R. Brent Gillespie

PURPOSE: Foot drop is a common clinical problem that is characterized by difficulty in foot dorsiflexion, thereby increasing the risk of unstable gait and falling. Restoring voluntary motor control in individuals with foot drop remains a critical challenge. Although exoskeletons offer a promising avenue for functional assistance, the current exoskeleton control interfaces are often hindered by instability and unreliable quality of the detected motor control signals. To address this limitation, the Muscle Cuff Regenerative Peripheral Nerve Interface (MC-RPNI) was developed as a biologic construct to amplify efferent motor signals from peripheral nerves, thereby providing improved control signals to drive exoskeletons. Previous studies have shown that the MC-RPNI can amplify peripheral nerve signals by 10-20 fold at 3 months post-surgery in anesthetized rats. However, its physiologic signaling during volitional movement in vivo has not been assessed. In this study, we evaluated the signal amplification and gait-correlated neural activity of the MC-RPNI in freely moving rats on a treadmill. METHODS: MC-RPNIs were created using donor muscle grafts on the intact common peroneal (CP) nerve, which is responsible for transmitting motor commands associated with foot dorsiflexion, in rats (n=6). Treadmill-trained rats were implanted with recording electrodes (MicroProbes) in both the proximal CP nerve and the MC-RPNI 3 months post-surgery, secured via chronic headstage implants. Volitional CP nerve signals, MC-RPNI signals, and the rat's gait on the treadmill (via Optitrack) were simultaneously recorded and aligned in real time every week for a duration of six weeks. After completion of in vivo data collections, MC-RPNIs were harvested for histological analysis, including hematoxylin and eosin (H&E) and immunohistochemistry (IHC) staining. RESULTS: All MC-RPNIs remained healthy throughout the study for 6 weeks with no signs of pain and motor deficits during volitional movements in rats. The CP nerve recording and the intramuscular electromyography (EMG) signals from the MC-RPNI revealed that the MC-RPNI amplified volitional CP nerve signals more than tenfold, achieving a signal-to-noise ratio of 20 dB. MC-RPNI activity was predominantly observed during the dorsiflexion phase of gait (i.e., decrease of ankle angle), indicating that the construct transduced CP nerve activity associated with motor commands for foot dorsiflexion. These findings remained consistent throughout the study for 6 weeks. In histological analysis of the MC-RPNI, H&E staining revealed well-preserved muscle architecture with no evidence of degeneration or neuroma, and IHC staining confirmed sustained muscle reinnervation of the MC-RPNI constructs. CONCLUSION: The MC-RPNI reliably amplifies volitional motor signals from the CP nerve and exhibits physiologic signaling during volitional gait for 6 weeks. Histological evidence from the MC-RPNI further validates the viability of the construct to provide improved motor control signals in vivo . These findings support the potential of the MC-RPNI as a robust biologic interface for advanced exoskeleton control.

PURPOSE: Foot drop is a common clinical problem that is characterized by difficulty in foot dorsiflexion, thereby increasing the risk of unstable gait and falling. Restoring voluntary motor control in individuals with foot drop remains a critical challenge. Although exoskeletons offer a promising avenue for functional assistance, the current exoskeleton control interfaces are often hindered by instability and unreliable quality of the detected motor control signals. To address this limitation, the Muscle Cuff Regenerative Peripheral Nerve Interface (MC-RPNI) was developed as a biologic construct to amplify efferent motor signals from peripheral nerves, thereby providing improved control signals to drive exoskeletons. Previous studies have shown that the MC-RPNI can amplify peripheral nerve signals by 10-20 fold at 3 months post-surgery in anesthetized rats. However, its physiologic signaling during volitional movement in vivo has not been assessed. In this study, we evaluated the signal amplification and gait-correlated neural activity of the MC-RPNI in freely moving rats on a treadmill. METHODS: MC-RPNIs were created using donor muscle grafts on the intact common peroneal (CP) nerve, which is responsible for transmitting motor commands associated with foot dorsiflexion, in rats (n=6). Treadmill-trained rats were implanted with recording electrodes (MicroProbes) in both the proximal CP nerve and the MC-RPNI 3 months post-surgery, secured via chronic headstage implants. Volitional CP nerve signals, MC-RPNI signals, and the rat's gait on the treadmill (via Optitrack) were simultaneously recorded and aligned in real time every week for a duration of six weeks. After completion of in vivo data collections, MC-RPNIs were harvested for histological analysis, including hematoxylin and eosin (H&E) and immunohistochemistry (IHC) staining. RESULTS: All MC-RPNIs remained healthy throughout the study for 6 weeks with no signs of pain and motor deficits during volitional movements in rats. The CP nerve recording and the intramuscular electromyography (EMG) signals from the MC-RPNI revealed that the MC-RPNI amplified volitional CP nerve signals more than tenfold, achieving a signal-to-noise ratio of 20 dB. MC-RPNI activity was predominantly observed during the dorsiflexion phase of gait (i.e., decrease of ankle angle), indicating that the construct transduced CP nerve activity associated with motor commands for foot dorsiflexion. These findings remained consistent throughout the study for 6 weeks. In histological analysis of the MC-RPNI, H&E staining revealed well-preserved muscle architecture with no evidence of degeneration or neuroma, and IHC staining confirmed sustained muscle reinnervation of the MC-RPNI constructs. CONCLUSION: The MC-RPNI reliably amplifies volitional motor signals from the CP nerve and exhibits physiologic signaling during volitional gait for 6 weeks. Histological evidence from the MC-RPNI further validates the viability of the construct to provide improved motor control signals in vivo . These findings support the potential of the MC-RPNI as a robust biologic interface for advanced exoskeleton control.

PURPOSE: Foot drop is a common clinical problem that is characterized by difficulty in foot dorsiflexion, thereby increasing the risk of unstable gait and falling. Restoring voluntary motor control in individuals with foot drop remains a critical challenge. Although exoskeletons offer a promising avenue for functional assistance, the current exoskeleton control interfaces are often hindered by instability and unreliable quality of the detected motor control signals. To address this limitation, the Muscle Cuff Regenerative Peripheral Nerve Interface (MC-RPNI) was developed as a biologic construct to amplify efferent motor signals from peripheral nerves, thereby providing improved control signals to drive exoskeletons. Previous studies have shown that the MC-RPNI can amplify peripheral nerve signals by 10-20 fold at 3 months post-surgery in anesthetized rats. However, its physiologic signaling during volitional movement in vivo has not been assessed. In this study, we evaluated the signal amplification and gait-correlated neural activity of the MC-RPNI in freely moving rats on a treadmill. METHODS: MC-RPNIs were created using donor muscle grafts on the intact common peroneal (CP) nerve, which is responsible for transmitting motor commands associated with foot dorsiflexion, in rats (n=6). Treadmill-trained rats were implanted with recording electrodes (MicroProbes) in both the proximal CP nerve and the MC-RPNI 3 months post-surgery, secured via chronic headstage implants. Volitional CP nerve signals, MC-RPNI signals, and the rat's gait on the treadmill (via Optitrack) were simultaneously recorded and aligned in real time every week for a duration of six weeks. After completion of in vivo data collections, MC-RPNIs were harvested for histological analysis, including hematoxylin and eosin (H&E) and immunohistochemistry (IHC) staining. RESULTS: All MC-RPNIs remained healthy throughout the study for 6 weeks with no signs of pain and motor deficits during volitional movements in rats. The CP nerve recording and the intramuscular electromyography (EMG) signals from the MC-RPNI revealed that the MC-RPNI amplified volitional CP nerve signals more than tenfold, achieving a signal-to-noise ratio of 20 dB. MC-RPNI activity was predominantly observed during the dorsiflexion phase of gait (i.e., decrease of ankle angle), indicating that the construct transduced CP nerve activity associated with motor commands for foot dorsiflexion. These findings remained consistent throughout the study for 6 weeks. In histological analysis of the MC-RPNI, H&E staining revealed well-preserved muscle architecture with no evidence of degeneration or neuroma, and IHC staining confirmed sustained muscle reinnervation of the MC-RPNI constructs. CONCLUSION: The MC-RPNI reliably amplifies volitional motor signals from the CP nerve and exhibits physiologic signaling during volitional gait for 6 weeks. Histological evidence from the MC-RPNI further validates the viability of the construct to provide improved motor control signals in vivo . These findings support the potential of the MC-RPNI as a robust biologic interface for advanced exoskeleton control.

PURPOSE: Foot drop is a common clinical problem that is characterized by difficulty in foot dorsiflexion, thereby increasing the risk of unstable gait and falling. Restoring voluntary motor control in individuals with foot drop remains a critical challenge. Although exoskeletons offer a promising avenue for functional assistance, the current exoskeleton control interfaces are often hindered by instability and unreliable quality of the detected motor control signals. To address this limitation, the Muscle Cuff Regenerative Peripheral Nerve Interface (MC-RPNI) was developed as a biologic construct to amplify efferent motor signals from peripheral nerves, thereby providing improved control signals to drive exoskeletons. Previous studies have shown that the MC-RPNI can amplify peripheral nerve signals by 10-20 fold at 3 months post-surgery in anesthetized rats. However, its physiologic signaling during volitional movement in vivo has not been assessed. In this study, we evaluated the signal amplification and gait-correlated neural activity of the MC-RPNI in freely moving rats on a treadmill. METHODS: MC-RPNIs were created using donor muscle grafts on the intact common peroneal (CP) nerve, which is responsible for transmitting motor commands associated with foot dorsiflexion, in rats (n=6). Treadmill-trained rats were implanted with recording electrodes (MicroProbes) in both the proximal CP nerve and the MC-RPNI 3 months post-surgery, secured via chronic headstage implants. Volitional CP nerve signals, MC-RPNI signals, and the rat's gait on the treadmill (via Optitrack) were simultaneously recorded and aligned in real time every week for a duration of six weeks. After completion of in vivo data collections, MC-RPNIs were harvested for histological analysis, including hematoxylin and eosin (H&E) and immunohistochemistry (IHC) staining. RESULTS: All MC-RPNIs remained healthy throughout the study for 6 weeks with no signs of pain and motor deficits during volitional movements in rats. The CP nerve recording and the intramuscular electromyography (EMG) signals from the MC-RPNI revealed that the MC-RPNI amplified volitional CP nerve signals more than tenfold, achieving a signal-to-noise ratio of 20 dB. MC-RPNI activity was predominantly observed during the dorsiflexion phase of gait (i.e., decrease of ankle angle), indicating that the construct transduced CP nerve activity associated with motor commands for foot dorsiflexion. These findings remained consistent throughout the study for 6 weeks. In histological analysis of the MC-RPNI, H&E staining revealed well-preserved muscle architecture with no evidence of degeneration or neuroma, and IHC staining confirmed sustained muscle reinnervation of the MC-RPNI constructs. CONCLUSION: The MC-RPNI reliably amplifies volitional motor signals from the CP nerve and exhibits physiologic signaling during volitional gait for 6 weeks. Histological evidence from the MC-RPNI further validates the viability of the construct to provide improved motor control signals in vivo . These findings support the potential of the MC-RPNI as a robust biologic interface for advanced exoskeleton control.

Multicopter uncrewed aircraft systems (UAS) commonly use parallel rotors to create body-fixed thrust and torque for control, leaving these systems underactuated. Under-actuation poses a significant challenge in tasks where attitude is critical, such as in collision-based aerial manipulation. Planning and control of system state at collision is required to ensure safe post-collision recovery. In particular, setting up pre-impact states such that impulses do not produce moments about mass centers can ensure recoverable departure velocities. To address the underactuated nature of UAS for collision-based aerial manipulation, this paper presents a UAS with an attached actuated pogostick. While the UAS with actuated pogostick is still underactuated, closing a control loop on the collision variables critical to managing collision response becomes possible with the new system equations. The proposed approach leverages an optimal trajectory planner coupled with a run-time controller based on partial feedback linearization of the UAS with actuated pogostick. Results show that the addition of the actuated pogostick enables setup for recoverable post-collision states when given dynamically feasible trajectories from the optimal trajectory planner.

The bag valve mask (BVM) is an essential and ubiquitous healthcare tool for ventilatory support of patients in all manner of settings, from routine operating procedures to first responder cardiopulmonary resuscitation. Despite its prevalence, the BVM is difficult and labor-intensive to use, requiring continuous pressure from one or both hands of a healthcare provider to seal the mask against the patient’s face. We propose a new category of mask that is a soft robot. By conforming, sealing, and adhering to the patient’s face using a combination of particle jamming and suction, our proposed mask requires only a one-time placement procedure, after which the mask operates hands-free. The mask is created from a soft silicone elastomer with two particle jamming rings around its circumference and a gap between them for a suction channel. In human face phantoms, we validate that our masks can support positive pressure ventilation at skin-safe vacuum pressures and show that particle jamming expands its operating region. We further demonstrate its successful operation in the presence of skin surface contaminants and hair. We believe that our soft robot face mask will relieve the provider of continuously pressing and holding a mask to seal it, enabling them to focus on other patient care tasks, reducing personnel demands in hospital settings, and stretching resources during mass casualty events.

Herein, the design, modeling, and validation of high‐flow, fluid‐driven, membrane valves tailored specifically for applications in soft robotic systems are described. Targeting the piping problem in hyper‐actuated soft robots, two fluid‐driven membrane valve designs that can admit flows of up to while weighing less than are introduced. A mathematical model to predict fluid flow by representing the displacement of the membrane as a scalar quantity influenced by the balance of pressures applied across the valve's ports is established. The model incorporates six parameters with direct physical relevance, enhancing its usefulness in valve design and system integration. In an experimental validation, flow rates with deviations within 4% are predicted and the onset of flow is correctly identified with an error rate of less than 1%. In addition, applications of these valves for flow amplification and for the creation of a fluid‐driven oscillator are experimentally demonstrated. This research contributes to the advancement of soft robotics by providing a tool for designing, optimizing, and controlling fluid‐driven systems and it lays the groundwork for the future development of embedded, fluid‐controlled valve networks that can be used to realize hyper‐actuated soft robotic systems.

A human operator using a manual control interface has ready access to their own command signal, both by efference copy and proprioception. In contrast, a human supervisor typically relies on visual information alone. We propose supplying a supervisor with a copy of the operator’s command signal, hypothesizing improved performance, especially when that copy is provided through haptic display. We experimentally compared haptic with visual access to the command signal, quantifying the performance of N=10 participants attempting to determine which of three reference signals was being tracked by an operator. Results indicate an improved accuracy in identifying the tracked target when haptic display was available relative to visual display alone. We conjecture the benefit follows from the relationship of haptics to the supervisor’s own experience, perhaps muscle memory, as an operator.

In this paper, we introduce the concept of the Fluid Jacobian, which provides a description of the power transmission that operates between the fluid and mechanical domains in soft robotic systems. It can be understood as a generalization of the traditional kinematic Jacobian that relates the joint space torques and velocities to the task space forces and velocities of a robot. In a similar way, the Fluid Jacobian relates fluid pressure to task space forces and fluid flow to task space velocities. In addition, the Fluid Jacobian can also be regarded as a generalization of the piston cross-sectional area in a fluid-driven cylinder that extends to complex geometries and multiple dimensions. In the following, we present a theoretical derivation of this framework, focus on important special cases, and illustrate the meaning and practical applicability of the Fluid Jacobian in four brief examples.

Soft fluidic actuators are becoming popular for their backdrivability, potential for high power density, and their support for power supply through flexible tubes. Control and design of such actuators requires serviceable models that describe how they relate fluid pressure and flow to mechanical force and motion. We present a simple 2-port model of a bellows actuator that accounts for the relationships among fluid and mechanical variables imposed by the kinematics of the deforming bellows structure and accounts for elastic energy stored in the actuator's thermoplastic material structure. Elastic energy storage due to axial deformation is captured by revolving a differential strip whose linear elastic behavior is a nonlinear function of the actuator length. The model is evaluated through experiments in which either actuator length and pressure or force and pressure are imposed. The model has an error of 9.8% of the force range explored and yields insight into the effects of geometry changes. The resulting model can be used for model-based control or actuator design across the full operating range and can be exercised under either imposed force or imposed actuator length.

In this information age, our machines have evolved from tools that process mechanical work into computerized devices that process information. A collateral outcome of this trend is a diminishing role for haptic feedback. If the benefits of haptic feedback, including those inherent in tool use, are to be preserved in information processing machines, we require an improved understanding of the various ways in which haptic feedback supports embodied cognition and supports high utility exchange of information. In this paper we classify manual control interfaces as instrumental or semiotic and describe an exploratory study in which a steering wheel functions simultaneously to communicate tactical and operational features in semi-autonomous driving. A shape-changing interface (semiotic/tactical) in the grip axis complements haptic shared control (instrumental/operational) in the steering axis. Experimental results involving $\mathrm{N}=30$ participants show that the addition of a semiotic interface improves human-automation team performance in a shared driving scenario with competing objectives and metered information sharing.

Aerial manipulation describes a process that includes physical interaction between an unmanned aircraft system (UAS) and its environment. We aim to apply aerial manipulation to sample leaves and small branches from rain forest trees. Current approaches to aerial manipulation involve extended periods of UAS-environment interaction, during which forces and moments can lead to a loss in attitude or position control in underactuated multicopters. By adapting intelligent foot placement strategies found in dynamically stable hopping robots, this work proposes a strategy involving carefully managed intentional collisions between the UAS and its environment. We designed an attitude controller denoted a Velocity Matching controller that aligns a UAS-mounted pogo-stick foot with the center of mass velocity vector during collision approach to maximize UAS ability to recover a hover state after collision. We propose the use of a flight envelope involving altitude and horizontal speed states to assess recoverability prior to initiating each approach to collision. We identify this flight envelope from a simulation study built on a model of flight in Conventional Waypoint Following and Velocity Matching control modes as well as a model of collision response. Experimental flight testing evaluates the simulation-based envelope resulting in an actual envelope that is somewhat smaller but similarly shaped to the envelope identified in simulation.