Brian Wodlinger

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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)
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)
OBJECTIVE In a previous study we demonstrated continuous translation, orientation and one-dimensional grasping control of a prosthetic limb (seven degrees of freedom) by a human subject with tetraplegia using a brain-machine interface (BMI). The current study, in the same subject, immediately followed the previous work and expanded the scope of the control(More)
CONTEXT Spinal cord injury (SCI) results in a loss of function and sensation below the level of the lesion. Neuroprosthetic technology has been developed to help restore motor and autonomic functions as well as to provide sensory feedback. FINDINGS This paper provides an overview of neuroprosthetic technology that aims to address the priorities for(More)
The ability to recover signals from the peripheral nerves would provide natural and physiological signals for controlling artificial limbs and neural prosthetic devices. Current cuff electrode systems can provide multiple channels but the signals have low signal to noise ratio and are difficult to recover. Previous work has shown that beamforming algorithms(More)
The peripheral nervous system carries sensory and motor information that could be useful as command signals for function restoration in areas such as neural prosthetics and functional electrical stimulation (FES). Nerve cuff electrodes provide a robust and safe technique for recording nerve signals. However, a method to separate and recover signals from(More)
The peripheral nerves of an amputee's residual limb still carry the information required to provide the robust, natural control signals needed to command a dexterous prosthetic limb. However, these signals are mixed in the volume conductor of the body and extracting them is an unmet challenge. A beamforming algorithm was used to leverage the spatial(More)
Our research group recently demonstrated that a person with tetraplegia could use a brain-computer interface (BCI) to control a sophisticated anthropomorphic robotic arm with skill and speed approaching that of an able-bodied person. This multiyear study exemplifies important principles in translating research from foundational theory and animal experiments(More)
OBJECTIVES Pain due to peripheral neuropathy is extremely difficult to treat as drugs often become less and less effective over the course of a patient's life. In order to augment such treatments, electrical stimulation has become relatively common, in the form of transcutaneous electrical nerve stimulation, peripheral nerve stimulation, and spinal cord(More)
In order to take full advantage of modern multiple-degree of freedom prosthetic limbs, robust and natural control signals are needed. Previous work has shown that beamforming provides a method to extract such signals from peripheral nerve activity [1]. This paper describes in vivo experiments done to validate that method in a more realistic case. A(More)