It has been repeatedly shown that females have lower stability and increased risk of ankle injury when compared to males participating in similar sports activities (e.g., basketball and soccer), yet sex differences in neuromuscular control of the ankle, including the modulation of ankle stiffness, and their contribution to stability remain unknown. To identify sex differences in human ankle stiffness, this study quantified 2- dimensional (2D) ankle stiffness in 20 young, healthy men and 20 young, healthy women during upright standing over a range of tasks, specifically, ankle muscle co-contraction tasks (4 levels up to 20% maximum voluntary co-contraction of ankle muscles), weight-bearing tasks (4 levels up to 90% of body weight), and ankle torque generation tasks accomplished by maintaining offset center-of-pressure (5 levels up to +6 cm to the center-of-pressure during quiet standing). A dual-axial robotic platform, capable of perturbing the ankle in both the sagittal and frontal planes and measuring the corresponding ankle torques, was used to reliably quantify the 2D ankle stiffness during upright standing. In all task conditions and in both planes of ankle motion, ankle stiffness in males was consistently greater than that in females. Among all 26 experimental conditions, all but 2 conditions in the frontal plane showed statistically significant sex differences. Further analysis on the normalized ankle stiffness scaled by weight times height suggests that while sex differences in ankle stiffness in the sagittal plane could be explained by sex differences in anthropometric factors as well as neuromuscular factors, the differences in the frontal plane could be mostly explained by anthropometric factors. This study also demonstrates that the sex differences in the sagittal plane were significantly higher as compared to those in the frontal plane. The results indicate that females have lower ankle stiffness during upright standing thereby providing the neuromuscular basis for further investigations on the correlation of ankle stiffness and the higher risk of ankle injury in females.

Robotic lower limb prostheses provide new opportunities to help transfemoral amputees regain mobility. However, their application is impeded by that the impedance control parameters need to be tuned and optimized manually by prosthetists for each individual user in different task environments. Reinforcement learning (RL) is capable of automatically learning from interacting with the environment. It becomes a natural candidate to replace human prosthetists to customize the control parameters. However, neither traditional RL approaches nor the popular deep RL approaches are readily suitable for learning with limited number of samples and samples with large variations. This dissertation aims to explore new RL based adaptive solutions that are data-efficient for controlling robotic prostheses.

This dissertation begins by proposing a new flexible policy iteration (FPI) framework. To improve sample efficiency, FPI can utilize either on-policy or off-policy learning strategy, can learn from either online or offline data, and can even adopt exiting knowledge of an external critic. Approximate convergence to Bellman optimal solutions are guaranteed under mild conditions. Simulation studies validated that FPI was data efficient compared to several established RL methods. Furthermore, a simplified version of FPI was implemented to learn from offline data, and then the learned policy was successfully tested for tuning the control parameters online on a human subject.

Next, the dissertation discusses RL control with information transfer (RL-IT), or knowledge-guided RL (KG-RL), which is motivated to benefit from transferring knowledge acquired from one subject to another. To explore its feasibility, knowledge was extracted from data measurements of able-bodied (AB) subjects, and transferred to guide Q-learning control for an amputee in OpenSim simulations. This result again demonstrated that data and time efficiency were improved using previous knowledge.

While the present study is new and promising, there are still many open questions to be addressed in future research. To account for human adaption, the learning control objective function may be designed to incorporate human-prosthesis performance feedback such as symmetry, user comfort level and satisfaction, and user energy consumption. To make the RL based control parameter tuning practical in real life, it should be further developed and tested in different use environments, such as from level ground walking to stair ascending or descending, and from walking to running.

Wearable assistive devices have been greatly improved thanks to advancements made in soft robotics, even creation soft extra arms for paralyzed patients. Grasping remains an active area of research of soft extra limbs. Soft robotics allow the creation of grippers that due to their inherit compliance making them lightweight, safer for human interactions, more robust in unknown environments and simpler to control than their rigid counterparts. A current problem in soft robotics is the lack of seamless integration of soft grippers into wearable devices, which is in part due to the use of elastomeric materials used for the creation of most of these grippers. This work introduces fabric-reinforced textile actuators (FRTA). The selection of materials, design logic of the fabric reinforcement layer and fabrication method are discussed. The relationship between the fabric reinforcement characteristics and the actuator deformation is studied and experimentally verified. The FRTA are made of a combination of a hyper-elastic fabric material with a stiffer fabric reinforcement on top. In this thesis, the design, fabrication, and evaluation of FRTAs are explored. It is shown that by varying the geometry of the reinforcement layer, a variety of motion can be achieve such as axial extension, radial expansion, bending, and twisting along its central axis. Multi-segmented actuators can be created by tailoring different sections of fabric-reinforcements together in order to generate a combination of motions to perform specific tasks. The applicability of this actuators for soft grippers is demonstrated by designing and providing preliminary evaluation of an anthropomorphic soft robotic hand capable of grasping daily living objects of various size and shapes.

Locomotion is of prime importance in enabling human beings to effectively respond

in space and time to meet different needs. Approximately 2 million Americans live

with an amputation with most of those amputations being of the lower limbs. To

advance current state-of-the-art lower limb prosthetic devices, it is necessary to adapt

performance at a level of intelligence seen in human walking. As such, this thesis

focuses on the mechanisms involved during human walking, while transitioning from

rigid to compliant surfaces such as from pavement to sand, grass or granular media.

Utilizing a unique tool, the Variable Stiffness Treadmill (VST), as the platform for

human walking, rigid to compliant surface transitions are simulated. The analysis of

muscular activation during the transition from rigid to different compliant surfaces

reveals specific anticipatory muscle activation that precedes stepping on a compliant

surface. There is also an indication of varying responses for different surface stiffness

levels. This response is observed across subjects. Results obtained are novel and

useful in establishing a framework for implementing control algorithm parameters to

improve powered ankle prosthesis. With this, it is possible for the prosthesis to adapt

to a new surface and therefore resulting in a more robust smart powered lower limb

prosthesis.

Existing theories suggest that evidence is accumulated before making a decision with competing goals. In motor tasks, reward and motor costs have been shown to influence the decision, but the interaction between these two variables has not been studied in depth. A novel reward-based sensorimotor decision-making task was developed to investigate how reward and motor costs interact to influence decisions. In human subjects, two targets of varying size and reward were presented. After a series of three tones, subjects initiated a movement as one of the targets disappeared. Reward was awarded when participants reached through the remaining target within a specific amount of time. Subjects had to initiate a movement before they knew which target remained. Reward was found to be the only factor that influenced the initial reach. When reward was increased, there was a lower probability of intermediate movements. Both target size and reward lowered reaction times individually and jointly. This interaction can be interpreted as the effect of the expected value, which suggests that reward and target size are not evaluated independently during motor planning. Curvature, or the changing of motor plans, was driven primarily by the target size. After an initial decision was made, the motor costs to switch plans and hit the target had the largest impact on the curvature. An interaction between the reward and target size was also found for curvature, suggesting that the expected value of the target influences the changing of motor plans. Reward, target size, and the interaction between the two were all significant factors for different parts of the decision-making process.

Proprioception is the sense of body position, movement, force, and effort. Loss of proprioception can affect planning and control of limb and body movements, negatively impacting activities of daily living and quality of life. Assessments employing planar robots have shown that proprioceptive sensitivity is directionally dependent within the horizontal plane however, few studies have looked at proprioceptive sensitivity in 3d space. In addition, the extent to which proprioceptive sensitivity is modifiable by factors such as exogenous neuromodulation is unclear. To investigate proprioceptive sensitivity in 3d we developed a novel experimental paradigm employing a 7-DoF robot arm, which enables reliable testing of arm proprioception along arbitrary paths in 3d space, including vertical motion which has previously been neglected. A participant’s right arm was coupled to a trough held by the robot that stabilized the wrist and forearm, allowing for changes in configuration only at the elbow and shoulder. Sensitivity to imposed displacements of the endpoint of the arm were evaluated using a “same/different” task, where participant’s hands were moved 1-4 cm from a previously visited reference position. A measure of sensitivity (d’) was compared across 6 movement directions and between 2 postures. For all directions, sensitivity increased monotonically as the distance from the reference location increased. Sensitivity was also shown to be anisotropic (directionally dependent) which has implications for our understanding of the planning and control of reaching movements in 3d space.

The effect of neuromodulation on proprioceptive sensitivity was assessed using transcutaneous electrical nerve stimulation (TENS), which has been shown to have beneficial effects on human cognitive and sensorimotor performance in other contexts. In this pilot study the effects of two frequencies (30hz and 300hz) and three electrode configurations were examined. No effect of electrode configuration was found, however sensitivity with 30hz stimulation was significantly lower than with 300hz stimulation (which was similar to sensitivity without stimulation). Although TENS was shown to modulate proprioceptive sensitivity, additional experiments are required to determine if TENS can produce enhancement rather than depression of sensitivity which would have positive implications for rehabilitation of proprioceptive deficits arising from stroke and other disorders.

Neural interfacing applications have advanced in complexity, with needs for increasingly high degrees of freedom in prosthetic device control, sharper discrimination in sensory percepts in bidirectional interfaces, and more precise localization of functional connectivity in the brain. As such, there is a growing need for reliable neurophysiological recordings at a fine spatial scale matching that of cortical columnar processing. Penetrating microelectrodes provide localization sufficient to isolate action potential (AP) waveforms, but often suffer from recorded signal deterioration linked to foreign body response. Micro-Electrocorticography (μECoG) surface electrodes elicit lower foreign body response and show greater chronic stability of recorded signals, though they typically lack the signal localization necessary to isolate individual APs. This dissertation validates the recording capacity of a novel, flexible, large area μECoG array with bilayer routing in a feline implant, and explores the ability of conventional μECoG arrays to detect features of neuronal activity in a very high frequency band associated with AP waveforms.

Recordings from both layers of the flexible μECoG array showed frequency features typical of cortical local field potentials (LFP) and were shown to be stable in amplitude over time. Recordings from both layers also showed consistent, frequency-dependent modulation after induction of general anesthesia, with large increases in beta and gamma band and decreases in theta band observed over three experiments. Recordings from conventional μECoG arrays over human cortex showed robust modulation in a high frequency (250-2000 Hz) band upon production of spoken words. Modulation in this band was used to predict spoken words with over 90% accuracy. Basal Ganglia neuronal AP firing was also shown to significantly correlate with various cortical μECoG recordings in this frequency band. Results indicate that μECoG surface electrodes may detect high frequency neuronal activity potentially associated with AP firing, a source of information previously unutilized by these devices.

Properly deciding to engage in or to withhold an action is a critical ability for goal-oriented movement control. Such decision may be driven by expected value from the choice of action but associating physical effort may discount such value. A novel anticipatory stopping task was developed to investigate effort discounted decision process potentially present in proactive inhibitory control. Subjects performed or abstained from target reach if they believed it was a Go or Stop trial respectively. Reward was awarded to a reach, correctly timed to hit a target at the same time as the moving bar in Go trials. During the Stop trials, correctly judging to not engage in a reach from the color of the moving bar that linked to the bar’s probability of stopping before the target resulted in gaining a reward. Resistive force field incurred additional physical effort for choosing to reach. Introducing effort expectedly decreased the tendency to respond at trials with higher stop probability. Surprisingly, tendency to respond increased and corresponding reaction time decreased in the trials with lower stop probability. Such asymmetric effect suggests that the value of context ineffective response is discounted, and the value of context effective response is flexibly enhanced by its associated effort cost to drive decision-process in goal-oriented manner. Medial frontal event related potential (ERP) locked to the onset of moving bar appearance reflected such effort discounted decision process. Theta band observed in Stop trials accounted for evaluation of effort and context possibly reinforcing such decision-making.

The human hand comprises complex sensorimotor functions that can be impaired by neurological diseases and traumatic injuries. Effective rehabilitation can bring the impaired hand back to a functional state because of the plasticity of the central nervous system to relearn and remodel the lost synapses in the brain. Current rehabilitation therapies focus on strengthening motor skills, such as grasping, employ multiple objects of varying stiffness and devices that are bulky, costly, and have limited range of stiffness due to the rigid mechanisms employed in their variable stiffness actuators. This research project presents a portable cost-effective soft robotic haptic device with a broad stiffness range that is adjustable and can be utilized in both clinical and home settings. The device eliminates the need for multiple objects by employing a pneumatic soft structure made with highly compliant materials that act as the actuator as well as the structure of the haptic interface. It is made with interchangeable soft elastomeric sleeves that can be customized to include materials of varying stiffness to increase or decrease the stiffness range. The device is fabricated using existing 3D printing technologies, and polymer molding and casting techniques, thus keeping the cost low and throughput high. The haptic interface is linked to either an open-loop system that allows for an increased pressure during usage or closed-loop system that provides pressure regulation in accordance with the stiffness the user specifies. A preliminary evaluation is performed to characterize the effective controllable region of variance in stiffness. Results indicate that the region of controllable stiffness was in the center of the device, where the stiffness appeared to plateau with each increase in pressure. The two control systems are tested to derive relationships between internal pressure, grasping force exertion on the surface, and displacement using multiple probing points on the haptic device. Additional quantitative evaluation is performed with study participants and juxtaposed to a qualitative analysis to ensure adequate perception in compliance variance. Finally, a qualitative evaluation showed that greater than 60% of the trials resulted in the correct perception of stiffness in the haptic device.

Recently, it was demonstrated that startle-evoked-movements (SEMs) are present during individuated finger movements (index finger abduction), but only following intense training. This demonstrates that changes in motor planning, which occur through training (motor learning - a characteristic which can provide researchers and clinicians with information about overall rehabilitative effectiveness), can be analyzed with SEM. The objective here was to determine if SEM is a sensitive enough tool for differentiating expertise (task solidification) in a common everyday task (typing). If proven to be true, SEM may then be useful during rehabilitation for time-stamping when task-specific expertise has occurred, and possibly even when the sufficient dosage of motor training (although not tested here) has been delivered following impairment. It was hypothesized that SEM would be present for all fingers of an expert population, but no fingers of a non-expert population. A total of 9 expert (75.2 ± 9.8 WPM) and 8 non-expert typists, (41.6 ± 8.2 WPM) with right handed dominance and with no previous neurological or current upper extremity impairment were evaluated. SEM was robustly present (all p < 0.05) in all fingers of the experts (except the middle) and absent in all fingers of non-experts except the little (although less robust). Taken together, these results indicate that SEM is a measurable behavioral indicator of motor learning and that it is sensitive to task expertise, opening it for potential clinical utility.