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Human levels of dexterity has not been duplicated in a robotic form to date. Dexterity is achieved in part due to the biomechanical structure, and in part due to the neural control of movement. An anatomically correct test-bed (ACT) hand has been constructed to investigate the importance and behavioral consequences of anatomical features and neural control strategies of the human hand. This paper...
When real objects are used in therapy their presence affects movement kinematics and hence the trajectories themselves. We examine the effectiveness of a trajectory planning algorithm to model the natural curving wrist movements observed in real life functional tasks. The fifth order minimum jerk model that incorporates curvature is used as a starting point for the model. The model was further developed...
A number of decoding methods, varying from common linear Gaussian models to more complicated point process frameworks, have been developed to infer hand movement from neuronal firing activity in the motor cortex. Most of these methods focus on estimating subjectpsilas hand trajectory in a continuous movement. We recently proposed a template-based time identification decoding approach and showed that...
In this paper, we propose a new method to make a quantitative evaluation of motor commands based on the EMG signals. Especially, we tried to resolve a remaining issue in our previous study: relatively poor estimation of the wrist joint torque from the EMG signals for extreme movements, such as jerky movements of the cerebellar patients. Subjects included eight cerebellar patients and eight normal...
This paper reports the preliminary results of a research effort aiming at conceptualizing novel insect/machine hybrid controllers for autonomous exploratory vehicles. In particular, we investigate the possibility to include pre-developed animal intelligence capable of sensory-motor integration, decision-making and learning behaviors. In this context we present an in-depth review of insect neurophysiology...
In this paper we present a method to make cells magnetotactic by using carbon nanotubes (CNTs). The key of the method consists of a highly biocompatible dispersion of CNTs. These CNTs, once added to culture medium of neuroblastoma cells, strongly interact with the cell membrane. CNTs-conjugated cells appear to be sensitive to applied magnetic field gradient and move towards the magnetic source. A...
Previously a Kalman filter has been developed to estimate joint angle of the tremulous upper limb using data from accelerometer (ACC) and surface electromyography (sEMG). Results have shown that the fused information can be useful for actively compensating the tremor and helping the clinicians in tremor diagnostics. In this paper, an improvement for the current algorithm is proposed by implementing...
Neurosurgery was the first field of application for robots in interventional medicine 20 years ago, and since then dozens of research projects have been focusing on brain and spine surgery, differently addressing the challenges of accuracy and effectiveness. We have developed a cooperatively-controlled system to assist with skull base drilling, to improve the safety and quality of neurosurgery while...
This paper presents a novel design for a 4 degree of freedom pneumatically-actuated upper-limb rehabilitation device. BONES is based on a parallel mechanism that actuates the upper arm by means of two passive, sliding rods pivoting with respect to a fixed structural frame. Four, mechanically-grounded pneumatic actuators are placed behind the main structural frame to control shoulder motion via the...
The present study is aimed at developing new rehabilitation protocols to be used in post-stroke robotic-aided therapy. In the recent past, it has been suggested that the use of robotic training forces that enhance error instead of reducing it, could stimulate new learning and feedback strategies at the base of an effective motor recovery. Starting from these findings, in this work two different robotic-aided...
Previous demonstrations of brain-machine interfaces have shown the potential for controlling a neuroprosthesis under pure motion control, i.e. predicting end effector kinematics from neural ensemble activity. For real world tasks, however, pure motion control lacks the information required for versatile manipulation in which the dynamic interactions of forces and torques between the musculoskeletal...
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