BackgroundSpinal cord injury is a devastating condition that can dramatically impact hand motor function. Passive and active assistive devices are becoming more commonly used to enhance lost hand strength and dexterity. Soft robotics is an emerging discipline that combines the classical principles of robotics with soft materials and could provide a new class of active assistive devices. Soft robotic assistive devices enable a human-robot interaction facilitated by compliant and light-weight structures. The scope of this work was to demonstrate that a fabric-based soft robotic glove can effectively assist participants affected by spinal cord injury in manipulating objects encountered in daily living.MethodsThe Toronto Rehabilitation Institute Hand Function Test was administered to 9 participants with C4-C7 spinal cord injuries to assess the functionality of the soft robotic glove. The test included object manipulation tasks commonly encountered during activities of daily living (ADL) and lift force measurements. The test was administered to each participant twice; once without the assistive glove to provide baseline data and once while wearing the assistive glove. The object manipulation subtests were evaluated using a linear mixed model, including interaction effects of variables such as time since injury. The lift force measures were separately evaluated using the Wilcoxon signed-rank test.ResultsThe soft robotic glove improved object manipulation in ADL tasks. The difference in mean scores between baseline and assisted conditions was significant across all participants and for all manipulated objects. An improvement of 33.42 ± 15.43% relative to the maximal test score indicates that the glove sufficiently enhances hand function during ADL tasks. Moreover, lift force also increased when using the assistive soft robotic glove, further demonstrating the effectiveness of the device in assisting hand function.ConclusionsThe results gathered in this study validate our fabric-based soft robotic glove as an effective device to assist hand function in individuals who have suffered upper limb paralysis following a spinal cord injury.Electronic supplementary materialThe online version of this article (10.1186/s12984-018-0391-x) contains supplementary material, which is available to authorized users.

Knit, woven, and nonwoven fabrics offer a diverse range of stretch and strain limiting mechanical properties that can be leveraged to produce tailored, whole-body deformation mechanics of soft robotic systems. This work presents new insights and methods for combining heterogeneous fabric material layers to create soft fabric-based actuators. This work demonstrates that a range of multi-degree-of-freedom motions can be generated by varying fabrics and their layered arrangements when a thin airtight bladder is inserted between them and inflated. Specifically, we present bending and straightening fabric-based actuators that are simple to manufacture, lightweight, require low operating pressures, display a high torque-to-weight ratio, and occupy a low volume in their unpressurized state. Their utility is demonstrated through their integration into a glove that actively assists hand opening and closing.

Stretchable strain sensors, as the soft mechanical interface, provide the key mechanical information of the systems for healthcare monitoring, rehabilitation assistance, soft exoskeletal devices, and soft robotics. Stretchable strain sensors based on 2D flat film have been widely developed to monitor the in-plane force applied within the plane where the sensor is placed. However, to comprehensively obtain the mechanical feedback, the capability to detect the out-of-plane force, caused by the interaction outside of the plane where the senor is located, is needed. Herein, a 3D-structured stretchable strain sensor is reported to monitor the out-of-plane force by employing 3D printing in conjunction with out-of-plane capillary force-assisted self-pinning of carbon nanotubes. The 3D-structured sensor possesses large stretchability, multistrain detection, and strain-direction recognition by one single sensor. It is demonstrated that out-of-plane forces induced by the air/fluid flow are reliably monitored and intricate flow details are clearly recorded. The development opens up for the exploration of next-generation 3D stretchable sensors for electronic skin and soft robotics.

In this paper, we present a soft wearable robot for the shoulder which has the potential to assist individuals suffering from a range of neuromuscular conditions affecting the shoulder to perform activities of daily living. This wearable robot combines two types of soft textile pneumatic actuators which were custom developed for this particular application to support the upper arm through shoulder abduction and horizontal flexion/extension. The advantage of a textile-based approach is that the robot can be lightweight, low-profile, comfortable and non-restrictive to the wearer, and easy to don like an item of clothing. The actuator's ability to fold flat when not in use allows the robot to be almost invisible under clothing, potentially allowing the user to avoid any stigma associated with using assistive devices in public. To abduct the arm, a textilebased pneumatic actuator was developed to fit within the axilla to push the arm upwards, while a pair of smaller actuators pivot the abduction actuator to allow for horizontal extension and flexion. The individual textile actuators were experimentally evaluated before being integrated into a wearable garment. Human subject testing was performed to evaluate the ability of the robot to assist the arm by monitoring changes in biological muscle activity when comparing the robot powered on and off. Preliminary results show large reductions in muscular effort in targeted muscles, demonstrating the feasibility and promise of such a soft wearable robot for the shoulder.

IntroductionImpaired proprioception severely affects the control of gross and fine motor function. However, clinical assessment of proprioceptive deficits and its impact on motor function has been difficult to elucidate. Recent advances in haptic robotic interfaces designed for sensorimotor rehabilitation enabled the use of such devices for the assessment of proprioceptive function.PurposeThis study evaluated the feasibility of a wrist robot system to determine proprioceptive discrimination thresholds for two different DoFs of the wrist. Specifically, we sought to accomplish three aims: first, to establish data validity; second, to show that the system is sensitive to detect small differences in acuity; third, to establish test–retest reliability over repeated testing.MethodologyEleven healthy adult subjects experienced two passive wrist movements and had to verbally indicate which movement had the larger amplitude. Based on a subject’s response data, a psychometric function was fitted and the wrist acuity threshold was established at the 75% correct response level. A subset of five subjects repeated the experimentation three times (T1, T2, and T3) to determine the test–retest reliability.ResultsMean threshold for wrist flexion was 2.15°± 0.43° and 1.52°± 0.36° for abduction. Encoder resolutions were 0.0075°(flexion–extension) and 0.0032°(abduction–adduction). Motor resolutions were 0.2°(flexion–extension) and 0.3°(abduction–adduction). Reliability coefficients were rT2-T1 = 0.986 and rT3-T2 = 0.971.ConclusionWe currently lack established norm data on the proprioceptive acuity of the wrist to establish direct validity. However, the magnitude of our reported thresholds is physiological, plausible, and well in line with available threshold data obtained at the elbow joint. Moreover, system has high resolution and is sensitive enough to detect small differences in acuity. Finally, the system produces reliable data over repeated testing.