was designed based on a simple rule by effectively using a pivot turn. The model successfully generated locomotion similar to primitive tetrapod walking, e.g. salamander and Polypterus walking based on their physical properties.

Quadruped Gait Transition from Walk to Pace to Rotary Gallop by Exploiting Head Movement

The manner in which quadrupeds change their locomotion patterns with change in speed is poorly understood. In this paper, we demonstrate spontaneous gait transition by using a quadruped robot model with a head segment, for which leg coordination can be self-organized through a simple “central pattern generator” (CPG) model with a postural reflex mechanism. Our model effectively makes use of head movement for the gait transition, suggesting that head movement is crucial for the reproduction of the gait transition to high-speed gaits in quadrupeds.

Securing an optimum operating field without undesired tissue damage in neurosurgery

Graphical Abstract In neurosurgery, surgeons sometimes retract brain tissue to prepare an operating field around a lesion. In addition, they are required to plan a safe surgical pathway for deep-brain regions while considering tissue damage caused by excessive stress. The goal of this study is to develop a technique for automatically generating a surgery pathway for lesions in the deep-brain region, focusing on securing an operating field around the lesion as a first step and also considering brain tissue deformation. In previous studies, securing the operating field has been treated as a single-objective optimization problem in order to maximize the viewable area of the lesion. However, in this study, the task of securing the operating field is formulated as a multi-objective optimization problem. Using a technique that combines finite element analysis and an optimization method, the principal stress on the brain is constrained to less than a certain threshold value, and the position and orientation of the surgical instrument are optimized for safe retraction of the brain according to various weighting factors.