191 research outputs found

    Optimal dimensional synthesis of force feedback lower arm exoskeletons

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    This paper presents multi-criteria design optimization of parallel mechanism based force feedback exoskeletons for human forearm and wrist. The optimized devices are aimed to be employed as a high fidelity haptic interfaces. Multiple design objectives are discussed and classified for the devices and the optimization problem to study the trade-offs between these criteria is formulated. Dimensional syntheses are performed for optimal global kinematic and dynamic performance, utilizing a Pareto front based framework, for two spherical parallel mechanisms that satisfy the ergonomic necessities of a human forearm and wrist. Two optimized mechanisms are compared and discussed in the light of multiple design criteria. Finally, kinematic structure and dimensions of an optimal exoskeleton are decided

    sEMG-based natural control interface for a variable stiffness transradial hand prosthesis

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    We propose, implement, and evaluate a natural human-machine control interface for a variable stiffness transradial hand prosthesis that achieves tele-impedance control through surface electromyography (sEMG) signals. This interface, together with variable stiffness actuation (VSA), enables an amputee to modulate the impedance of the prosthetic limb to properly match the requirements of a task while performing activities of daily living (ADL). Both the desired position and stiffness references are estimated through sEMG signals and used to control the VSA hand prosthesis. In particular, regulation of hand impedance is managed through the impedance measurements of the intact upper arm; this control takes place naturally and automatically as the amputee interacts with the environment, while the position of the hand prosthesis is regulated intentionally by the amputee through the estimated position of the shoulder. The proposed approach is advantageous since the impedance regulation takes place naturally without requiring amputees' attention and diminishing their functional capability. Consequently, the proposed interface is easy to use, does not require long training periods or interferes with the control of intact body segments. This control approach is evaluated through human subject experiments conducted over able volunteers where adequate estimation of references and independent control of position and stiffness are demonstrated.Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) ; 219M58

    Design, implementation, and evaluation of a variable stiffness transradial hand prosthesis

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    We present the design, implementation, and experimental evaluation of a low-cost, customizable, easy-to-use transradial hand prosthesis capable of adapting its compliance. Variable stiffness actuation (VSA) of the prosthesis is based on antagonistically arranged tendons coupled to nonlinear springs driven through a Bowden cable based power transmission. Bowden cable based antagonistic VSA can, not only regulate the stiffness and the position of the prosthetic hand but also enables a light-weight and low-cost design, by the opportunistic placement of motors, batteries, and controllers on any convenient location on the human body, while nonlinear springs are conveniently integrated inside the forearm. The transradial hand prosthesis also features tendon driven underactuated compliant fingers that allow natural adaption of the hand shape to wrap around a wide variety of object geometries, while the modulation of the stiffness of their drive tendons enables the prosthesis to perform various tasks with high dexterity. The compliant fingers of the prosthesis add inherent robustness and flexibility, even under impacts. The control of the variable stiffness transradial hand prosthesis is achieved by an sEMG based natural human-machine interface

    Detection of intention level in response to task difficulty from EEG signals

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    We present an approach that enables detecting intention levels of subjects in response to task difficulty utilizing an electroencephalogram (EEG) based brain-computer interface (BCI). In particular, we use linear discriminant analysis (LDA) to classify event-related synchronization (ERS) and desynchronization (ERD) patterns associated with right elbow flexion and extension movements, while lifting different weights. We observe that it is possible to classify tasks of varying difficulty based on EEG signals. Additionally, we also present a correlation analysis between intention levels detected from EEG and surface electromyogram (sEMG) signals. Our experimental results suggest that it is possible to extract the intention level information from EEG signals in response to task difficulty and indicate some level of correlation between EEG and EMG. With a view towards detecting patients' intention levels during rehabilitation therapies, the proposed approach has the potential to ensure active involvement of patients throughout exercise routines and increase the efficacy of robot assisted therapies

    Development of a micromanipulation system with force sensing

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    This article provides in-depth knowledge about our undergoing effort to develop an open architecture micromanipulation system with force sensing capabilities. The major requirement to perform any micromanipulation task effectively is to ensure the controlled motion of actuators within nanometer accuracy with low overshoot even under the influence of disturbances. Moreover, to achieve high dexterity in manipulation, control of the interaction forces is required. In micromanipulation, control of interaction forces necessitates force sensing in milli-Newton range with nano-Newton resolution. In this paper, we present a position controller based on a discrete time sliding mode control architecture along with a disturbance observer. Experimental verifications for this controller are demonstrated for 100, 50 and 10 nanometer step inputs applied to PZT stages. Our results indicate that position tracking accuracies up to 10 nanometers, without any overshoot and low steady state error are achievable. Furthermore, the paper includes experimental verification of force sensing within nano-Newton resolution using a piezoresistive cantilever endeffector. Experimental results are compared to the theoretical estimates of the change in attractive forces as a function of decreasing distance and of the pull off force between a silicon tip and a glass surface, respectively. Good agreement among the experimental data and the theoretical estimates has been demonstrated

    Gravity-Assist: a series elastic body weight support system with inertia compensation

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    We present GRAVITY-ASSIST, a series elastic active body weight support and inertia compensation system for use in robot assisted gait rehabilitation. The device consists of a single degree of freedom series elastic actuator that connects to the trunk of a patient. The series elastic system is novel in that, it can provide the desired level of dynamic unloading such that the patient experiences only a percentage of his/her weight and inertia. Inertia compensation is important, since the inertial forces can cause significant deviations from the desired unloading force, specially at low support forces and fast walking speeds. Furthermore, this feature enables the inertia of the harness and force sensing unit attached to the patient to be compensated for, making sure that the device does not interfere with the natural gait cycle. We present a functional prototype of the device, its characterization and experimental verification of the approach

    Convex multi-criteria design optimization of robotic manipulators via sum-of-squares programming

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    This paper presents a general framework for optimization of robotic manipulators via sums-of-squares (SoS) programming (semidefinite convex optimization) with multiple design objectives. Both kinematic and dynamic performance measures are discussed and an optimization problem for a proof-of-concept robotic manipulator has been formulated. SoS programming is shown to promise advantages as it can provide globally optimal results up to machine precision and scales much better with respect to the number of design variables than other methods which can obtain globally optimal solutions

    MRI-VisAct: a Bowden cable-driven MRI compatible series viscoelastic actuator

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    Presence of the strong magnetic fields in the Magnetic Resonance Imaging (MRI) environment limits the integration of robotic rehabilitation systems to the MRI process. The tendency to improve imaging quality by the amplification of magnetic field strength further tightens the bidirectional compatibility constraints on MRI compatible rehabilitation devices. We present the design, control, and characterization of MRI-VisAct—a low-cost, Bowden cable-actuated rotary series viscoelastic actuator that fulfills the bidirectional compatibility requirements to the maximum extend. Components of MRI-VisAct that are placed in the magnet room are built using nonconductive, diamagnetic MRI compatible materials, while ferromagnetic/paramagnetic components are placed in the control room, located outside the MRI room. Power and data transmission are achieved through Bowden-cables and fiber optics, respectively. This arrangement ensures that neuroimaging artifacts are minimized, while safety hazards are eliminated, and the device performance is not affected by the magnetic field. MRIVisAct works under closed-loop torque control enabled through series viscoelastic actuation. MRI-VisAct is fully customizable; it can serve as the building block of higher degrees of freedom MRI compatible robotic devices

    Brain computer interface based robotic rehabilitation with online modification of task speed

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    We present a systematic approach that enables online modification/adaptation of robot assisted rehabilitation exercises by continuously monitoring intention levels of patients utilizing an electroencephalogram (EEG) based Brain-Computer Interface (BCI). In particular, we use Linear Discriminant Analysis (LDA) to classify event-related synchronization (ERS) and desynchronization (ERD) patterns associated with motor imagery; however, instead of providing a binary classification output, we utilize posterior probabilities extracted from LDA classifier as the continuous-valued outputs to control a rehabilitation robot. Passive velocity field control (PVFC) is used as the underlying robot controller to map instantaneous levels of motor imagery during the movement to the speed of contour following tasks. In other words, PVFC changes the speed of contour following tasks with respect to intention levels of motor imagery. PVFC also allows decoupling of the task and the speed of the task from each other, and ensures coupled stability of the overall robot patient system. The proposed framework is implemented on AssistOn-Mobile - a series elastic actuator based on a holonomic mobile platform, and feasibility studies with healthy volunteers have been conducted test effectiveness of the proposed approach. Giving patients online control over the speed of the task, the proposed approach ensures active involvement of patients throughout exercise routines and has the potential to increase the efficacy of robot assisted therapies

    Design and control of an MRI compatible series elastic actuator

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    Bidirectional compatibility requirements with Magnetic Resonance Imaging (MRI) have limited the adaptation of rehabilitation robots for use in MRI machines. In this paper, we present the design and control of a Bowden cable-actuated, MRI-compatible series elastic actuator (SEA) that aims to fulfil the bidirectional compatibility requirements to the maximum extend. The proposed device is built using nonconductive diamagnetic MRI compatible materials, fiber optic sensing units and a Bowden cable based actuation, such that imaging artifacts created under strong magnetic field required for neuro-imaging are minimized. In particular, utilization of Bowden-cable transmission enables the placement of the conventional non-MRI compatible control/signal processing units and electric actuators outside the MRI room. This approach not only helps avoid the MR interference caused by these parts and eliminates safety hazards within the MRI room, but also ensures that the performance of the device is not affected by the strong magnetic field, resulting in ideal bidirectional MRI compatibility. Use of a custom-built fiber optic encoder together with nonconductive leaf spring based elastic element enables torque outputs of the device to be measured and used for closed-loop torque control, rendering the system into a series elastic actuator. The proposed MRI compatible SEA is easily customizable and can be used as the building block of higher degrees of freedom MRI compatible robotic devices. Current prototype is validated to administer continuous torques up to 2 Nm with a torque control bandwidth of 1 Hz and a torque sensing resolution of 0.05 Nm
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