Background Different groups developed wearable robots for walking assistance, but there is still a need for methods to quickly tune actuation parameters for each robot and population or sometimes even for individual users. Protocols where parameters are held constant for multiple minutes have traditionally been used for evaluating responses to parameter changes such as metabolic rate or walking symmetry. However, these discrete protocols are time-consuming. Recently, protocols have been proposed where a parameter is changed in a continuous way. The aim of the present study was to compare effects of continuously varying assistance magnitude with a soft exosuit against discrete step conditions.
Methods Seven participants walked on a treadmill wearing a soft exosuit that assists plantarflexion and hip flexion. In Continuous-up, peak exosuit ankle moment linearly increased from approximately 0 to 38% of biological moment over 10 min. Continuous-down was the opposite. In Discrete, participants underwent five periods of 5 min with steady peak moment levels distributed over the same range as Continuous-up and Continuous-down. We calculated metabolic rate for the entire Continuous-up and Continuous-down conditions and the last 2 min of each Discrete force level. We compared kinematics, kinetics and metabolic rate between conditions by curve fitting versus peak moment.
Results Reduction in metabolic rate compared to Powered-off was smaller in Continuous-up than in Continuous-down at most peak moment levels, due to physiological dynamics causing metabolic measurements in Continuous-up and Continuous-down to lag behind the values expected during steady-state testing. When evaluating the average slope of metabolic reduction over the entire peak moment range there was no significant difference between Continuous-down and Discrete. Attempting to correct the lag in metabolics by taking the average of Continuous-up and Continuous-down removed all significant differences versus Discrete. For kinematic and kinetic parameters, there were no differences between all conditions.
Conclusions The finding that there were no differences in biomechanical parameters between all conditions suggests that biomechanical parameters can be recorded with the shortest protocol condition (i.e. single Continuous directions). The shorter time and higher resolution data of continuous sweep protocols hold promise for the future study of human interaction with wearable robots.
This paper presents design and batch manufacturing of a highly stretchable textile-silicone capacitive sensor to be used in human articulation detection, soft robotics, and exoskeletons. The proposed sensor is made of conductive knit fabric as electrode and silicone elastomer as dielectric. The batch manufacturing technology enables production of large sensor mat and arbitrary shaping of sensors, which is precisely achieved via laser cutting of the sensor mat. Individual capacitive sensors exhibit high linearity, low hysteresis, and a gauge factor of 1.23. Compliant, low-profile, and robust electrical connections are established by fusing filaments of micro coaxial cable to conductive fabric electrodes of the sensor with thermoplastic film. The capacitive sensors are integrated on a reconstructed glove for monitoring finger motions.
Background Only very recently, studies have shown that it is possible to reduce the metabolic rate of unloaded and loaded walking using robotic ankle exoskeletons. Some studies obtained this result by means of high positive work assistance while others combined negative and positive work assistance. There is no consensus about the isolated contribution of negative work assistance. Therefore, the aim of the present study is to examine the effect of varying negative work assistance at the ankle joint while maintaining a fixed level of positive work assistance with a multi-articular soft exosuit.
Methods We tested eight participants during walking at 1.5 ms−1 with a 23-kg backpack. Participants wore a version of the exosuit that assisted plantarflexion via Bowden cables tethered to an off-board actuation platform. In four active conditions we provided different rates of exosuit bilateral ankle negative work assistance ranging from 0.015 to 0.037 W kg−1 and a fixed rate of positive work assistance of 0.19 W kg−1.
Results All active conditions significantly reduced metabolic rate by 11 to 15% compared to a reference condition, where the participants wore the exosuit but no assistance was provided. We found no significant effect of negative work assistance. However, there was a trend (p = .08) toward greater reduction in metabolic rate with increasing negative work assistance, which could be explained by observed reductions in biological ankle and hip joint power and moment.
Conclusions The non-significant trend of increasing negative work assistance with increasing reductions in metabolic rate motivates the value in further studies on the relative effects of negative and positive work assistance. There may be benefit in varying negative work over a greater range or in isolation from positive work assistance.
Soft robotic devices have significant potential for medical device applications that warrant safe synergistic interaction with humans. This article describes the optimization of an implantable soft robotic system for heart failure whereby soft actuators wrapped around the ventricles are programmed to contract and relax in synchrony with the beating heart. Elastic elements integrated in to the soft actuators provide recoiling function so as to aid refilling during the diastolic phase of the cardiac cycle. Improved synchronization with the biological system is achieved by incorporating the native ventricular pressure in to the control system to trigger assistance and synchronize the device with the heart. A three-state electro-pneumatic valve configuration allows the actuators to contract at different rates to vary contraction patterns. An in vivo study was performed to test three hypotheses relating to mechanical coupling and temporal synchronization of the actuators and heart. First, that adhesion of the actuators to the ventricles improves cardiac output. Second, that there is a contraction–relaxation ratio of the actuators which generates optimal cardiac output. Third, that the rate of actuator contraction is a factor in cardiac output.
Wearable sensing technology is an emerging area and can be utilized for human motion monitoring, physiology monitoring, and human–machine interaction. In this paper, a new manufacturing approach is presented to create highly stretchable and soft capacitance-based strain sensors. This involves a rapid surface modification technique based on direct-write laser rastering to create microstructured surfaces on prestrained elastomeric sheets. Then, to impart conductivity, sputtering technology is utilized to deposit aluminum and silver metal layers on the bottom and top surfaces of the elastomer sheet, creating a soft capacitor. During benchtop characterization of the sensors, this study demonstrates that the fabricated electrodes maintain their electrical conductivity up to the 250% strain, and the sensor shows a linear and repeatable output up to 85% strain. Finally, their potential is demonstrated for monitoring human motion and respiration through their integration into a wearable arm sleeve and a thoracic belt, respectively.
Background Wearable assistive devices have demonstrated the potential to improve mobility outcomes for individuals with disabilities, and to augment healthy human performance; however, these benefits depend on how effectively power is transmitted from the device to the human user. Quantifying and understanding this power transmission is challenging due to complex human-device interface dynamics that occur as biological tissues and physical interface materials deform and displace under load, absorbing and returning power.
Methods Here we introduce a new methodology for quickly estimating interface power dynamics during movement tasks using common motion capture and force measurements, and then apply this method to quantify how a soft robotic ankle exosuit interacts with and transfers power to the human body during walking. We partition exosuit end-effector power (i.e., power output from the device) into power that augments ankle plantarflexion (termed augmentation power) vs. power that goes into deformation and motion of interface materials and underlying soft tissues (termed interface power).
Results We provide empirical evidence of how human-exosuit interfaces absorb and return energy, reshaping exosuit-to-human power flow and resulting in three key consequences: (i) During exosuit loading (as applied forces increased), about 55% of exosuit end-effector power was absorbed into the interfaces. (ii) However, during subsequent exosuit unloading (as applied forces decreased) most of the absorbed interface power was returned viscoelastically. Consequently, the majority (about 75%) of exosuit end-effector work over each stride contributed to augmenting ankle plantarflexion. (iii) Ankle augmentation power (and work) was delayed relative to exosuit end-effector power, due to these interface energy absorption and return dynamics.
Conclusions Our findings elucidate the complexities of human-exosuit interface dynamics during transmission of power from assistive devices to the human body, and provide insight into improving the design and control of wearable robots. We conclude that in order to optimize the performance of wearable assistive devices it is important, throughout design and evaluation phases, to account for human-device interface dynamics that affect power transmission and thus human augmentation benefits.
We introduce an implantable intracardiac soft robotic right ventricular ejection device (RVED) for dynamic approximation of the right ventricular (RV) free wall and the interventricular septum (IVS) in synchrony with the cardiac cycle to augment blood ejection in right heart failure (RHF). The RVED is designed for safe and effective intracardiac operation and consists of an anchoring system deployed across the IVS, an RV free wall anchor, and a pneumatic artificial muscle linear actuator that spans the RV chamber between the two anchors. Using a ventricular simulator and a custom controller, we characterized ventricular volume ejection, linear approximation against different loads and the effect of varying device actuation periods on volume ejection. The RVED was then tested in vivo in adult pigs (n = 5). First, we successfully deployed the device into the beating heart under 3D echocardiography guidance (n = 4). Next, we performed a feasibility study to evaluate the device's ability to augment RV ejection in an experimental model of RHF (n = 1). RVED actuation augmented RV ejection during RHF; while further chronic animal studies will provide details about the efficacy of this support device. These results demonstrate successful design and implementation of the RVED and its deployment into the beating heart. This soft robotic ejection device has potential to serve as a rapidly deployable system for mechanical circulatory assistance in RHF.
When defining requirements for any wearable robot for walking assistance, it is important to maximize the user’s metabolic benefit resulting from the exosuit assistance while limiting the metabolic penalty of carrying the system’s mass. Thus, the aim of this study was to isolate and characterize the relationship between assistance magnitude and the metabolic cost of walking while also examining changes to the wearer’s underlying gait mechanics. The study was performed with a tethered multiarticular soft exosuit during normal walking, where assistance was directly applied at the ankle joint and indirectly at the hip due to a textile architecture. The exosuit controller was designed such that the delivered torque profile at the ankle joint approximated that of the biological torque during normal walking. Seven participants walked on a treadmill at 1.5 meters per second under one unpowered and four powered conditions, where the peak moment applied at the ankle joint was varied from about 10 to 38% of biological ankle moment (equivalent to an applied force of 18.7 to 75.0% of body weight). Results showed that, with increasing exosuit assistance, net metabolic rate continually decreased within the tested range. When maximum assistance was applied, the metabolic rate of walking was reduced by 22.83 ± 3.17% relative to the powered-off condition (mean ± SEM).
Soft actuators are the components responsible for producing motion in soft robots. Although soft actuators have allowed for a variety of innovative applications, there is a need for design tools that can help to efficiently and systematically design actuators for particular functions. Mathematical modeling of soft actuators is an area that is still in its infancy but has the potential to provide quantitative insights into the response of the actuators. These insights can be used to guide actuator design, thus accelerating the design process. Here, we study fluid-powered fiber-reinforced actuators, because these have previously been shown to be capable of producing a wide range of motions. We present a design strategy that takes a kinematic trajectory as its input and uses analytical modeling based on nonlinear elasticity and optimization to identify the optimal design parameters for an actuator that will follow this trajectory upon pressurization. We experimentally verify our modeling approach, and finally we demonstrate how the strategy works, by designing actuators that replicate the motion of the index finger and thumb.
Soft bending actuators are inherently compliant, compact, and lightweight. They are preferable candidates over rigid actuators for robotic applications ranging from physical human interaction to delicate object manipulation. However, characterizing and predicting their behaviors are challenging due to the material nonlinearities and the complex motions they can produce. This paper investigates a soft bending actuator design that uses a single air chamber and fiber reinforcements. Additionally, the actuator design incorporates a sensing layer to enable real-time bending angle measurement for analysis and control. In order to study the bending and force exertion characteristics when interacting with the environment, a quasistatic analytical model is developed based on the bending moments generated from the applied internal pressure and stretches of the soft materials. Comparatively, a finite-element method model is created for the same actuator design. Both the analytical model and the finite-element model are used in the fiber reinforcement analysis and the validation experiments with fabricated actuators. The experimental results demonstrate that the analytical model captures the relationships of supplied air pressure, actuator bending angle, and interaction force at the actuator tip. Moreover, it is shown that an off-the-shelf bend angle sensor integrated to the actuator in this study could provide real-time force estimation, thus eliminating the need for a force sensor.
There is much interest in form-fitting, low-modulus, implantable devices or soft robots that can mimic or assist in complex biological functions such as the contraction of heart muscle. We present a soft robotic sleeve that is implanted around the heart and actively compresses and twists to act as a cardiac ventricular assist device. The sleeve does not contact blood, obviating the need for anticoagulation therapy or blood thinners, and reduces complications with current ventricular assist devices, such as clotting and infection. Our approach used a biologically inspired design to orient individual contracting elements or actuators in a layered helical and circumferential fashion, mimicking the orientation of the outer two muscle layers of the mammalian heart. The resulting implantable soft robot mimicked the form and function of the native heart, with a stiffness value of the same order of magnitude as that of the heart tissue. We demonstrated feasibility of this soft sleeve device for supporting heart function in a porcine model of acute heart failure. The soft robotic sleeve can be customized to patient-specific needs and may have the potential to act as a bridge to transplant for patients with heart failure.
The Soft Robotics Toolkit (SRT) is an open-access website containing detailed information about the design, fabrication, and characterization of soft-robotic components and systems (Figure 1). Soft robotics is a growing field of research concerned with the development of electromechanical technology composed of compliant materials or structures. The SRT website hosts design files, multimedia fabrication instructions, and software tutorials submitted by an international community of soft-robotics researchers and designers. In this article, we describe the development of the SRT and some challenges in developing widely disseminated robotic-hardware resources. Our attempts to overcome these challenges in the development of the toolkit are discussed by focusing on strategies that have been used to engage participants ranging from K-12 grade students to robotics research groups. A series of design competitions encouraged people to use and contribute to the toolkit. New fabrication methods requiring only low-cost and accessible materials were developed to lower the entry barriers to soft robotics and instructional materials and outreach activities were used to engage new audiences. We hope that our experiences in developing and scaling the toolkit may serve as guidance for other open robotic-hardware projects.
Recent advances in medical robotics have initiated a transition from rigid serial manipulators to flexible or continuum robots capable of navigating to confined anatomy within the body. A desire for further procedure minimization is a key accelerator for the development of these flexible systems where the end goal is to provide access to the previously inaccessible anatomical workspaces and enable new minimally invasive surgical (MIS) procedures. While sophisticated navigation and control capabilities have been demonstrated for such systems, existing manufacturing approaches have limited the capabilities of millimeter-scale end-effectors for these flexible systems to date and, to achieve next generation highly functional end-effectors for surgical robots, advanced manufacturing approaches are required. We address this challenge by utilizing a disruptive 2D layer-by-layer precision fabrication process (inspired by printed circuit board manufacturing) that can create functional 3D mechanisms by folding 2D layers of materials which may be structural, flexible, adhesive, or conductive. Such an approach enables actuation, sensing, and circuitry to be directly integrated with the articulating features by selecting the appropriate materials during the layer-by-layer manufacturing process. To demonstrate the efficacy of this technology, we use it to fabricate three modular robotic components at the millimeter-scale: (1) sensors, (2) mechanisms, and (3) actuators. These modules could potentially be implemented into transendoscopic systems, enabling bilateral grasping, retraction and cutting, and could potentially mitigate challenging MIS interventions performed via endoscopy or flexible means. This research lays the ground work for new mechanism, sensor and actuation technologies that can be readily integrated via new millimeter-scale layer-by-layer manufacturing approaches.
Background Recent advances in wearable robotic devices have demonstrated the ability to reduce the metabolic cost of walking by assisting the ankle joint. To achieve greater gains in the future it will be important to determine optimal actuation parameters and explore the effect of assisting other joints. The aim of the present work is to investigate how the timing of hip extension assistance affects the positive mechanical power delivered by an exosuit and its effect on biological joint power and metabolic cost during loaded walking. In this study, we evaluated 4 different hip assistive profiles with different actuation timings: early-start-early-peak (ESEP), early-start-late-peak (ESLP), late-start-early-peak (LSEP), late-start-late-peak (LSLP).
Methods Eight healthy participants walked on a treadmill at a constant speed of 1.5 m · s-1 while carrying a 23 kg backpack load. We tested five different conditions: four with the assistive profiles described above and one unpowered condition where no assistance was provided. We evaluated participants’ lower limb kinetics, kinematics, metabolic cost and muscle activation.
Results The variation of timing in the hip extension assistance resulted in a different amount of mechanical power delivered to the wearer across conditions; with the ESLP condition providing a significantly higher amount of positive mechanical power (0.219 ± 0.006 W · kg-1) with respect to the other powered conditions. Biological joint power was significantly reduced at the hip (ESEP and ESLP) and at the knee (ESEP, ESLP and LSEP) with respect to the unpowered condition. Further, all assistive profiles significantly reduced the metabolic cost of walking compared to the unpowered condition by 5.7 ± 1.5 %, 8.5 ± 0.9 %, 6.3 ± 1.4 % and 7.1 ± 1.9 % (mean ± SE for ESEP, ESLP, LSEP, LSLP, respectively).
Conclusions The highest positive mechanical power delivered by the soft exosuit was reported in the ESLP condition, which showed also a significant reduction in both biological hip and knee joint power. Further, the ESLP condition had the highest average metabolic reduction among the powered conditions. Future work on autonomous hip exoskeletons may incorporate these considerations when designing effective control strategies.
Light-Intensity Modulated (LIM) force sensors are seeing increasing interest in the field of surgical robotics and flexible systems in particular. However, such sensing modalities are notoriously susceptible to ambient effects such as temperature and environmental irradiance which can register as false force readings. We explore machine learning techniques to dynamically compensate for environmental biases that plague multi-axis optoelectronic force sensors. In this work, we fabricate a multisensor: three-axis LIM force sensor with integrated temperature and ambient irradiance sensing manufactured via a monolithic, origami-inspired fabrication process called printed-circuit MEMS. We explore machine learning regression techniques to compensate for temperature and ambient light sensitivity using on-board environmental sensor data. We compare batch-based ridge regression, kernelized regression and support vector techniques to baseline ordinary least-squares estimates to show that on-board environmental monitoring can substantially improve sensor force tracking performance and output stability under variable lighting and large (>100C) thermal gradients. By augmenting the least-squares estimate with nonlinear functions describing both environmental disturbances and cross-axis coupling effects, we can reduce the error in Fx, Fy and Fz by 10%, 33%, and 73%, respectively. We assess viability of each algorithm tested in terms of both prediction accuracy and computational overhead, and analyze kernel-based regression for prediction in the context of online force feedback and haptics applications in surgical robotics. Finally, we suggest future work for fast approximation and prediction using stochastic, sparse kernel techniques.
Carrying load alters normal walking, imposes additional stress to the musculoskeletal system, and results in an increase in energy consumption and a consequent earlier onset of fatigue. This phenomenon is largely due to increased work requirements in lower extremity joints, in turn requiring higher muscle activation. The aim of this work was to assess the biomechanical and physiological effects of a multi-joint soft exosuit that applies assistive torques to the biological hip and ankle joints during loaded walking.
Severe skeletal muscle injuries are common and can lead to extensive fibrosis, scarring, and loss of function. Clinically, no therapeutic intervention exists that allows for a full functional restoration. As a result, both drug and cellular therapies are being widely investigated for treatment of muscle injury. Because muscle is known to respond to mechanical loading, we investigated instead whether a material system capable of massage-like compressions could promote regeneration. Magnetic actuation of biphasic ferrogel scaffolds implanted at the site of muscle injury resulted in uniform cyclic compressions that led to reduced fibrous capsule formation around the implant, as well as reduced fibrosis and inflammation in the injured muscle. In contrast, no significant effect of ferrogel actuation on muscle vascularization or perfusion was found. Strikingly, ferrogel-driven mechanical compressions led to enhanced muscle regeneration and a ∼threefold increase in maximum contractile force of the treated muscle at 2 wk compared with no-treatment controls. Although this study focuses on the repair of severely injured skeletal muscle, magnetically stimulated bioagent-free ferrogels may find broad utility in the field of regenerative medicine.
The innovation in surgical robotics has seen a shift toward flexible systems that can access remote locations inside the body. However, a general reliance on the conventional fabrication techniques ultimately limits the complexity and the sophistication of the distal implementations of such systems, and poses a barrier to further innovation and widespread adoption. In this paper, we present a novel, self-assembling force sensor manufactured using a composite lamination fabrication process, wherein linkages pre-machined in the laminate provide the required degrees-of-freedom and fold patterns to facilitate self-assembly. Using the purely 2-D fabrication techniques, the energy contained within a planar elastic biasing element directly integrated into the laminate is released post-fabrication, allowing the sensor to self-assemble into its final 3-D shape. The sensors are batch-fabricated, further driving down the production costs. The transduction mechanism relies on the principle of light intensity modulation, which allows the sensor to detect axial forces with millinewton-level resolution. The geometry of the sensor was selected based on the size constraints inherent in minimally invasive surgery, as well as with a specific focus on optimizing the sensor's linearity. The sensor is unique from the fiber-based force sensors in that the emitter and the detector are encapsulated within the sensor itself. The bare sensor operates over a force range of 0-200 mN, with a sensitivity of 5 V/N and a resolution of 0.8 mN. The experimental results show that the sensor's stiffness can be tuned using a thicker material for the spring layer and/or encapsulation/integration with soft materials. The empirical validation shows that the sensor has the sensitivity and the resolution necessary to discern the biologically relevant forces in a simulated cannulation task.
Introduction: Inclined walking while carrying a loaded backpack induces fatigue, which may destabilize gait and lead to injury. Stochastic resonance (SR) technology has been used to stabilize spatiotemporal gait characteristics of elderly individuals but has not been tested on healthy recreational athletes. Herein, we determined if sustained vigorous walking on an inclined surface while carrying a load destabilizes gait and if SR has a further effect.
Methods: Participants were fitted with a backpack weighing 30% of their body weight and asked to walk at a constant self-selected pace while their feet were tracked using an optical motion capture system. Their shoes were fitted with SR insoles that were set at 90% of the participant’s sensory threshold. The treadmill incline was increased every 5 min until volitional exhaustion after which the treadmill was returned to a level grade. SR stimulation was turned ON and OFF in a pairwise random fashion throughout the protocol. Spatiotemporal gait characteristics were calculated when SR was ON and OFF for the BASELINE period, the MAX perceived exertion period, and the POST period.
Results: Vigorous activity increases variability in the rhythmic stepping (stride time and stride length) and balance control (double support time and stride width) mechanisms of gait. Overall, SR increased stride width variability by 9% before, during, and after a fatiguing exercise.
Conclusion: The increased stride time and stride length variability may compromise the stability of gait during and after vigorous walking. However, participants may compensate by increasing double support time and stride width variability to maintain their stability under these adverse conditions. Furthermore, applying SR resulted in an additional increase of stride width variability and may potentially improve balance before, during, and after adverse walking conditions.