Exosuits show much promise as a method for augmenting the body with lightweight, portable, and compliant wearable systems. We envision that such systems can be further refined so that they can be sufficiently low profile to fit under a wearer's existing clothing. Our focus is on creating an assistive device that provides a fraction of the nominal biological torques and does not provide external load transfer. In early work, we showed that the system can substantially maintain normal biomechanics and positively affect a wearer's metabolic rate. Many basic fundamental research and development challenges remain in actuator development, textile innovation, soft sensor development, human-machine interface (control), biomechanics, and physiology, which provides fertile ground for academic research in many disciplines. While we have focused on gait assistance thus far, numerous other applications are possible, including rehabilitation, upper body support, and assistance for other motions. We look forward to a future where wearable robots provide benefits for people across many areas of our society.
Soft sensors comprising a flexible matrix with embedded circuit elements can undergo large deformations while maintaining adequate performance. These devices have attracted considerable interest for their ability to be integrated with the human body and have enabled the design of skin-like health monitoring devices, sensing suits, and soft active orthotics. Numerical tools are needed to facilitate the development and optimization of these systems. In this letter, we introduce a 3D finite element-based numerical tool to simultaneously characterize the mechanical and electrical response of fluid-embedded soft sensors of arbitrary shape, subjected to any loading. First, we quantitatively verified the numerical approach by comparing simulation and experimental results of a dog-bone shaped sensor subjected to uniaxial stretch and local compression. Then, we demonstrate the power of the numerical tool by examining a number of different loading conditions. We expect this work will open the door for further design of complex and optimal soft sensors.
Cell delivery to the infarcted heart has emerged as a promising therapy, but is limited by very low acute retention and engraftment of cells. The objective of this study was to compare a panel of biomaterials to evaluate if acute retention can be improved with a biomaterial carrier. Cells were quantified post-implantation in a rat myocardial infarct model in five groups (n = 7–8); saline injection (current clinical standard), two injectable hydrogels (alginate, chitosan/β-glycerophosphate (chitosan/ß-GP)) and two epicardial patches (alginate, collagen). Human mesenchymal stem cells (hMSCs) were delivered to the infarct border zone with each biomaterial. At 24 h, retained cells were quantified by fluorescence. All biomaterials produced superior fluorescence to saline control, with approximately 8- and 14-fold increases with alginate and chitosan/β-GP injectables, and 47 and 59-fold increases achieved with collagen and alginate patches, respectively. Immunohistochemical analysis qualitatively confirmed these findings. All four biomaterials retained 50–60% of cells that were present immediately following transplantation, compared to 10% for the saline control. In conclusion, all four biomaterials were demonstrated to more efficiently deliver and retain cells when compared to a saline control. Biomaterial-based delivery approaches show promise for future development of efficient in vivo delivery techniques.
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.
This article describes the development of the Soft Robotics Toolkit, a set of open access resources to support the design, fabrication, modeling, characterization, and control of soft robotic devices. The ultimate aim of the toolkit is to support researchers in building upon each other's work, and thereby advance the field of soft robotics. An additional aim is to support educators and encourage students to pursue careers in engineering and science by making the resources as accessible as possible. The toolkit was developed and refined through a series of pilot studies and user tests. Specifically, the resources were used by students in a project-based medical device design course; volunteers from a variety of backgrounds tested the toolkit and provided feedback, and soft robotics researchers used the collection of resources and contributed to its development. Throughout all user studies, qualitative data were collected and used to guide improvements to the toolkit. This process of testing and refinement has resulted in a website containing design documentation describing general hardware control platforms and specific soft robotic component designs. The online documentation includes downloadable computer-aided design (CAD) files, detailed multimedia protocols for the fabrication of soft devices, tutorials and scripts for modeling and analyzing soft actuators and sensors, and source code for controlling soft devices. Successive iterations of qualitative data gathering and redesign have confirmed that the toolkit documentation is sufficiently detailed to be useful for researchers from a wide range of backgrounds. To date, the focus of the toolkit has primarily been fluid-actuated robotic systems, but the plan is to expand it to support a wider range of soft robotic-enabling technologies. The toolkit is intended as a community resource, and all researchers working in this field are invited to guide its future development by providing feedback and contributing new content.
Wearable robots based on soft materials will augment mobility and performance of the host without restricting natural kinematics. Such wearable robots will need soft sensors to monitor the movement of the wearer and robot outside the lab. Until now wearable soft sensors have not demonstrated significant mechanical robustness nor been systematically characterized for human motion studies of walking and running. Here, we present the design and systematic characterization of a soft sensing suit for monitoring hip, knee, and ankle sagittal plane joint angles. We used hyper-elastic strain sensors based on microchannels of liquid metal embedded within elastomer, but refined their design with the use of discretized stiffness gradients to improve mechanical durability. We found that these robust sensors could stretch up to 396% of their original lengths, would restrict the wearer by less than 0.17% of any given joint’s torque, had gauge factor sensitivities of greater than 2.2, and exhibited less than 2% change in electromechanical specifications through 1500 cycles of loading–unloading. We also evaluated the accuracy and variability of the soft sensing suit by comparing it with joint angle data obtained through optical motion capture. The sensing suit had root mean square (RMS) errors of less than 5° for a walking speed of 0.89 m/s and reached a maximum RMS error of 15° for a running speed of 2.7 m/s. Despite the deviation of absolute measure, the relative repeatability of the sensing suit’s joint angle measurements were statistically equivalent to that of optical motion capture at all speeds. We anticipate that wearable soft sensing will also have applications beyond wearable robotics, such as in medical diagnostics and in human–computer interaction.
A class of soft actuated materials that can achieve lifelike motion is presented. By embedding pneumatic actuators in a soft material inspired by a biological muscle fibril architecture, and developing a simple finite element simulation of the same, tunable biomimetic motion can be achieved with fully soft structures, exemplified here by an active left ventricle simulator.
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.
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.
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.
Finger therapy exercises, which include table-top, proximal-interphalangeal blocking, straight-fist, distal-interphalangeal blocking, hook-fist and fist exercises, are important for maintaining hand mobility and preventing development of tendon adhesions in post-operative hand-injury patients. Continuous passive motion devices act as an adjunct to the therapist in performing therapy exercises on patients, however current devices are unable to recreate these exercises well. The current study aimed to design and evaluate a finger exercise device that reproduces the therapy exercises, by adopting a cable-actuated flexion and spring-return extension mechanism. The device comprises of phalanx interface attachments, connected by palmar-side cables to spooling actuators and linked by dorsal-side extension springs to provide passive return. Two designs were tested, whereby the springs had similar (Design 1) or different stiffnesses (Design 2). The device was donned onto a model hand and actuated into the desired therapy postures. Our findings indicated that Design 1 is able to recreate table-top, straight-fist and fist exercises, while Design 2 is capable of further replicating distal-interphalangeal blocking, proximal-interphalangeal blocking and hook-fist exercises. Considering that these therapy exercises have not yet been well-replicated in current devices, developing a new device that reproduces the exercises will be beneficial for post-operative rehabilitation of patients.
Soft robots actuated by inflation of a pneumatic network (a “pneu-net”) of small channels in elastomeric materials are appealing for producing sophisticated motions with simple controls. Although current designs of pneu-nets achieve motion with large amplitudes, they do so relatively slowly (over seconds). This paper describes a new design for pneu-nets that reduces the amount of gas needed for inflation of the pneu-net, and thus increases its speed of actuation. A simple actuator can bend from a linear to a quasi-circular shape in 50 ms when pressurized at ΔP = 345 kPa. At high rates of pressurization, the path along which the actuator bends depends on this rate. When inflated fully, the chambers of this new design experience only one-tenth the change in volume of that required for the previous design. This small change in volume requires comparably low levels of strain in the material at maximum amplitudes of actuation, and commensurately low rates of fatigue and failure. This actuator can operate over a million cycles without significant degradation of performance. This design for soft robotic actuators combines high rates of actuation with high reliability of the actuator, and opens new areas of application for them.