Doctor of Philosophy, Case Western Reserve University, 2020, Biomedical Engineering

Over one million individuals in the United States have a lower-limb amputation. Though locomotion is a sensorimotor process, no commercially available prostheses offer somatosensory feedback, and amputees continue to face locomotor challenges. Recent studies have demonstrated that electrically stimulating the residual nerves of amputees can elicit somatosensory percepts referred to the missing limb. Though peripheral nerve stimulation (PNS) takes advantage of the existing neural pathways that carry sensory information from the amputated limb to the brain, neural stimulation does not activate these afferent fibers in the same manner as physically-applied tactile stimuli. We hypothesized that these differences in neural activation may cause PNS-evoked sensation to be perceived differently than natural touch with respect to temporal synchrony and multisensory integration. In Aim 1, we found that the processing time and temporal sensitivity were not different between PNS-evoked and natural somatosensation. The similarity in visuotactile synchrony provided further evidence that PNS-evoked sensations are processed in broadly the same way as natural touch. In Aim 2, we established that much like natural somatosensation, vision and postural manipulations could reinforce PNS-evoked somatosensation. This multisensory integration had not been previously demonstrated and it is important for sensory neuroprostheses, which will be used in diverse environments with various sensory resources. The findings from Aims 1-2 demonstrated that PNS-evoked and natural somatosensation have similar properties, but did not guarantee that the body would utilize the sensory information accordingly. In Aim 3, we showed that amputees utilized PNS-evoked plantar sensation while performing a challenging locomotor task, revealing a significant and immediate benefit of somatosensory feedback to amputees. The use of a sensory-enabled prosthesis did not change the amputees' locomotor strategies, (open full item for complete abstract)

Committee: Ronald Triolo (Advisor); Dustin Tyler (Committee Chair); Bolu Ajiboye (Committee Member); Cenk Cavusoglu (Committee Member) Subjects: Biomedical Engineering

Doctor of Philosophy, Case Western Reserve University, 2020, Biomedical Engineering

The objective of this project was to explore the use of myoelectric signals generated from muscles below the SCI level as command sources for a neuroprosthetic system. Using functional electrical stimulation, motor neuroprostheses can restore function after paralysis caused by spinal cord injury (SCI). Command signals derived from the user's volitional intent are required to control these devices. In current systems, command is provided by myoelectric activity from muscles above the injury level. For improved functional capabilities, advanced neuroprosthetic technology demands more command signals than are conventionally available. Previous studies suggest that axonal sparing is common even in injuries diagnosed as motor complete, in which no visible signs of muscle activity below the injury are observed. As a result of this sparing, it is possible, even in the absence of visible movement, for movement attempts to produce myoelectric activity detectable via electromyographic (EMG) sensors. This myoelectric activity could provide an innovative source for neuroprosthetic control. To characterize the prevalence of this activity, surface EMG recordings from lower-extremity muscles were performed during volitional movement attempts in individuals with motor-complete SCI. Significant below-injury muscle activity was identified in the majority of participants, with a smaller proportion producing high-quality signals which we theorized capable of providing neuroprosthetic control. To support this theory, as a proof-of-concept we demonstrated the successful control of an implanted hand grasp neuroprosthesis via EMG signals from the participant's toe flexor. This feasibility test, which included functional grasp measures, demonstrates the potential for below-injury signals to provide a novel form of neuroprosthesis control. Lastly, we implemented a biofeedback training protocol with the goal of improving signal quality from muscles which contained significant, but no (open full item for complete abstract)

Committee: P. Hunter Peckham PhD (Advisor); A. Bolu Ajiboye PhD (Committee Chair); Kevin Kilgore PhD (Committee Member); Warren Alilain PhD (Committee Member); Michael Keith MD (Committee Member) Subjects: Biomedical Engineering

Master of Sciences (Engineering), Case Western Reserve University, 2019, EMC - Mechanical Engineering

This thesis details the design and preliminary testing of a low-passive-friction motorized knee brace for use in a hybrid neuroprosthesis (HNP). This device is specifically intended to assist walking in hemiparetic stroke survivors. The brace design incorporates a Maxon 100W brushless motor, a Harmonic Drive 50:1 gearbox, a Thomson brake, and spur gear transmission; human interface components; sensors to record gait data; and electronic and control systems. Bench testing measured the brace passive resistance, the torque required to move the device while it is unpowered. The passive resistance ranged from 8% to 16% of the desired peak torque of 25 N-m. Preliminary human testing evaluated the device on one able-bodied individual. The device was tested in passive mode without power applied to the motor and in friction-compensated mode with power applied to account for velocity based friction. The friction compensation controller accounted for kinetic friction and improved range of motion.

Committee: Roger Quinn PhD (Advisor); Nathaniel Makowski PhD (Committee Chair); Kathryn Daltorio PhD (Committee Member); Kiju Lee PhD (Committee Member); Rudolf Kobetic (Other); Mark Nandor (Other) Subjects: Biomechanics; Biomedical Research; Mechanical Engineering

Doctor of Philosophy, Case Western Reserve University, 2015, EECS - Electrical Engineering

A stimulus artifact rejection (SAR) system has been developed for performing artifact removal from contaminated neural data in real time (i.e., as the recording is taking place). The SAR algorithm is first developed for hardware implementation and prototyped in a field-programmable gate array (FPGA) platform. The design is then implemented in AMS 0.35µm two-poly four-metal (2P/4M) CMOS technology and integrated with neural-recording and microstimulation circuitry into a 3.1 × 3.1-mm2 chip to create a functional, standalone neural interface microsystem with recording, stimulation, and real-time SAR capability. The SAR algorithm along with its system- and circuit-level architecture, as well as experimental results from benchtop and neurobiological testing of the neural interface microsystem are presented and discussed.

Committee: Pedram Mohseni (Committee Chair); Hillel Chiel (Committee Member); Marc Buchner (Committee Member); Swarup Bhunia (Committee Member) Subjects: Electrical Engineering

Doctor of Philosophy, Case Western Reserve University, 2015, Biomedical Engineering

The overall goal of this work is to optimize nerve cuff stimulation for selective activation of upper extremity nerves. The characterization of upper extremity nerve dimensions is important for electrode design development. Quantitative measures such as nerve diameter, number of fascicles, and fascicle diameters were used to guide neural electrode dimensions. The quantitative upper extremity measurements were used as a template to create upper extremity simulation models. We constructed physiologically based Finite Element Method (FEM) models of nerve cuff electrodes at low, moderate, and high contact densities at 16 nerve locations in median, ulnar, and radial nerves. We hypothesize that adding two flanking anodes to an active cathode is sufficient for optimal selectivity of fascicles in upper extremity nerves. We exhaustively tested one and two channel configurations, as well as, all three channel configuration within six contacts. Since the number of permutations of stimulation parameters increases exponentially by adding anodes, a genetic algorithm search routine was employed. Seventy-nine percent of all fascicles were selectively activated with high density electrodes and multiple channel stimulation. Only 2.5% of selective fascicles required more than 2 anodes in the stimulation configuration. The important implication of this work is that optimal system design requires high density nerve cuff electrodes, but no more than four simultaneously active stimulation channels routed through a multiplexor. We tested the capabilities of a high density electrode with multipolar stimulation in non-human primate upper extremity nerves. A high density Composite Flat Interface Nerve Electrode (CFINE) was implanted chronically in a non-human primate on the median, radial, and ulnar nerves. Electromyography (EMG) recordings were used to optimize nerve stimulation parameters to increase selective muscle activation of the hand and arm muscles using high density nerve cuf (open full item for complete abstract)

Committee: Dustin Tyler Ph.D. (Advisor); Robert Kirsch Ph.D. (Committee Member); Kevin Kilgore Ph.D. (Committee Member); Vira Chankong Ph.D. (Committee Member) Subjects: Biomedical Engineering

Doctor of Philosophy, Case Western Reserve University, 2008, Biomedical Engineering

Functional Electrical Stimulation (FES) has been used to restore upper extremity function in individuals with C5/C6 level of spinal cord injury (SCI). Neuroprostheses for this SCI population typically restore hand grasp. In their shoulder and elbow, these individuals have a combination of voluntary, denervated and paralyzed muscles that reduces their workspace and forces them to adopt non-natural kinematic strategies. Controlling these FES systems and integrating them seamlessly with the remaining function is still challenging. This project explored the use of electromyographic signals (EMG) recorded from muscles that remain under voluntary control to automatically stimulate paralyzed muscles in the shoulder and elbow; restoring proximal arm function in a more natural manner; interacting synergistically with the remaining function; and complementing the hand grasp function provided by the current systems. A musculoskeletal model of the shoulder and elbow was used to select an optimal set of muscles for stimulation. The model was also used to generate the patterns of activation required to restore high level reaching function. We demonstrated that a neural network controller could be trained to predict activations for the paralyzed muscles using voluntary muscle activations as inputs. The controller was then implemented in one human subject, where his recorded EMG signals were used to train it. The implemented strategy showed that it is possible to restore reaching function, controlling the stimulation automatically. Furthermore, the intervention proved useful in increasing the range of motion of the arm and improving overall shoulder stability.

Committee: Robert Kirsch PhD (Advisor); Edward Chadwick PhD (Committee Member); Patrick Crago PhD (Committee Member); Michael Branicky PhD (Committee Member); Musa Audu PhD (Committee Member) Subjects: Biomedical Research

Doctor of Philosophy, Case Western Reserve University, 2007, Biomedical Engineering

Functional electrical stimulation (FES) is used to elicit contractions in paralyzed muscles and increase the independence of people with impaired neurological function. Most existing neuroprostheses consists of muscle-based electrodes. However, nerve electrodes are emerging as a tool to provide increased benefit for increasingly complicated systems. Many types of nerve electrodes have been developed and tested in animals but few have been transferred to clinical use and none have been used in motor neuroprostheses. This work has set up and followed a strategy to overcome the obstacles to clinical deployment for the spiral nerve cuff electrode. Initial intraoperative testing provided valuable information about the function of human nerves. Stimulation thresholds were determined to be similar to the animal studies and selective activation of a single muscle was possible from all nerves. This information was used to choose electrode locations and stimulation parameters for chronic testing. Chronically implanted spiral nerve cuff electrodes were found to be a stable platform for activation of paralyzed muscles. There were no adverse functional changes or sensation due to the implanted electrodes implanted for over 1.5 years. Nerve stimulation produced controllable activation of the distal muscles with joint moments sufficient for functional tasks. At least one muscle could be selectively activated from each proximal nerve trunk and the selectivity increased with the use of multi-contact stimulation. The spiral nerve cuff electrode is an effective tool for activating paralyzed muscles in the human extremities.

Committee: Dustin Tyler (Advisor) Subjects: