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BACKGROUND Paralysis or amputation of an arm results in the loss of the ability to orient the hand and grasp, manipulate, and carry objects, functions that are essential for activities of daily living. Brain-machine interfaces could provide a solution to restoring many of these lost functions. We therefore tested whether an individual with tetraplegia could(More)
Sensorimotor control is greatly affected by two factors--the time it takes for an animal to sense and respond to stimuli (responsiveness), and the ability of an animal to distinguish between sensory stimuli and generate graded muscle forces (resolution). Here, we demonstrate that anatomical limitations force a necessary trade-off between responsiveness and(More)
Brain-computer interface (BCI) technology aims to help individuals with disability to control assistive devices and reanimate paralyzed limbs. Our study investigated the feasibility of an electrocorticography (ECoG)-based BCI system in an individual with tetraplegia caused by C4 level spinal cord injury. ECoG signals were recorded with a high-density(More)
This article reviews neural interface technology and its relationship with neuroplasticity. Two types of neural interface technology are reviewed, highlighting specific technologies that the authors directly work with: (1) neural interface technology for neural recording, such as the micro-ECoG BCI system for hand prosthesis control, and the comprehensive(More)
During reaching to grasp objects with different shapes hand posture is molded gradually to the object's contours. The present study examined the extent to which the temporal evolution of hand posture depends on continuous visual feedback. We asked subjects to reach and grasp objects with different shapes under five vision conditions (VCs). Subjects wore(More)
Magnetoencephalography (MEG) enables a noninvasive interface with the brain that is potentially capable of providing movement-related information similar to that obtained using more invasive neural recording techniques. Previous studies have shown that movement direction can be decoded from multichannel MEG signals recorded in humans performing wrist(More)
A major issue to be addressed in the development of neural interfaces for prosthetic control is the need for somatosensory feedback. Here, we investigate two possible strategies: electrical stimulation of either dorsal root ganglia (DRG) or primary somatosensory cortex (S1). In each approach, we must determine a model that reflects the representation of(More)
Sensory feedback is required by biological motor control systems to maintain stability, respond to perturbations, and adapt. Similarly, motor neuroprostheses require feedback to provide natural and complete restoration of motor functions. In this paper, we show that ensemble firing rates from the body's mechanoreceptors can provide a natural source of(More)
State-of-the-art upper extremity prostheses include anthropomorphic hands with dexterity that approximates that of a human. To be fully useful, these devices will require an advanced somatosensory neural interface to convey tactile and proprioceptive feedback to the user. To this end, microstimulation methods are being developed using microelectrode arrays(More)
This paper demonstrates a synergy-based brain-machine interface that uses low-dimensional command signals to control a high dimensional virtual hand. First, temporal postural synergies were extracted from the angular velocities of finger joints of five healthy subjects when they performed hand movements that were similar to activities of daily living. Two(More)