Vikram Aggarwal

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We are building a multimedia conversation system to facilitate information seeking in large and complex data spaces. To provide tailored responses to diverse user queries introduced during a conversation, we automate the generation of a system response. Here we focus on the problem of determining the data content of a response. Specifically, we develop an(More)
The performance of brain-machine interfaces (BMIs) that continuously control upper limb neuroprostheses may benefit from distinguishing periods of posture and movement so as to prevent inappropriate movement of the prosthesis. Few studies, however, have investigated how decoding behavioral states and detecting the transitions between posture and movement(More)
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 senses of(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)
A visual investigation involves both the examination of existing information and the synthesis of new analytic knowledge. This is a progressive process in which newly synthesized knowledge becomes the foundation for future discovery. In this paper, we present a novel system supporting interactive, progressive synthesis of analytic knowledge. Here we use the(More)
Information seeking is an important but often difficult task, especially when it involves large and complex data sets. We hypothesize that a context-sensitive interaction paradigm would greatly assist users in their information seeking. Such a paradigm would allow users to both express their requests and receive requested information in context. Driven by(More)
To aid users in exploring large and complex data sets, we are building an intelligent multimedia conversation system. Given a user request, our system dynamically creates a multimedia response that is tailored to the interaction context. In this paper, we focus on the problem of media allocation, a process that assigns one or more media, such as graphics or(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)
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)
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)