Springer Science and Business Media LLC

Brain damage due to stroke often leaves survivors with lateral functional motor deficits. Bimanual rehabilitation of the paretic arm is an active field of research aimed at restoring normal functionality by making use of the complex neural bindings that exist between the arms. In search of an effective rehabilitation method, we introduced a group of post-stroke rehabilitation patients to a set of bimanual motion tasks with inter-manual coupling and phasing. The surface EMG profiles of the patients were compared in order to understand the effect of the motion conditions. The paretic arms of the patients were more strongly affected by the task conditions compared with the non-paretic arms. These results suggest that in-phase motion may activate neural circuits that trigger recovery. Coupling also had an effect on behavior, but the response of patients was divided between those whom coupling helped or hindered.

In neurosurgery, dissection and retraction are basic techniques for approaching the site of pathology. These techniques are carefully performed in order to avoid damage to nerve tissues or blood vessels. However, novice surgeons cannot train in such techniques using the haptic cues of existing training systems. This paper proposes a real-time simulation scheme for training in dissection and retraction when opening a brain fissure, which is a procedure for creating a working space before treating an affected area. In this procedure, spatulas are commonly used to perform blunt dissection and brain tissue retraction. In this study, the interaction between spatulas and soft tissues is modeled on the basis of a finite element method (FEM). The deformation of soft tissue is calculated according to a corotational FEM by considering geometrical nonlinearity and element inversion. A fracture is represented by removing tetrahedrons using a novel mesh modification algorithm in order to retain the manifold property of a tetrahedral mesh. Moreover, most parts of the FEM are implemented on a graphics processing unit (GPU). This paper focuses on parallel algorithms for matrix assembly and matrix rearrangement related to FEM procedures by considering a sparse-matrix storage format. Finally, two simulations are conducted. A blunt dissection simulation is conducted in real time (less than 20 ms for a time step) using a soft-tissue model having 4807 nodes and 19,600 elements. A brain retraction simulation is conducted using a brain hemisphere model having 8647 nodes and 32,639 elements with force feedback (less than 80 ms for a time step). These results show that the proposed method is effective in simulating dissection and retraction for opening a brain fissure.

Microfluidic chips are powerful tools for biochemical experiments. High speed and precise flow control can be achieved by using microvalves on a chip. Several types of microvalves that can be integrated into a microfluidic chip have been reported. Among them, gel microvalves have certain advantages over other valves because of their soft structure, which will contribute to prevent mechanical damage the cells passing though the valve. Here we use Bioresist, a photoprocessable thermoresponsive gel, as a key component of the microvalve. Since Bioresist is photopatternable, we can create any arbitrary 2D shape from the thermoresponsive gel using photolithography. Moreover, Bioresist has the unique feature of a phase transition around 30°C, and swells and shrinks repeatedly with temperature change. By integrating the patterned thermoresponsive gel with a microheater, we developed a gel actuator and designed a gel-valve. The gel-valve has the advantages of a simple actuation mechanism: high leakage pressure, high speed actuation and low power consumption. The valve is biocompatible and easily integrated into a chip by using conventional photolithography. Using this valve, we achieved on-chip flow control, and applied it to cell sorting on a chip.

Innovative soft robotic grippers, such as granular grippers, enable the automated handling of a wide spectrum of different geometries, increasing the flexibility and robustness of industrial production systems. Granular grippers vary in their design as well as in their configuration, which affects the specific characteristics and capabilities regarding grippable objects. Relevant aspects are the selection of granulates and membranes, as they affect the deformability. This influences the achievable gripping forces, which vary with the gripped objects geometry. On the basis of experimental studies, the modeling of interpolations as well as through experimental validations, the present research investigates the influences of different configurations on the achievable gripping forces for a specific concept of an innovative vacuum-based granular gripper. Specifically, the focus lies on design as well as configuration parameters, which could influence the achievable gripping force. Influencing parameters are determined based on a literature review of similar gripping concepts. Various adjustment possibilities are identified, such as materials of granulates or membranes. The possible configuration options are experimentally analyzed with a one-factor-at-a-time approach. The possibility of modelling the effects of their interrelations on the achievable gripping force is examined with approaches for linear models and compared to interpolations based on Machine Learning. Especially the granulate filling level and the membrane configuration exhibit the largest influences, which were best predicted with the approach based on artificial neural networks. A selection of an optimized gripper configuration for a specified object set as well as possible further developments such as a continuous expandability of the approaches and integrations with simulations are discussed. As a result of these analyses, this research provides methodologies for an optimized selection of a gripper configuration for an improved object-specific achievable gripping force and allows for more efficient handling processes with the examined type of vacuum-based granular gripper.

This paper discusses a force sensing method using a built-in position sensing system for an electrostatic visuo-haptic display. The display provides passive haptic feedback on a flat panel visual monitor, such as LCD, using electrostatic friction modulation via multiple contact pads arranged on a surface-insulated transparent electrode. The display demonstrated in previous studies measured the positions of the pads in a similar manner to surface-capacitive touch-screens. This paper extends the sensor such that the system can monitor the electrostatic interaction force provided to the contact pads. The extension is realized by estimating the capacitance between the contact pads and the display surface. The paper investigates its basic characteristics to show that the force estimation is possible, regardless of the pad positions and the pushing force exerted by users. The force estimation capability is used for feedback control of interaction force, which improves the accuracy of the interaction force. The paper further extends the method such that the system can detect the moving direction of contact pads. By dividing the electrode of a contact pad and comparing their capacitances, the system can detect in which direction the user is trying to move the pad. Such capability is effective for solving the sticky-wall problem, which is known to be a common problem in passive haptic systems. A pilot experiment shows that the proposed system can considerably reduce the sticky-wall effect.

In this paper, we propose a wearable tactile sensor for measuring the shape of micro-undulations on a hard surface. The proposed sensor has two layers. The inner one is a thin rubber layer into which a strain gauge is embedded that is formed around a user’s finger. The outer layer is a flexible structure that consists of numerous pins on a flexible sheet. The shape of micro-undulations on an object surface can be measured when a user wearing the sensor traces the surface. The results of an experiment, in which we compare the cases with and without the flexible structure of the sensor, show that our proposed sensor is sufficiently accurate to measure the shape of micro-undulations due to its flexible structure, which contributes significantly to improving its signal-to-noise ratio.

In laparoscopic surgery, smaller incisions produce good clinical results for patients. Therefore, there is a great need to develop thinner instruments for use in laparoscopic surgery. However, thinner instruments have smaller end effectors that limit the functionality of the instruments. To address this problem, we previously developed a new type of forceps that uses a least-incision transformable end-effector (LITE) mechanism for graspers of two sizes (i.e., a two-way LITE mechanism), which decreases the instrument exchange frequency and the total procedure time during surgery. Robot-assisted surgery is currently receiving considerable attention. However, instrument exchange during robot-assisted surgery is complicated. The purpose of this study was to develop a new two-way LITE forceps that would be suitable for use in robot-assisted surgery and laparoscopic surgery by being attached to a handpiece to reduce the time and difficulty associated with the instrument exchange during robot-assisted surgery. The experimental results show that the proposed forceps can reduce the total instrument exchange time in a simulated robot-assisted surgery environment, generate sufficient grasping forces to serve as a laparoscopic grasper, and perform switching between its small-grasper and large-grasper modes when operated with one hand using the handpiece. An in vivo experiment was performed on a pig under simulated surgery conditions to evaluate the usefulness of the prototype developed in this study. When operated with a motor drive, the forceps was able to grasp the liver using its large grasper.