Learn More
BACKGROUND It has been suggested that Brain-Computer Interfaces (BCI) may one day be suitable for controlling a neuroprosthesis. For closed-loop operation of BCI, a tactile feedback channel that is compatible with neuroprosthetic applications is desired. Operation of an EEG-based BCI using only vibrotactile feedback, a commonly used method to convey haptic(More)
(a) (b) Figure 1: (a) HARVEST allows users to interactively define newly synthesized knowledge. Here, Boynton is derived as a possible high-tech scam. (b) Synthesized knowledge (Pro jectX and Pro jectY , inferred from calendar data) can be dynamically incorporated into the visual exploration environment to enable progressive analysis. ABSTRACT A visual(More)
To examine the spatiotemporal distribution of discriminable information about reach-to-grasp movements in the primary motor cortex upper extremity representation, we implanted four microelectrode arrays in the anterior bank and lip of the central sulcus in each of two monkeys. We used linear discriminant analysis to compare information, quantified as(More)
Together with the obvious increase of elderly patients with end-stage renal disease (ESRD), utilization of peritoneal dialysis (PD) has declined since the mid-1990s in a number of countries--a decline that is particularly marked in this elderly ESRD population. A major obstacle that affects any dialysis modality in elderly patients is the greater disease(More)
Previous research has shown that neuronal activity can be used to continuously decode the kinematics of gross movements involving arm and hand trajectory. However, decoding the kinematics of fine motor movements, such as the manipulation of individual fingers, has not been demonstrated. In this study, single unit activities were recorded from task-related(More)
Individuated finger and wrist movements can be decoded using random subpopulations of neurons that are widely distributed in the primary motor (M1) hand area. This work investigates 1) whether it is possible to decode dexterous finger movements using spatially-constrained volumes of neurons as typically recorded from a microelectrode array; and 2) whether(More)
Previous efforts in brain-machine interfaces (BMI) have looked at decoding movement intent or hand and arm trajectory, but current cortical control strategies have not focused on the decoding of dexterous [corrected] actions such as finger movements. The present work demonstrates the asynchronous decoding (i.e., where cues indicating the onset of movement(More)
Central venous pressure (CVP) is an important physiological parameter, the correct measure of which is a clinically relevant diagnostic tool for heart failure patients. A current challenge for physicians, however, is to obtain a quick and accurate measure of a patient's CVP in a manner that poses minimum discomfort. Current approaches for measuring CVP(More)
We present an optimal method for decoding the activity of primary motor cortex (M1) neurons in a nonhuman primate during single finger movements. The method is based on the maximum-likelihood (ML) inference, which assuming the probability of finger movements is uniform, is equivalent to the maximum a posteriori (MAP) inference. Each neuron's activation is(More)