12,341 research outputs found
Design and Development of an Affordable Haptic Robot with Force-Feedback and Compliant Actuation to Improve Therapy for Patients with Severe Hemiparesis
The study describes the design and development of a single degree-of-freedom haptic robot, Haptic Theradrive, for post-stroke arm rehabilitation for in-home and clinical use. The robot overcomes many of the weaknesses of its predecessor, the TheraDrive system, that used a Logitech steering wheel as the haptic interface for rehabilitation. Although the original TheraDrive system showed success in a pilot study, its wheel was not able to withstand the rigors of use. A new haptic robot was developed that functions as a drop-in replacement for the Logitech wheel. The new robot can apply larger forces in interacting with the patient, thereby extending the functionality of the system to accommodate low-functioning patients. A new software suite offers appreciably more options for tailored and tuned rehabilitation therapies. In addition to describing the design of the hardware and software, the paper presents the results of simulation and experimental case studies examining the system\u27s performance and usability
Human Like Adaptation of Force and Impedance in Stable and Unstable Tasks
Abstract—This paper presents a novel human-like learning con-troller to interact with unknown environments. Strictly derived from the minimization of instability, motion error, and effort, the controller compensates for the disturbance in the environment in interaction tasks by adapting feedforward force and impedance. In contrast with conventional learning controllers, the new controller can deal with unstable situations that are typical of tool use and gradually acquire a desired stability margin. Simulations show that this controller is a good model of human motor adaptation. Robotic implementations further demonstrate its capabilities to optimally adapt interaction with dynamic environments and humans in joint torque controlled robots and variable impedance actuators, with-out requiring interaction force sensing. Index Terms—Feedforward force, human motor control, impedance, robotic control. I
State Variables of the Arm May Be Encoded by Single Neuron Activity in the Monkey Motor Cortex
Revealing the type of information encoded by neurons activity in the motor cortex is essential not only for understanding the mechanism of motion control but also for developing a brain-machine interface. Thus far, the concept of preferred direction vector (PD) has dominated the discussion regarding how neural activity encodes information; however, a unified view of exactly what information is encoded has not yet been established. In the present study, a model was constructed to describe temporal neuron activity by a dot product of the PD and the movement variables vector consisting of joint torque and angular velocity. The plausibility of this model was tested by comparing estimated neural activity with that recorded from the monkey motor cortex, and it was found that this model was able to explain the temporal pattern of neuron activity irrespective of its passive responsiveness. The mean determination coefficients of neurons that responded to proprioceptive stimuli and that responded to visual stimuli were relatively high values of 0.57 and 0.58, respectively. These results suggest that neurons in the monkey motor cortex encode state variables of the arm in a framework of modern control theory and that this information could be decoded for controlling a brain-machine interface
Effect of Tendon Vibration on Hemiparetic Arm Stability in Unstable Workspaces
Sensory stimulation of wrist musculature can enhance stability in the proximal arm and may be a useful therapy aimed at improving arm control post-stroke. Specifically, our prior research indicates tendon vibration can enhance stability during point-to-point arm movements and in tracking tasks. The goal of the present study was to investigate the influence of forearm tendon vibration on endpoint stability, measured at the hand, immediately following forward arm movements in an unstable environment. Both proximal and distal workspaces were tested. Ten hemiparetic stroke subjects and 5 healthy controls made forward arm movements while grasping the handle of a two-joint robotic arm. At the end of each movement, the robot applied destabilizing forces. During some trials, 70 Hz vibration was applied to the forearm flexor muscle tendons. 70 Hz was used as the stimulus frequency as it lies within the range of optimal frequencies that activate the muscle spindles at the highest response rate. Endpoint position, velocity, muscle activity and grip force data were compared before, during and after vibration. Stability at the endpoint was quantified as the magnitude of oscillation about the target position, calculated from the power of the tangential velocity data. Prior to vibration, subjects produced unstable, oscillating hand movements about the target location due to the applied force field. Stability increased during vibration, as evidenced by decreased oscillation in hand tangential velocity
Collision Detection and Reaction: A Contribution to Safe Physical Human-Robot Interaction
In the framework of physical Human-Robot Interaction
(pHRI), methodologies and experimental tests are
presented for the problem of detecting and reacting to collisions
between a robot manipulator and a human being. Using a
lightweight robot that was especially designed for interactive
and cooperative tasks, we show how reactive control strategies
can significantly contribute to ensuring safety to the human
during physical interaction. Several collision tests were carried
out, illustrating the feasibility and effectiveness of the proposed
approach. While a subjective “safety” feeling is experienced by
users when being able to naturally stop the robot in autonomous
motion, a quantitative analysis of different reaction strategies
was lacking. In order to compare these strategies on an objective
basis, a mechanical verification platform has been built. The
proposed collision detection and reactions methods prove to
work very reliably and are effective in reducing contact forces
far below any level which is dangerous to humans. Evaluations
of impacts between robot and human arm or chest up to a
maximum robot velocity of 2.7 m/s are presented
Robotic tele-existence
Tele-existence is an advanced type of teleoperation system that enables a human operator at the controls to perform remote manipulation tasks dexterously with the feeling that he or she exists in the remote anthropomorphic robot in the remote environment. The concept of a tele-existence is presented, the principle of the tele-existence display method is explained, some of the prototype systems are described, and its space application is discussed
The separate neural control of hand movements and contact forces
To manipulate an object, we must simultaneously control the contact forces exerted on the object and the movements of our hand. Two alternative views for manipulation have been proposed: one in which motions and contact forces are represented and controlled by separate neural processes, and one in which motions and forces are controlled jointly, by a single process. To evaluate these alternatives, we designed three tasks in which subjects maintained a specified contact force while their hand was moved by a robotic manipulandum. The prescribed contact force and hand motions were selected in each task to induce the subject to attain one of three goals: (1) exerting a regulated contact force, (2) tracking the motion of the manipulandum, and (3) attaining both force and motion goals concurrently. By comparing subjects' performances in these three tasks, we found that behavior was captured by the summed actions of two independent control systems: one applying the desired force, and the other guiding the hand along the predicted path of the manipulandum. Furthermore, the application of transcranial magnetic stimulation impulses to the posterior parietal cortex selectively disrupted the control of motion but did not affect the regulation of static contact force. Together, these findings are consistent with the view that manipulation of objects is performed by independent brain control of hand motions and interaction forces
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