Learn More
Tactile sensation is critical for effective object manipulation, but current prosthetic upper limbs make no provision for delivering somesthetic feedback to the user. For individuals who require use of prosthetic limbs, this lack of feedback transforms a mundane task into one that requires extreme concentration and effort. Although vibrotactile motors and(More)
207 their natural limb. In Phase 1, the leveraging of COTS products coupled with prototypical technology development was demonstrated in the 7-degree-of-freedom (DOF) Prototype 1 system, which was fully patient tested in a clinical environment using noninvasive neural integration strategies. Prototype 2 improved upon this technological foundation to(More)
OBJECTIVE We used native sensorimotor representations of fingers in a brain-machine interface (BMI) to achieve immediate online control of individual prosthetic fingers. APPROACH Using high gamma responses recorded with a high-density electrocorticography (ECoG) array, we rapidly mapped the functional anatomy of cued finger movements. We used these(More)
To increase the ability of brain-machine interfaces (BMIs) to control advanced prostheses such as the modular prosthetic limb (MPL), we are developing a novel system: the Hybrid Augmented Reality Multimodal Operation Neural Integration Environment (HARMONIE). This system utilizes hybrid input, supervisory control, and intelligent robotics to allow users to(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)
— Existing brain-computer interface (BCI) control of highly dexterous robotic manipulators and prosthetic devices typically rely solely on neural decode algorithms to determine the user's intended motion. Although these approaches have made significant progress in the ability to control high degree of freedom (DOF) manipulators, the ability to perform(More)
— Effective user control of highly dexterous and robotic assistive devices requires intuitive and natural modalities. Although surgically implanted brain-computer interfaces (BCIs) strive to achieve this, a number of non-invasive engineering solutions may provide a quicker path to patient use by eliminating surgical implantation. We present the development(More)
We present a micropatterning method for the automatic transfer and arbitrary positioning of computer-generated three-dimensional structures within a substrate. The Gerchberg-Saxton algorithm and an electrically addressed spatial light modulator (SLM) are used to create and display phase holograms, respectively. A holographic approach to light manipulation(More)
Intracranial electroencephalographic (iEEG) signals from two human subjects were used to achieve simultaneous neural control of reaching and grasping movements with the Johns Hopkins University Applied Physics Lab (JHU/APL) Modular Prosthetic Limb (MPL), a dexterous robotic prosthetic arm. We performed functional mapping of high gamma activity while the(More)
The ability of robotic systems to effectively address disaster scenarios that are potentially dangerous for human operators is continuing to grow as a research and development field. This leverages research from areas such as bimanual manipulation, dexterous grasping, bipedal locomotion, computer vision, sensing, object segmentation, varying degrees of(More)