BME Lecture Series: A. Bolu Ajiboye, Case Western Reserve University
Department of Biomedical Engineering
Case Western Reserve University
Abstract: Cortically controlled neuroprostheses have long been posited as the holy grail for intracortical brain-computer-interfaces (iBCIs). The efficacy of iBCIs has advanced to the point where a small number of laboratories around the U.S. are now involved in iBCI trials involving humans with chronic paralysis. As part of the Braingate2 Clinical Trial, we at Case Western Reserve University are investigating using iBCIs to control functional electrical stimulation (FES) systems for restoring functional arm movements to persons with chronic high cervical spinal cord injury. This lecture will highlight a number of our clinical, technological and scientific advances toward developing an iBCI-controlled FES arm neuroprosthesis. Additionally, this lecture will discuss the efficacy of non-microelectrode recording techniques for extracting movement-related information from cortical signals. Specifically, we have used arrays of DBS-style depth electrodes to record from cortical areas not accessible by traditional microelectrode or electrocorticography arrays, such as deep within sulci walls of primary (M1), dorsal premotor (PMd), and insular cortices. We show grasp-related cortical modulation useful for control of hand neuroprostheses. Finally, this lecture will briefly discuss hurdles with the development of chronically implanted clinically viable iBCI neuroprosthetic systems.
Bio: A. Bolu Ajiboye is an assistant professor of biomedical engineering at Case Western Reserve University. He also holds an appointment as a biomedical engineering scientist at the Louis Stokes Cleveland VA Medical Center. Ajiboye’s main research interest is in the development and control of brain-computer-interface (BCI) neuroprosthetic technologies for restoring function to individuals who have experienced severely debilitating injuries to the nervous system, such as spinal cord injury and stroke. Currently, he is interested in understanding at a systems level the relationships between the firing patterns of multineuronal networks and the kinetic (muscle activity and force) and kinematic (limb position and velocity) outputs of these neural systems in the control of upper-limb movements. The end goal of his research is to develop BCI systems that allow for more natural interactions with one’s surrounding environment and more natural control of assistive technologies, such as artificial limbs and FES-based systems. Additionally, his research focuses on understanding natural muscle coordination patterns involved in motor coordination, and how these patterns can be used in neuroprosthetic systems to restore lost or compromised function through FES.