Recent work has shown that exoskeletons con-trolled through data-driven methods can dynamically adapt assistance to various tasks for healthy young adults. However, applying these methods to populations with neuromotor gait deficits, such as post-stroke hemiparesis, is challenging. This is due not only to high population heterogeneity and gait variability but also to a lack of post-stroke gait datasets to train accurate models. Despite these challenges, data-driven methods offer a promising avenue for control, potentially allowing exoskeletons to function safely and effectively in unstructured community settings. This work presents a first step towards enabling adaptive plantarflexion and dorsiflexion assistance from data-driven torque estimation during post-stroke walking. We trained a multi-task Temporal Convolutional Network (TCN) using collected data from four post-stroke participants walking on a treadmill (R2of 0.74 ± 0.13). The model uses data from three inertial measurement units (IMU) and was pretrained on healthy walking data from 6 participants. We implemented a wearable prototype for our ankle torque estimation approach for exoskeleton control and demonstrated the viability of real-time sensing, estimation, and actuation with one post-stroke participant.

The Fugl Meyer Assessment (FMA) is a widely-used assessment for tracking motor function recovery post-stroke. Due to the limited access to rehabilitation, there exists a need for remote and automated assessment solutions. Wearable sensors and data-driven methods have shown promise for enabling automatic upper extremity FMA (FMA-UE) estimation, but minimizing user input motion and aligning with current clinical activities will aid the adoption of sensor-based assessments. In this work, we present an FMA-UE estimator which can make score predictions for a key subset of the assessment (70$\% $ of all items) using data from inertial measurement units (IMUs) placed on the arms and the trunk from three volitional reaching motions representative of functional daily activities. We collected a dataset of eleven stroke participants performing a subset of FMA-UE, and three reaching motions. The FMA-UE of each participant was assessed by an occupational therapist providing the labeled score for the training data. The estimator was trained on windowed data during FMA-UE motions and was able to make score estimates from reaching motions. Through leave-one-subject-out cross validation, the estimator achieved a normalized RMSE of 7$\% $, which is comparable to or below the established minimal clinically important difference and minimal detectable change of FMA-UE of post-stroke individuals. Comparison experiments of various model designs also revealed the importance of trunk-based features inspired by compensation strategies common post stroke and features extracted from the hand sensor. The proposed estimator has the potential to broaden the possibility of automatic assessment via wearable sensors.

Community-based locomotor training post-stroke has shown improvements in independent ambulation by increasing dose, intensity, and specificity of walking practice. Robotic ankle exoskeletons hold the potential to facilitate continued rehabilitation at home, but understanding what aspects of the design are most relevant for successful translation to the community presents a challenge. Here, we design a portable rigid ankle exoskeleton to use as a research platform for investigating the effect of assistance on post-stroke gait during overground, community-based walking. We first test our device with stroke survivors and validate its potential for future community use. We then present a systematic method for quantifying power transmission losses at each transmission stage from the battery to the wearer, using data gathered from walking trials with healthy participants. Our evaluation method revealed inefficiencies in power transfer at the interface level, likely resulting from the compliance in the structural components of the system, which motivates future redesign considerations. Overall, our method provides a framework to identify and characterize the components that must be redesigned to lower exoskeleton weight and maximize performance.

Soft, wearable systems hold promise for a wide variety of new or enhanced applications in the realm of human-computer interaction, physiological monitoring, wear-able robotics, and a host of other human-centric devices. Soft sensor systems have been developed concurrently in order to allow these wearable systems to respond intelligently with their surroundings. A recently reported sensing mechanism based on the strain-mediated contact in anisotropically resistive structures (SCARS) is an attractive solution due to its high sensing resolution, low-profile nature, and high mechanical resilience. Furthermore, the resistance-based output provides a simple electronic readout, facilitating its use in a wide variety of applications. However, previous iterations of the sensing mech-anism have exhibited stress relaxation and hysteretic behaviors that limit the scope of its use. Here, we report an iteration of the SCARS mechanism that uses silicone-based materials with low mechanical loss in order to improve the sensor signal stability and bandwidth. A new fabrication approach is developed which permits the incorporation of a liquid elastomer adhesive layer while also preserving the SCARS sensing functionality. The silicone-based SCARS sensors exhibited fast stress relaxation response (< 1 s) and reduced cyclic drift properties by more than half that of previously reported designs. A physiological monitoring demonstration is presented, validating that the new sensor design is mechanically resilient to such applications and has potential for use in real-world wearable use cases.

The papers in this special section focus on the development and applications supported by wearable robots. Wearable powered robots may be used for functional substitution in patients suffering from motor disorders, rehabilitation, assistance, and strength augmentation. Despite recent technological and scientific achievements, more research is needed to realize the promise of intuitive, easy-to-wear, safe, and effective wearable robots

Soft strain sensors have been explored as an unobtrusive approach for wearable motion tracking. However, accurate tracking of multi degree-of-freedom (DOF) noncyclic joint movements remains a challenge. This paper presents a soft sensing shirt for tracking shoulder kinematics of both cyclic and random arm movements in 3 DOFs: adduction/abduction, horizontal flexion/extension, and internal/external rotation. The sensing shirt consists of 8 textile-based capacitive strain sensors sewn around the shoulder joint that communicate to a customized readout electronics board through sewn micro-coaxial cables. An optimized sensor design includes passive shielding and demonstrates high linearity and low hysteresis, making it suitable for wearable motion tracking. In a study with a single human subject, we evaluated the tracking capability of the integrated shirt in comparison with a ground truth optical motion capture system. An ensemble-based regression algorithm was implemented in post-processing to estimate joint angles and angular velocities from the strain sensor data. Results demonstrated root mean square errors (RMSEs) less than 4.5° for joint angle estimation and normalized root mean square errors (NRMSEs) less than 4% for joint velocity estimation. Furthermore, we applied a recursive feature elimination (RFE)-based sensor selection analysis to down select the number of sensors for future shirt designs. This sensor selection analysis found that 5 sensors out of 8 were sufficient to generate comparable accuracies.

Exosuits can reduce metabolic demand and improve gait. Controllers explicitly derived from biological mechanisms that reflect the user's joint or muscle dynamics should in theory allow for individualized assistance and enable adaptation to changing gait. With the goal of developing an exosuit control strategy based on muscle power, we present an approach for estimating, at real time rates, when the soleus muscle begins to generate positive power. A low-profile ultrasound system recorded B-mode images of the soleus in walking individuals. An automated routine using optical flow segmented the data to a normalized gait cycle and estimated the onset of concentric contraction at real-time rates (~130Hz). Segmentation error was within 1% of the gait cycle compared to using ground reaction forces. Estimation of onset of concentric contraction had a high correlation (R2=0.92) and an RMSE of 2.6% gait cycle relative to manual estimation. We demonstrated the ability to estimate the onset of concentric contraction during fixed speed walking in healthy individuals that ranged from 39.3% to 45.8% of the gait cycle and feasibility in two persons post-stroke walking at comfortable walking speed. We also showed the ability to measure a shift in onset timing to 7% earlier when the biological system adapts from level to incline walking. Finally, we provided an initial evaluation for how the onset of concentric contraction might be used to inform exosuit control in level and incline walking.

Recent human-in-the-loop (HIL) optimization studies using wearable devices have shown an improved average metabolic reduction by optimizing a small number of control parameters during short-duration walking experiments. However, the slow metabolic dynamics, high measurement noise, and experimental time constraints create challenges for increasing the number of control parameters to be optimized. Prior work applying gradient descent and Bayesian optimization to this problem have decoupled metabolic estimation and control parameter selection using fixed estimation intervals, which imposes a hard limit on the number of parameter evaluations possible in a given time budget. In this work, we take a different approach that couples estimation and parameter selection, allowing the algorithm to spend less time on refining the metabolic estimates for parameters that are unlikely to improve performance over the best observed values. Our approach uses a Kalman filter-based metabolic estimator to formulate an optimal stopping problem during the data acquisition step of standard Bayesian optimization. Performance was analyzed in numerical simulations and in pilot human subject testing with two subjects that involved optimizing six control parameters of a single-joint exosuit and four parameters of a multi-joint exosuit.

This paper presents a fully-integrated soft robotic glove with multi-articular textile actuators, custom soft sensors, and an intuitive state machine intent detection controller. We demonstrate that the pressurized actuators can generate motion and force comparable to natural human fingers through bench-top testing. We apply textile-elastomer capacitive sensors to the glove to track finger flexion via strain and detect contact with objects via force. Intuitive user control is achieved via a state machine controller based on signals from the integrated sensors to detect relative changes in hand-object interactions. Results from an initial evaluation with 3 participants with spinal cord injury (SCI), of varied injury levels and years since injury, wearing and controlling the glove show an average of 87% improvement in grasping force, and improvements in functional assessments for participants with recent injuries. A significant variation in response suggests further investigation is required to understand the adaptation needed across different injury levels and durations since injury. Additionally, we evaluate the controller and find an average of 3 seconds from user initiations to completed grasps, and 10% inadvertent grasp triggers and no false releases when objects are held.

Robotic artificial muscles are a subset of artificial muscles that are capable of producing biologically inspired motions useful for robot systems, i.e., large power-to-weight ratios, inherent compliance, and large range of motions. These actuators, ranging from shape memory alloys to dielectric elastomers, are increasingly popular for biomimetic robots as they may operate without using complex linkage designs or other cumbersome mechanisms. Recent achievements in fabrication, modeling, and control methods have significantly contributed to their potential utilization in a wide range of applications. However, no survey paper has gone into depth regarding considerations pertaining to their selection, design, and usage in generating biomimetic motions. In this paper, we discuss important characteristics and considerations in the selection, design, and implementation of various prominent and unique robotic artificial muscles for biomimetic robots, and provide perspectives on next-generation muscle-powered robots.

The development of soft, compliant force sensors is greatly sought after in areas such as soft robotics and prosthetics. Nevertheless, solutions for measuring forces in multiple axes, while being mechanically compliant, have been few and far between. Here we present a compliant sensor able to detect forces tangential and normal to the sensor surface. The transduction mechanism is based on the deformation of laser-machined carbon fiber composite (CFC) micro-scale meanders, encapsulated within elastomers layers. Strains in the elastomer are transmitted to the meanders, causing changes in the electrical resistance of the sensor contact mechanics. Configuring the meanders in a radial pattern, segmenting them into quadrants (two antagonist pairs) and biasing the center of the sensor out-of-plane enables detection of forces in multiple axis via differential measurement. Sensors were manufactured using a custom fabrication process and exhibited high mechanical compliance with a very low form factor. The sensors were experimentally characterized and demonstrated large differential changes in resistance (up to 26 kΩ for tangential forces applied to the sensor surface). We integrated our sensor onto a soft robotic gripper finger and demonstrated the ability to detect changes in friction at the actuator surface, thus demonstrating their potential for real world applications.

Hemiparetic gait after stroke is typically asymmetric and energetically inefficient. A major contributor to walking deficits is impaired paretic ankle function. Impaired paretic ankle plantarflexion (PF) reduces forward propulsion symmetry and impaired paretic ankle dorsiflexion (DF) diminishes ground clearance during swing. We have developed soft wearable robots (soft exosuits) to assist paretic PF and DF during walking after stroke. Through experimental studies with poststroke patients, we have demonstrated that exosuits can improve forward propulsion symmetry and ground clearance in walking, ultimately reducing the metabolic cost of walking. This paper presents an optimized soft exosuit aimed at use in clinical gait training for patients poststroke. The optimized exosuit is lightweight, easy to don and doff, and capable of efficiently delivering mechanical assistance to the paretic ankle. This paper focuses on the optimized controller that can deliver well-timed consistent ankle assistance to patients. A preliminary study was performed using this exosuit with three poststroke patients with heterogeneous gait patterns. Results showed that compared to a previously published controller, more consistent assistive force profiles could be delivered to individuals poststroke while consuming 50% less electrical power. Additionally, a preliminary biomechanical assessment was performed during overground walking.

We present an autonomous and portable hip-only soft exosuit, for augmenting human walking and running that assists hip extension by delivering peak forces of 300N to the user. Different fixed assistance profiles for walking and running were applied based on an online classification algorithm. The approach is based on the biomechanical understanding that the center of mass potential energy fluctuations during walking and running are out of phase. Specifically, we monitor the vertical acceleration with an abdomen-mounted IMU at the moment of maximum hip extension. Validation is demonstrated with six subjects on the treadmill and with eight subjects outdoors. Our results demonstrated a 99.99% accuracy on average over the fourteen participants for various speeds (0.5 - 4m/s), slopes (-10 -20%), treadmill and overground terrain, loaded (13.6 kg) and unloaded, Exo On and Exo Off conditions, and different shoe types. Results from an evaluation outdoors overground on the energetics of eight subjects demonstrated a significant reduction for running when comparing Exo On to No Exo (3.9%) and for walking and running when comparing Exo On to Exo Off (12.2% and 8.2% respectively). This study represents the first demonstration of an autonomous wearable robot reducing the energy cost of running. Significant variation in response across subjects was observed, highlighting further improvements may be possible via assistance profile individualization with human-in-the-Ioop optimization.

Soft exosuits are a new approach for assisting with human locomotion, which applies assistive torques to the wearer through functional apparel. In this paper, we present a new version of autonomous multi-joint soft exosuit for gait assistance, particularly designed for overground walking. The soft exosuit assists with ankle plantarflexion, hip flexion, and hip extension, equally distributing the forces between ankle plantarflexion and hip flexion. A mobile actuation system was developed to generate high assistive forces, and Bowden cables are used to transmit the forces to the exosuit. A sensor harness connects two load cells and three IMU s per leg that are used to measure real-time data for a controller that commands desired force profiles as a function of the walking cycle. In addition, a control adaptation method was developed which adjusts control parameters while walking on irregular surfaces. In preliminary studies, the proposed method substantially improved the force consistency while walking over uneven terrain. Specifically, the number of steps where the peak force deviated from the target force decreased from 100 to 57 out of 250 steps, and RMS error on the peak force decreased from 90.0 N to 76.6 N with respect to 300 N target force. Also, a two-subject case study on country-course walking demonstrated the potential of this soft exosuit to improve human energy economy while walking overground.

Soft robotic devices have been utilized in a number of biomedical applications involving human interaction. An emerging opportunity for soft robotic wearable devices is in mechanotherapeutic applications for the recovery and regeneration of soft tissues. Previous studies have implied that judicious force application during mechanotherapy plays an important role in the functional outcome of tissue regeneration. In this paper, we propose soft robotic devices with closed-loop force control to precisely manipulate muscular tissue. The developed devices incorporate fully soft sensors and actuators using textile-based materials and fabrication methods. The closed-loop force control system is demonstrated in bench studies to regulate massage-magnitude forces at frequencies akin to those expected in manual mechanotherapy practices. Testing of the device on human limbs demonstrates the precision and accuracy of the closed-loop force control methodology across different body shapes and types. When commanded to regulate sinusoidal force profiles (with amplitudes of 30N, 45N and 60N), the soft robotic force control device could regulate peak compressive loads to within 0.7N of the desired force. Conversely, open-loop pressure-based control resulted in up to +/-6.6N force tracking variability between participants. A soft robotic system with independently actuatable modules was also fabricated to demonstrate force-controlled actuation patterns to mimic manual massage techniques.

Soft actuators are ideal candidates for wearable biomedical devices, their inherent compliance, robustness, lightweight and the possibility to be washable take advantage over rigid actuators. Thus, a soft pneumatic fabric-polymer bending actuator as a base component for a robotic device for lymphedema treatment is reported in this work. The actuator is composed of two mechanical elements, one made of fabric and the other one made of a hyperelastic polymer which is stuck on the fabric element. The fabric element is designed and fabricated with a curved shape longer than the polymer element, that is a hyperelastic beam. To assemble both elements, the fabric element was folded before sticking in order to match the length of the polymer beam. Once the air is pumped into the fabric, it bends towards its original curved shape. Once the air is removed, the hyperelastic beam allows the actuator to recover its initial position. This actuator is capable of exerting compression and lateral force on a human arm mimicking manual lymphatic drainage. A mathematical model is presented which is in good agreement with the experimental data, it could serve to predict the actuator motion. An end-tip free bending displacement of about 2.2 cm and a bending force of about 0.35 N were achieved at 12.5 kPa. A proof-of-concept system for lymphedema treatment is presented as well.

Nascent endoscopic therapeutic procedures, such as endoscopic submucosal dissection, enable unparalleled access to and removal of mid-size cancerous neoplasia from within the gastrointestinal tract. However, the remote locations of these lesions often incur substantial distal dexterity which imparts appreciable cognitive loading on the clinician and opens up the possibility of adverse events such as intestinal perforation due to limited dexterity and a lack of sensory feedback. In this work, we introduce a mm-scale, tip-mounted robotic system, EndoMODRA (Endoscopic Module for On-Demand Robotic Assistance), which interfaces with commercially-available endoscopic tools and provides additional dexterity and feedback sensing using on-board actuators and sensors, decoupling tool motion from endoscope motion. Leveraging alternative high-energy-density actuation strategies and monolithic, printed-circuit-inspired manufacturing processes, all actuation and sensing is fully contained within the distally-mounted module, obviating the need for a continuous mechanical transmission to a proximal motor package. We develop a fuzzy-tuned PID/PWM controller for closing the loop distally to enable closed-loop position-controlled trajectory execution using onboard actuation and sensing, realizing fully -distal loop closure in an endoscope-mounted robotic module with no proximal actuation or sensing component. Controller performance is validated on a fully-integrated module with on-board sensing, demonstrating the ability to execute pre-determined trajectories as well as real-time rate-based teleoperation.

`Snap-On' robotic modules that can integrate distally with existing commercially-available endoscopic equipment have the potential to provide new capabilities such as enhanced dexterity, bilateral manipulation and feedback sensing with minimal disruption of the current clinical workflow. However, the desire for fully-distal integration of sensors and actuators and the resulting form factor requirements preclude the use of many off-the-shelf actuators capable of generating the relevant strokes and forces required to interact with tools and tissue. In this work, we investigate the use of millimeter-scale, optimally-packed helical shape memory alloy (SMA) actuators in an antagonistic configuration to provide distal actuation without the need for a continuous mechanical coupling to proximal, off-board actuation packages to realize a truly plug-and-play solution. Using phenomenological modeling, we design and fabricate antagonistic helical SMA pairs and implement them in an at-scale roboendoscopic module to generate strokes and forces necessary for deflecting tools passed through the endoscope working port, thereby providing a controllable robotic `wrist' inside the body to otherwise passive flexible tools. Bandwidth is drastically improved through the integration of targeted fluid cooling. The integrated system can generate maximum lateral forces of 10N and demonstrates an additional 96 degrees of distal angulation, expanding the reachable workspace of tools passed through a standard endoscope.

Flexible endoscopes are still the gold standard in most natural orifice translumenal endoscopic surgery (NOTES) procedures; however their flexibility (necessary for navigating through the GI tract) limits their capabilities in terms of distal manipulation and stability. We propose a deployable endoscopic add-on aimed at locally counteracting forces applied at the tip of an endoscope. We analyze different designs: a fully soft version and two hybrid soft-folded versions. The hybrid designs exploit either an inextensible structure pressurized by a soft actuator or the stiffness provided by the unfolded “magic cube” origami structure. We focus on the fabrication and experimental characterization of the proposed structures and present some preliminary designs and integration strategies to mount them on top of current flexible endoscopes.

Wearable robotic systems which aid or enhance human performance are the subject of substantial ongoing research efforts. Soft exosuits to assist with walking represent one class of system that leverage textiles and apparel to provide a lightweight and nonrestrictive means to interface to the lower extremity and apply assistive joint torques via a cable that applies a force across a biological joint. Current embodiments of the soft exosuit use off-the-shelf load cells attached to the distal end of a Bowden cable to measure and control the delivered force. As these systems evolve, we envision replacing all rigid components with compliant, textile-based components. Here we present a new force sensing concept suitable for exosuit applications. The approach is based on micro-machined carbon fiber composite structures encapsulated in elastomer materials as the transducer element, and high-strength, stiff textiles as the load bearing element. The transduction mechanism uses the Poisson effect in the encapsulating elastomer to create electrical contact between the carbon fiber structures. This method allows the sensor to be sensitive in tension while remaining insensitive to bending deformation. We fabricate a prototype sensor capable of detected forces up to 300 N, yet weighing just 2.15 g. The compliant nature of the materials used in fabrication allow the sensor to be flexible. The sensor output is qualitatively very repeatable, yet exhibits moderate drift at peak load. However this drift begins to stabilize over the test duration. These preliminary results demonstrate the promising potential of this sensor technology for soft exosuit systems.

In this paper, we present a design and control approach of a modular off-board actuation system with mono-articular hip exosuit, enabling the instantaneous assistive profile modification of magnitude, shape, and timing. The off-board system consists an actuation unit with two degrees of freedom that can transmit forces to our soft exosuit via Bowden cables. To perform accurate force tracking and cable slack management, we implemented a switching admittance-position control approach that utilizes the advantages of both admittance and position control. In particular, feedforward models (FFMs) are added to the admittance control to compensate variability of individual kinematics, nonlinear hip exosuit stiffness and actuator transmission loss to enable a more accurate force tracking. This system allows us to track force profiles accurately and robustly under normal walking or jogging speed. The performance of force tracking was evaluated on three subjects walking on a treadmill at 1.25 m/s with various magnitude, shape, and timings of assistive profiles and jogging on a treadmill at 2.3 m/s with varied magnitude of a representative assistance profile. Results showed that assistance could be delivered reliably across different profiles. In case of walking experiments, the errors of the magnitude, RMS-E, and timing were within 2.0 N, 8.4 N, and 1.8% when varying the magnitude, shape, and timing respectively. In case of jogging experiments, the RMS-E was within 3.0 N. This system will be used for future research examining how to individualize assistive profiles for different wearers during walking and jogging.

In this paper we describe an IMU-based iterative controller for hip extension assistance where the onset timing of assistance is based on an estimate of the maximum hip flexion angle. The controller was implemented on a mono-articular soft exosuit coupled to a lab-based multi-joint actuation platform that enables rapid reconfiguration of different sensors and control strategy implementation. The controller design is motivated by a model of the suit-human interface and utilizes an iterative control methodology that includes gait detection and step-by-step actuator position profile generation to control the onset timing, peak timing, and peak magnitude of the delivered force. This controller was evaluated on eight subjects walking on a treadmill at a speed of 1.5 m/s while carrying a load of 23 kg. Results showed that assistance could be delivered reliably across subjects. Specifically, for a given profile, the average delivered force started concurrently with the timing of the maximum hip flexion angle and reached its peak timing 22.7 ± 0.63% later in the gait cycle (desired 23%) with a peak magnitude of 198.2 ± 1.6 N (desired 200 N), equivalent to an average peak torque of 30.5 ± 4.7 Nm. This control approach was used to assess the metabolic effect of four different assistive profiles. Metabolic reductions ranging from 5.7% to 8.5% were found when comparing the powered conditions with the unpowered condition. This work enables studies to assess the biomechanical and physiological responses to different assistive profiles to determine the optimal hip extension assistance during walking.

Burgeoning transendoscopic procedures, such as endoscopic submucosal dissection (ESD), provide a promising means of treating early-stage gastric neoplasia in a minimally-invasive way. However, the remote locations of these lesions, coupled with their origination in the submucosal layers of the gastrointestinal tract, often lead to extreme technical, cognitive and ergonomic challenges which combat the widespread applicability and adoption of these techniques. Among these challenges is achieving the in vivo dexterity required to retract and dissect tissue. By leveraging workspace and force data obtained through clinical studies, we developed a modular, disposable, distally-mounted actuator (an `active endcap') that can augment an endoscopist's distal dexterity in ways that are not achievable with the endoscope's built-in degrees-of-freedom. The device consists of a flexible articulating `exoskeleton' manufactured via printed-circuit MEMS (PCMEMS) which engages and deflects electrosurgical tools that are passed through the endoscopic working channel. Embedded proprioceptive sensing is implemented on-board using distributed LED/phototransistor pairs and the principle of light intensity modulation (LIM). The distal degree-of-freedom is actuated using shape memory alloy (SMA) technology, and the actuation transmission system is fully contained within a 1-inch-long end cap that can be mounted on the distal end of the endoscope, thereby obviating the need for a mechanical connection to a proximal source. Proof-of-concept tests demonstrate that the actuator adds over 50 degrees of distal articulation to existing tools and can generate 450 mN of lateral force which has been clinically determined to be sufficient for performing circumferential incisions in ESD.

The soft exosuit is a new approach for applying assistive forces over the wearer's body through load paths configured by the textile architecture. In this paper, we present a body-worn lower-extremity soft exosuit and a new control approach that can independently control the level of assistance that is provided during negative- and positive-power periods at the ankle. The exosuit was designed to create load paths assisting ankle plantarflexion and hip flexion, and the actuation system transmits forces from the motors to the suit via Bowden cables. A load cell and two gyro sensors per leg are used to measure real-time data, and the controller performs position control of the cable on a step-by-step basis with respect to the power delivered to the wearer's ankle by controlling two force parameters, the pretension and the active force. Human subjects testing results demonstrate that the controller is capable of modulating the amount of power delivered to the ankle joint. Also, significant reductions in metabolic rate (11%-15%) were observed, which indicates the potential of the proposed control approach to provide benefit to the wearer during walking.

This paper introduces a manufacturing technique which enables the integration of soft materials and soft fluidic micro-actuators in the Pop-up book MEMS paradigm. Such a technique represents a promising approach to the design and fabrication of low cost and scalable articulated mechanisms provided with sensing capabilities and on-board actuation with potential applications in the field of minimally invasive surgery. Design and integration of soft components in the rigid-flex laminates is described along with the resulting soft pop-up mechanisms realized at different scales. Prototype characterization is presented, demonstrating forces and dexterity in a range suitable for surgical applications, as well as the possibility to integrate sensing capabilities. Based on these results, a multi-articulated robotic arm is fabricated and mounted on top of an endoscope model to provide a proof of concept of simple robotic mechanisms that could be useful in a surgical scenario.

Exosuits represent a new approach for applying assistive forces to an individual, using soft textiles to interface to the wearer and transmit forces through specified load paths. In this paper we present a body-worn, multi-joint soft exosuit that assists both ankle plantar flexion and hip flexion through a multiarticular load path, and hip extension through a separate load path, at walking speeds up to 1.79m/s (4.0mph). The exosuit applies forces of 300N in the multiarticular load path and 150N in hip extension, which correspond to torques of 21% and 19% of the nominal biological moments at the ankle and hip during unloaded walking. The multi-joint soft exosuit uses a new actuation approach that exploits joint synergies, with one motor actuating the multiarticular load paths on both legs and one motor actuating the hip extension load paths on both legs, in order to reduce the total system weight. Control is accomplished by an algorithm that uses only a gyroscope at the heel and a load cell monitoring the suit tension, and is shown to adapt within a single step to changes in cadence. Additionally, the control algorithm can create slack in the suit during non-level-ground walking motions such as stepping over obstacles so that the system can be transparent to the wearer when required. The resulting system consumes 137W, and has a mass of 6.5kg including batteries.

This paper presents advancements in the design of a portable, soft robotic glove for individuals with functional grasp pathologies. The robotic glove leverages soft material actuator technology to safely distribute forces along the length of the finger and provide active flexion and passive extension. These actuators consist of molded elastomeric bladders with anisotropic fiber reinforcements that produce specific bending, twisting, and extending trajectories upon fluid pressurization. In particular, we present a method for customizing a soft actuator to a wearer's biomechanics and demonstrate in a motion capture system that the ranges of motion (ROM) of the two are nearly equivalent. The active ROM of the glove is further evaluated using the Kapandji test. Lastly, in a case study, we present preliminary results of a patient with very weak hand strength performing a timed Box-and-Block test with and without the soft robotic glove.

This paper presents the design and control of a teleoperated robotic system for dexterous micromanipulation tasks at the meso-scale, specifically open microsurgery. Robotic open microsurgery is an unexplored yet potentially a high impact area of surgical robotics. Microsurgical operations, such as microanastomosis of blood vessels and reattachment of nerve fibers, require high levels of manual dexterity and accuracy that surpass human capabilities. A 3-DoF robotic wrist is designed and built based on a spherical five-bar mechanism. The wrist is attached to a 3-axis commercial off-the-shelf linear stage, achieving a fully dexterous system. Design requirements are determined using motion data collected during a simulated microanastomosis operation. The wrist design is optimized to maximize workspace and manipulability. The system is teleoperated using a haptic device, and has the required bandwidth to replicate microsurgical motions. The system was successfully used in a micromanipulation task to stack 1 mm-diameter metal spheres. The micromanipulation system presented here may improve surgical outcomes during open microsurgery by offering better accuracy and dexterity to surgeons.

Soft fluidic actuators consisting of elastomeric matrices with embedded flexible materials are of particular interest to the robotics community because they are affordable and can be easily customized to a given application. However, the significant potential of such actuators is currently limited as their design has typically been based on intuition. In this paper, the principle of operation of these actuators is comprehensively analyzed and described through experimentally validated quasi-static analytical and finite-element method models for bending in free space and force generation when in contact with an object. This study provides a set of systematic design rules to help the robotics community create soft actuators by understanding how these vary their outputs as a function of input pressure for a number of geometrical parameters. Additionally, the proposed analytical model is implemented in a controller demonstrating its ability to convert pressure information to bending angle in real time. Such an understanding of soft multimaterial actuators will allow future design concepts to be rapidly iterated and their performance predicted, thus enabling new and innovative applications that produce more complex motions to be explored.

Lower-limb wearable robots have been proposed as a means to augment or assist the wearer's natural performance, in particular, in the military and medical field. Previous research studies on human-robot interaction and biomechanics have largely been performed with rigid exoskeletons that add significant inertia to the lower extremities and provide constraints to the wearer's natural kinematics in both actuated and non-actuated degrees of freedom. Actuated lightweight soft exosuits minimize these effects and provide a unique opportunity to study human-robot interaction in wearable systems without affecting the subjects underlying natural dynamics. In this paper, we present the design and control of a reconfigurable multi-joint actuation platform that can provide biologically realistic torques to ankle, knee, and hip joints through lower extremity soft exosuits. Two different soft exosuits have been designed to deliver assistive forces through Bowden cable transmission to the ankle and hip joints. Through human subject experiments, it is demonstrated that with a real-time admittance controller, accurate force profile tracking can be achieved during walking. The average energy delivered to the test subject was calculated while walking at 1.25 m/s and actuated with 15% of the total torque required by the biological joints. The results show that the ankle joint received an average of 3.02J during plantar flexion and that the hip joint received 1.67J during flexion each gait cycle. The efficiency of the described suit and controller in transferring energy to the human biological joints is 70% for the ankle and 48% for the hip.

In this paper we have rapidly prototyped customized, highly-sensitive, mm-scale multi-axis force sensors for medical applications. Using a composite laminate batch fabrication process with biocompatible constituent materials, we have fabricated a fully-integrated, 10×10 mm three-axis force sensor with up to 5 V/N sensitivity and RMS noise on the order of ~1.6 mN, operational over a range of -500 to 500 mN in the x- and y-axes, and -2.5 to 2.5 N in the z-axis. Custom foil-based strain sensors were fabricated in parallel with the mechanical structure, obviating the need for post-manufacturing alignment and assembly. The sensor and its custom-fabricated signal conditioning circuitry fit within a 1×1×2 cm volume to realize a fully-integrated force transduction platform with potential haptics and control applications in minimally-invasive surgical tools. The form factor, biocompatibility, and cost of the sensor and signal conditioning makes this method ideal for rapid-prototyping low-cost, mm-scale distal force sensors. Sensor performance is validated in a simulated tissue palpation task using a robotic master-slave platform.

Magnetic localization systems based on passive permanent magnets (PM) are of great interest due to their ability to provide non-contact sensing and without any power requirement for the PM. Medical procedures such as ventriculostomy can benefit greatly from real-time feedback of the inserted catheter tip. While the effects of the number of sensors on the localization accuracy in such systems has been reported, the spatial design of the sensor layout has been largely overlooked. Here in this paper, a framework for determining an optimal sensor assembly for enhanced localization performance is presented and investigated through numerical simulations and direct experiments. Two approaches are presented: one based on structured grid configuration and the other derived using Genetic Algorithms. Simulation results verified by experiments strongly suggest that the layout of the sensors not only has an effect on the localization accuracy, but also has an effect far more pronounced than improvements brought by increasing the number of sensors.

Accurately targeting multi-adjacent points (MAPs) during image-guided percutaneous procedures is challenging due to needle deflection and misalignment. The associated errors can result in inadequate treatment of cancer in the case of prostate brachytherapy, or inaccurate diagnosis during biopsy, while repeated insertions increase procedure time, radiation dose, and complications. To address these challenges, we present an image-guided robotic system capable of MAP targeting of irregularly shaped volumes after a single insertion of a percutaneous instrument. The design of the compact CT-compatible drive mechanism is based on a nested screw and screw-spline combination that actuates a straight outer cannula and a curved inner stylet that can be repeatedly straightened when retracted inside the cannula. The stylet translation and cannula rotation/translation enable a 3-D workspace to be reached with the stylet's tip. A closed-form inverse kinematics and image-to-robot registration are implemented in an image-guided system including a point-and-click user interface. The complete system is successfully evaluated with a phantom under a Siemens Definition Flash CT scanner. We demonstrate that the system is capable of MAP targeting for a 2-D shape of the letter “H” and a 3-D helical pattern with an average targeting error of 2.41 mm. These results highlight the benefit and efficacy of the proposed robotic system in seed placement during image-guided brachytherapy.

Motion sensing has played an important role in the study of human biomechanics as well as the entertainment industry. Although existing technologies, such as optical or inertial based motion capture systems, have relatively high accuracy in detecting body motions, they still have inherent limitations with regards to mobility and wearability. In this paper, we present a soft motion sensing suit for measuring lower extremity joint motion. The sensing suit prototype includes a pair of elastic tights and three hyperelastic strain sensors. The strain sensors are made of silicone elastomer with embedded microchannels filled with conductive liquid. To form a sensing suit, these sensors are attached at the hip, knee, and ankle areas to measure the joint angles in the sagittal plane. The prototype motion sensing suit has significant potential as an autonomous system that can be worn by individuals during many activities outside the laboratory, from running to rock climbing. In this study we characterize the hyperelastic sensors in isolation to determine their mechanical and electrical responses to strain, and then demonstrate the sensing capability of the integrated suit in comparison with a ground truth optical motion capture system. Using simple calibration techniques, we can accurately track joint angles and gait phase. Our efforts result in a calculated trade off: with a maximum error less than 8%, the sensing suit does not track joints as accurately as optical motion capture, but its wearability means that it is not constrained to use only in a lab.

In this paper we present a soft lower-extremity robotic exosuit intended to augment normal muscle function in healthy individuals. Compared to previous exoskeletons, the device is ultra-lightweight, resulting in low mechanical impedance and inertia. The exosuit has custom McKibben style pneumatic actuators that can assist the hip, knee and ankle. The actuators attach to the exosuit through a network of soft, inextensible webbing triangulated to attachment points utilizing a novel approach we call the virtual anchor technique. This approach is designed to transfer forces to locations on the body that can best accept load. Pneumatic actuation was chosen for this initial prototype because the McKibben actuators are soft and can be easily driven by an off-board compressor. The exosuit itself (human interface and actuators) had a mass of 3500 g and with peripherals (excluding air supply) is 7144 g. In order to examine the exosuit's performance, a pilot study with one subject was performed which investigated the effect of the ankle plantar-flexion timing on the wearer's hip, knee and ankle joint kinematics and metabolic power when walking. Wearing the suit in a passive unpowered mode had little effect on hip, knee and ankle joint kinematics as compared to baseline walking when not wearing the suit. Engaging the actuators at the ankles at 30% of the gait cycle for 250 ms altered joint kinematics the least and also minimized metabolic power. The subject's average metabolic power was 386.7 W, almost identical to the average power when wearing no suit (381.8 W), and substantially less than walking with the unpowered suit (430.6 W). This preliminary work demonstrates that the exosuit can comfortably transmit joint torques to the user while not restricting mobility and that with further optimization, has the potential to reduce the wearer's metabolic cost during walking.

The small scale of minimally-invasive surgery (MIS) presents significant challenges to developing robust, smart, and dexterous tools for manipulating millimeter and sub-millimeter anatomical structures (vessels, nerves) and surgical equipment (sutures, staples). Robotic MIS systems offer the potential to transform this medical field by enabling precise repair of these miniature tissue structures through the use of teleoperation and haptic feedback. However, this effort is currently limited by the inability to make robust and accurate MIS end effectors with integrated force and contact sensing. In this paper, we demonstrate the use of the novel Pop-Up Book MEMS manufacturing method to fabricate the mechanical and sensing elements of an instrumented MIS grasper. A custom thin-foil strain gage was manufactured in parallel with the mechanical components of the grasper to realize a fully-integrated electromechanical system in a single manufacturing step, removing the need for manual assembly, bonding and alignment. In preliminary experiments, the integrated grasper is capable of resolving forces as low as 30 mN, with a sensitivity of approximately 408 mV/N. This level of performance will enable robotic surgical systems that can handle delicate tissue structures and perform dexterous procedures through the use of haptic feedback guidance.

This paper presents preliminary results for the design, development and evaluation of a hand rehabilitation glove fabricated using soft robotic technology. Soft actuators comprised of elastomeric materials with integrated channels that function as pneumatic networks (PneuNets), are designed and geometrically analyzed to produce bending motions that can safely conform with the human finger motion. Bending curvature and force response of these actuators are investigated using geometrical analysis and a finite element model (FEM) prior to fabrication. The fabrication procedure of the chosen actuator is described followed by a series of experiments that mechanically characterize the actuators. The experimental data is compared to results obtained from FEM simulations showing good agreement. Finally, an open-palm glove design and the integration of the actuators to it are described, followed by a qualitative evaluation study.

The focus of this paper is on the design and evaluation of a robust drive mechanism intended to robotically steer a thermal ablation electrode or similar percutaneous instrument. We present the design of an improved screw-spline drive mechanism based on a profiled threaded shaft and nut that reduces the part count and simplifies manufacturing and assembly. To determine the optimal parameters for the profile shape, an analytical expression was derived that relates the tolerance between the nut and shaft to the angular backlash, which was validated using SolidWorks. We outline the forward kinematics of a steering mechanism that is based on the concept of substantially straightening a pre-curved Nitinol stylet by retracting it into a concentric outer cannula, and re-deploying it at a different position. This model was compared to data collected during targeting experiments performed in ex-vivo tissue samples where the distal tip of the stylet was repositioned in ex-vivo bovine tissue and the location of its distal tip was recorded with CT imaging. Results demonstrated that the drive mechanism operated robustly and targeting errors of less than 2mm were achieved.

Metabolic studies have shown that there is a metabolic cost associated with carrying load. Several leg exoskeletons have been developed by various groups in an attempt to augment the load carrying capability of the human. Previous research efforts have not fully exploited the passive dynamics of walking and have largely focused on fully actuated exoskeletons that are heavy with large energy requirements. In this paper, a lightweight, underactuated exoskeleton design is presented that runs in parallel to the human and supports the weight of a payload. Two exoskeleton architectures are pursued based on examining human walking data. A first architecture consists of springs at the hip, a variable impedance device at the knee, and springs at the ankle. A second architecture replaces the springs at the hip with a non-conservative actuator to examine the effect of adding power at desired instances throughout the gait cycle. Preliminary studies show that an efficient, underactuated leg exoskeleton can effectively transmit payload forces to the ground during the walking cycle

Metabolic studies have shown that there is a metabolic cost associated with carrying load (T. M. Griffen, et al., 2003). In previous work, a lightweight, underactuated exoskeleton has been described that runs in parallel to the human and supports the weight of a payload (C. J. Walsh, et al., 2006). A state-machine control strategy is written based on joint angle and ground-exoskeleton force sensing to control the joint actuation at this exoskeleton hip and knee. The joint components of the exoskeleton in the sagittal plane consist of a force-controllable actuator at the hip, a variable-damper mechanism at the knee and a passive spring at the ankle. The control is motivated by examining human walking data. Positive, non-conservative power is added at the hip during the walking cycle to help propel the mass of the human and payload forward. At the knee, the damper mechanism is turned on at heel strike as the exoskeleton leg is loaded and turned off during terminal stance to allow knee flexion. The passive spring at the ankle engages in controlled dorsiflexion to store energy that is later released to assist in powered plantarflexion. Preliminary studies show that the state machines for the hip and knee work robustly and that the onset of walking can be detected in less than one gait cycle. Further, it is found that an efficient, underactuated leg exoskeleton can effectively transmit payload forces to the ground during the walking cycle