All Publications

Textile technology for soft robotic and autonomous garments
V. Sanchez, C. Walsh, and R. Wood, “Textile technology for soft robotic and autonomous garments,” Advanced Functional Materials, vol. 31, no. 6, 2021. PDF
O. A. Araromi, et al., “Ultra-sensitive and resilient compliant strain gauges for soft machines,” Nature, vol. 587, pp. 219-224, 2020. Publisher's VersionAbstract
Soft machines are a promising design paradigm for human-centric devices and systems required to interact gently with their environment. To enable soft machines to respond intelligently to their surroundings, compliant sensory feedback mechanisms are needed. Specifically, soft alternatives to strain gauges—with high resolution at low strain (less than 5 per cent)—could unlock promising new capabilities in soft systems. However, currently available sensing mechanisms typically possess either high strain sensitivity or high mechanical resilience, but not both. The scarcity of resilient and compliant ultra-sensitive sensing mechanisms has confined their operation to laboratory settings, inhibiting their widespread deployment. Here we present a versatile and compliant transduction mechanism for high-sensitivity strain detection with high mechanical resilience, based on strain-mediated contact in anisotropically resistive structures (SCARS). The mechanism relies upon changes in Ohmic contact between stiff, micro-structured, anisotropically conductive meanders encapsulated by stretchable films. The mechanism achieves high sensitivity, with gauge factors greater than 85,000, while being adaptable for use with high-strength conductors, thus producing sensors resilient to adverse loading conditions. The sensing mechanism also exhibits high linearity, as well as insensitivity to bending and twisting deformations—features that are important for soft device applications. To demonstrate the potential impact of our technology, we construct a sensor-integrated, lightweight, textile-based arm sleeve that can recognize gestures without encumbering the hand. We demonstrate predictive tracking and classification of discrete gestures and continuous hand motions via detection of small muscle movements in the arm. The sleeve demonstration shows the potential of the SCARS technology for the development of unobtrusive, wearable biomechanical feedback systems and human–computer interfaces.
Smart Thermally Actuating Textiles
V. Sanchez, et al., “Smart Thermally Actuating Textiles,” Advanced Materials Technologies, 2020. PDF
C. Siviy, et al., “Offline Assistance Optimization of a Soft Exosuit for Augmenting Ankle Power of Stroke Survivors During Walking,” IEEE Robotics and Automation Letters, vol. 5, no. 2, 2020. PDF
R. W. Nuckols, K. Swaminathan, S. Lee, L. Awad, C. J. Walsh, and R. D. Howe, “Automated detection of soleus concentric contraction in variable gait conditions for improved exosuit control,” in IEEE International Conference on Robotics and Automation (ICRA), 2020. PDF
Y. Jin, et al., “Soft Sensing Shirt for Shoulder Kinematics Estimation,” in IEEE International Conference on Robotics and Automation (ICRA), 2020. PDF
C. Correia, et al., “Improving Grasp Function after Spinal Cord Injury with a Soft Robotic Glove,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 28, no. 6, pp. 1407-1415, 2020. PDF
C. O'Neill, et al., “Inflatable soft wearable robot for reducing therapist fatigue during upper extremity rehabilitation in severe stroke,” IEEE Robotics and Automation Letters, vol. 5, no. 3, pp. 3899-3906, 2020. PDF
D. Bautista-Salinas, et al., “Synchronization of a Soft Robotic Ventricular Assist Device to the Native Cardiac Rhythm Using an Epicardial Electrogram,” ASME Journal of Medical Devices, 2020. PDF
E. J. Park, et al., “A Hinge-Free, Non-Restrictive, Lightweight Tethered Exosuit for Knee Extension Assistance During Walking,” IEEE Transactions on Medical Robotics and Bionics, 2020. PDF
L. Awad, P. Kudzia, D. A. Revi, T. D. Ellis, and C. J. Walsh, “Walking Faster and Farther With a Soft Robotic Exosuit: Implications for Post-Stroke Gait Assistance and Rehabilitation,” IEEE Open Journal of Engineering in Medicine and Biology, vol. 1, pp. 108-115, 2020. PDF
M. Kim, et al., “Bayesian Optimization of Soft Exosuits Using a Metabolic Estimator Stopping Process.” in The 36th IEEE International Conference on Robotics and Automation (ICRA), 2019. PDF
S. Berndt, M. Herman, C. Walsh, and D. Holland, “The SDM Finger: Teaching engineering design through soft robotics,” Science Scope, vol. 43, no. 4, pp. 14-21, 2019. PDF
Reducing the metabolic rate of walking and running with a versatile, portable exosuit
J. Kim, et al., “Reducing the metabolic rate of walking and running with a versatile, portable exosuit,” Science, vol. 365, no. 6454, pp. 668-672, 2019. Publisher's VersionAbstract
Walking and running have fundamentally different biomechanics, which makes developing devices that assist both gaits challenging. We show that a portable exosuit that assists hip extension can reduce the metabolic rate of treadmill walking at 1.5 meters per second by 9.3% and that of running at 2.5 meters per second by 4.0% compared with locomotion without the exosuit. These reduction magnitudes are comparable to the effects of taking off 7.4 and 5.7 kilograms during walking and running, respectively, and are in a range that has shown meaningful athletic performance changes. The exosuit automatically switches between actuation profiles for both gaits, on the basis of estimated potential energy fluctuations of the wearer’s center of mass. Single-participant experiments show that it is possible to reduce metabolic rates of different running speeds and uphill walking, further demonstrating the exosuit’s versatility.
W. - H. Hsu, E. J. Park, D. L. Miranda, H. M. Sallum, C. J. Walsh, and E. C. Goldfield, “Gait Initiation of New Walkers and the Adult's Role in Regulating Directionality of the Child's Body Motion,” Journal of Motor Learning and Development, vol. 7, no. 1, pp. 35-48, 2019. PDF
Y. M. Zhou, et al., “Soft Robotic Glove with Integrated Sensing for Intuitive Grasping Assistance Post Spinal Cord Injury,” in IEEE Internaional Conference on Robotics and Automation (ICRA), Montreal, Canada, May 20-24, 2019. PDF
F. Panizzolo, et al., “Metabolic cost adaptations during training with a soft exosuit assisting the hip joint,” Scientific Reports, 2019. PDF
D. J. Preston, et al., “A soft ring oscillator,” Science Robotics, vol. 4, no. 31, 2019. PDF
J. Zhang, et al., “Robotic Artificial Muscles: Current Progress and Future Perspectives,” IEEE Transaction on Robitics, pp. 1-21, 2019. PDF
J. Kang, K. Ghonasgi, C. Walsh, and S. Agrawal, “Simulating Hemiparetic Gait in Healthy Subjects using TPAD with a Closed-loop Controller,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 27, no. 5, pp. 974-983, 2019. PDF