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This work is part of an ongoing effort to explore a new mode of intervention for children at risk of cerebral palsy. The intervention uses an autonomous mobile robot that recognizes crawling like movements to respond to the infant. We propose a new system to capture crawling motions of infants. Our methodology involves placing planar marker patterns on the body and tracking them using cameras. A single...
Electroencephalography has been studied to understand various brain functions. These functions can be related to their frequency and spatial patterns. These properties are relatively unknown in infants. The first year of life includes stages of significant growth neurologically and behaviorally. The present study is aimed to investigate infant brain development using high-density EEG(124 channel)...
Crawling is an important milestone in infant motor development. However, infants with developmental motor disorders can exhibit delays, or even miss, in the acquisition of crawling skill. And little information is available from the neurodevelopmental domain about the changes in brain function with intervention. The mu rhythm can potentially play a substantial role in understanding human motor development...
Rhythmic activities in electroencephalography (EEG) have been extensively studied in adults and classic rhythms are found to correlate with specific human brain functions. However, less has been investigated in infant EEG, and EEG rhythms in infants at early ages have not been well characterized in terms of their frequency ranges. In the present pilot study, we investigated rhythmic activities in...
Observing an action being performed and executing the same action cause similar patterns of neural activity to emerge in the primary motor cortex (MI). Previous work has shown that the neural activity evoked during action observation (AO) is informative as to both the kinematics and muscle activation patterns of the action being performed, although the neural activity recorded during action observation...
Operant conditioning with biofeedback has been shown to be an effective method to modify neural activity to generate goal-directed actions in a brain-machine interface. It is particularly useful when neural activity cannot be mathematically mapped to motor actions of the actual body such as in the case of amputation. Here, we implement an operant conditioning approach with visual feedback in which...
Traditional brain machine interfaces for control of a prosthesis have typically focused on the kinematics of movement, rather than the dynamics. BMI decoders that extract the forces and/or torques to be applied by a prosthesis have the potential for giving the patient a much richer level of control across different dynamic scenarios or even scenarios in which the dynamics of the limb/environment are...
We present a method for predicting action outcomes in unstructured environments with variable numbers of participants and hidden relationships between them. For example, when pouring flour from a cup into a mixing bowl, important relations must exist between the cup and the bowl. The action Pour(x, y) might depend on the precondition Above(x, y). How well the predicate Above actually predicts action...
Typically, brain-machine interfaces that enable the control of a prosthetic arm work by decoding a subjects' intended hand position or velocity and using a controller to move the arm accordingly. Researchers taking this approach often choose to decode the subjects' desired arm state in the present moment, which causes the prosthetic arm to lag behind the state desired by the user, as the dynamics...
Although most brain-machine interface (BMI) studies have focused on decoding kinematic parameters of motion, it is known that motor cortical activity also correlates with kinetic signals, including hand force and joint torque. In this experiment, a monkey used a cortically-controlled BMI to move a visual cursor and hit a sequence of randomly placed targets. By varying the contributions of separate...
This paper addresses the problem of designing a practical system able to grasp real objects with a three-fingered robot hand. A general approach for synthesizing two- and three-finger grasps on planar unknown objects is presented. Visual perception is used to reduce the uncertainty and to obtain relevant information about the objects.We focus on non-modeled planar extruded objects, which can represent...
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