Purpose of Review: The new paradigm of soft robotics has been widely developed in the international robotics community. These robots being soft can be used in applications where delicate yet effective interaction is necessary. Soft grippers and manipulators are important, and their actuation is a fundamental area of study. The main purpose of this work is to provide readers with fast references to actuation technologies for soft robotic grippers in relation to their intended application. Recent Findings: The authors have surveyed recent findings on actuation technologies for soft grippers. They presented six major kinds of technologies which are either used independently for actuation or in combination, e.g., pneumatic actuation combined with electro-adhesion, for certain applications. Summary: A review on the latest actuation technologies for soft grippers and manipulators is presented. Readers will get a guide on the various methods of technology utilization based on the application.

Detecting differences in upper limb use in children with unilateral cerebral palsy (UCP) is challenging and highly dependent on examiner experience. The recent introduction of technologies in the clinical environment, and in particular the use of wearable sensors, can provide quantitative measurement to overcome this issue. This study aims to evaluate ActiGraph GT3X+ as a tool for measuring asymmetry in the use of the two upper limbs (ULs) during the assessment with a standardized clinical tool, the Assisting Hand Assessment (AHA) in UCP patients aged 3–25 years compared to age-matched typically developing (TD) subjects. Fifty children with UCP and 50 TD subjects were assessed with AHA while wearing ActiGraphs GT3X+ on both wrists. The mean activity of each hand (dominant and non-dominant, MADH and MANDH, respectively) and the asymmetry index (AI) were calculated. Two linear mixed model analyses were carried out to evaluate how dependent actigraphic variables (i.e. MANDH and AI) varied by group (TD vs UCP) and among levels of manual ability based on Manual Ability Classification System (MACS). In both models age, sex, side of hemiplegia, presence/absence of mirror movements were specified as random effects. The MANDH was significantly lower in UCP compared to TD, while the AI was significantly higher in UCP compared to TD. Moreover, in UCP group there were significant differences related to MACS levels, both for MANDH and AI. None of the random variables (i.e. age, sex, side, presence/absence of mirror movements) showed significant interaction with MANDH and AI. These results confirm that actigraphy could provide, in a standardized setting, a quantitative description of differences between upper limbs activity. ClincalTrials.gov, NCT03054441 . Registered 15 February 2017.

This paper is concerned with modeling of smart textiles, aimed at compensating their intrinsic nonlinearities. In particular, a new model is proposed to compensate for hysteresis and relaxation in strain sensors made of Electrolycra. These sensors are increasingly employed in emerging areas such as wearable electronics and soft robotics for their simple transduction mechanism and low cost. However, being intrinsically nonlinear, the signals measured from these devices need some processing, in order to increase their sensing accuracy. Here, we propose a new model for the compensation of the main distortions intrinsic to these soft sensors, which are mainly caused by hysteresis and relaxation, whose combined effect produces rate-dependent hysteresis. The model capabilities are tested on experimental data measured on Electrolycra. The comparisons with the results obtained with two different models witness the good behavior of the proposed model.

Understanding development of bimanual upper limb (UL) activities in both typical and atypical conditions in children is important for: i) tailoring rehabilitation programs, ii) monitoring progress, iii) determining outcomes and iv) evaluating effectiveness of treatment/rehabilitation. Recent technological advances, such as wearable sensors, offer possibilities to perform standard medical monitoring. Body-worn motion sensors, mainly accelerometers, have shown very promising results but, so far, these studies have mainly focused on adults. The main aim of this review was to report the evidence of UL activity of both typically developing (TD) children and children with neurodevelopmental disorders (NDDs) that are reliably reported and comparable, using a combination of multiple wearable inertial sensors, both in laboratory and natural settings. Articles were selected from three research databases (PubMed, Web of Science and EBSCO). Included studies reported data on children aged 0–20 years old simultaneously wearing at least two inertial sensors on upper extremities. The collected and reported data were relevant in order to describe the amount of physical activity performed by the two ULs separately. A total of 21 articles were selected: 11 including TD, and 10 regarding NDDs. For each article, a review of both clinical and technical data was performed. We considered inertial sensors used for following aims: (i) to establish activity intensity cut-points; (ii) to investigate validity and reliability of specified markers, placement and/or number of inertial sensors; (iii) to evaluate duration and intensity of natural UL movements, defined motor tasks and tremor; and (iv) to assess efficacy of certain rehabilitation protocols. Our conclusions were that inertial sensors are able to detect differences in use between both hands and that all reviewed studies support use of accelerometers as an objective outcome measure, appropriate in assessing UL activity in young children with NDDs and determining intervention effectiveness. Further research on responsiveness to interventions and consistency with use in real-world settings is needed. This information could be useful in planning UL rehabilitation strategies.

Long-term and minimally invasive joint angular measurements are required for monitoring everyday activities, motor rehabilitation sessions, and sport training. In this paper, we designed an innovative wearable device composed of a light, comfortable, and low-cost textile strain-resistance sensor. First, we proposed a methodology to characterize and to calibrate a commercial knitted textile. This characterization procedure represents an interesting result per se. It has been conducted on a single material, but its general characteristics make it suitable for analyzing the behavior of any conductive and stretchable fabrics. Second, we developed a wearable sensor (a goniometer) and we validated it using the humanoid robot SABIAN. Dynamic tests demonstrated that our wearable device is suitable for scenarios, where the accuracy of measurements is less relevant than the ability to continuously track joint movements in a not-obtrusive way.

Matrix textile sensors hold great potential for measuring pressure distribution in applications of modern daily lives, mainly regarding the biomedical field, but also robotics, automotive systems, and wearable and consumer electronics. However, an experimental analysis of their metrological properties is lacking in the literature, thus compromising their widespread acceptance. In the present work, we report the characterization of an 8 × 8 textile sensor assembled by sandwiching a piezoresistive fabric sheet between two outer fabric layers embedding conductive rows and columns. The location of the applied pressure can be identified by detecting the position where the change of resistances occurs between the external conductive paths. The sensor structure, its electrical circuit and characteristics are described in detail, after studying both the integration levels of the hierarchical structure and the composition of the piezoresistive fabric sheet. The pressure measurement range and the calibration curve were studied by tuning circuital parameters. Repeatability, time drift, temperature dependence, signal-to-noise ratio and dynamic response were analyzed. Novel tests were employed to consider the sensor sensitivity to stretch, shear force and surface curvature. A special analysis was taken over hysteresis and dynamic accuracy, focusing on a possible compensating solution. Results indicated that the system provides overall good quality performances with the main drawback of a limited dynamic accuracy, typical of piezoresistive sensing elements. Nevertheless, the use of textiles allows the realization of lightweight, wearable, washable, thin and stretchable sensors. In addition fabric sensors are robust, cheap, easy-to-use and employable to cover large area three dimensional surfaces. The wide characterization reported here could provide precious insights and guidelines to help researchers and users in taking advantages from all of these benefits, supporting them in choosing the best sensor design and application.