Sudden infant death syndrome prevention

We looked at existing recommendations and supporting evidence for successful strategies to prevent the sudden infant death syndrome (SIDS).We conducted a literature search up to the 14th of December 2020 by using key terms and manual search in selected sources. We summarized the recommendations and the strength of the recommendation when and as reported by the authors. We summarized the main findings of systematic reviews with the certainty of the evidence as reported.Current evidence supports statistical associations between risk factors and SIDS, but there is globally limited evidence by controlled studies assessing the effect of the social promotion strategies to prevent SIDS through knowledge, attitude and practices, due to obvious ethical reasons. A dramatic decline in SIDS incidence has been observed in many countries after the introduction of “Back to Sleep” campaigns for prevention of SIDS. All infants should be placed to sleep in a safe environment including supine position, a firm surface, no soft objects and loose bedding, no head covering, no overheating, and room-sharing without bed-sharing. Breastfeeding on demand and the use of pacifier during sleep time protect against SIDS and should be recommended. Parents should be advised against the use of tobacco, alcohol and illicit drugs during gestation and after birth.

Classification of Rigid and Non-Rigid Objects Using CNN

Classifying moving objects in video surveillance can be difficult, and it is challenging to classify hard and soft objects with high Accuracy. Here rigid and non-rigid objects are limited to vehicles and people. CNN is used for the binary classification of rigid and non-rigid objects. A deep-learning system using convolutional neural networks was trained using python and categorized according to their appearance. The classification is supplemented by the use of a data set, which contains two classes of images that are both rigid and not rigid that differ by illuminations.

Comparison of Different Technologies for Soft Robotics Grippers

Soft grippers have experienced a growing interest due to their considerable flexibility that allows them to grasp a variety of objects, in contrast to hard grippers, which are designed for a specific item. One of their most remarkable characteristics is the ability to manipulate soft objects without damaging them. This, together with their wide range of applications and the use of novels materials and technologies, renders them a very robust device. In this paper, we present a comparison of different technologies for soft robotics grippers. We fabricated and tested four grippers. Two use pneumatic actuation (the gripper with chambered fingers and the jamming gripper), while the other two employ electromechanical actuation (the tendon driver gripper and the gripper with passive structure). For the experiments, a group of twelve objects with different mechanical and geometrical properties have been selected. Furthermore, we analyzed the effect of the environmental conditions on the grippers, by testing each object in three different environments: normal, humid, and dusty. The aim of this comparative study is to show the different performances of different grippers tested under the same conditions. Our findings indicate that we can highlight that the mechanical gripper with a passive structure shows greater robustness.

Extra-Soft Tactile Sensor for Sensitive Force/Displacement Measurement with High Linearity Based on a Uniform Strength Beam

The soft sensing system has drawn huge enthusiasm for the application of soft robots and healthcare recently. Most of them possess thin-film structures that are beneficial to monitoring strain and pressure, but are unfavorable for measuring normal displacement with high linearity. Here we propose soft tactile sensors based on uniform-strength cantilever beams that can be utilized to measure the normal displacement and force of soft objects simultaneously. First, the theoretical model of the sensors is constructed, on the basis of which, the sensors are fabricated for testing their sensing characteristics. Next, the test results validate the constructed model, and demonstrate that the sensors can measure the force as well as the displacement. Besides, the self-fabricated sensor can have such prominent superiorities as follows—it is ultra-soft, and its equivalent stiffness is only 0.31 N·m−1 (approximately 0.4% of fat); it has prominent sensing performance with excellent linearity (R2 = 0.999), high sensitivity of 0.533 pF·mm−1 and 1.66 pF·mN−1 for measuring displacement and force; its detection limit is as low as 70 μm and 20 μN that is only one-tenth of the touch of a female fingertip. The presented sensor highlights a new idea for measuring the force and displacement of the soft objects with broad application prospects in mechanical and medical fields.

An elasticity-curvature illusion decouples cutaneous and proprioceptive cues in active exploration of soft objects

Our sense of touch helps us encounter the richness of our natural world. Across a myriad of contexts and repetitions, we have learned to deploy certain exploratory movements in order to elicit perceptual cues that are salient and efficient. The task of identifying optimal exploration strategies and somatosensory cues that underlie our softness perception remains relevant and incomplete. Leveraging psychophysical evaluations combined with computational finite element modeling of skin contact mechanics, we investigate an illusion phenomenon in exploring softness; where small-compliant and large-stiff spheres are indiscriminable. By modulating contact interactions at the finger pad, we find this elasticity-curvature illusion is observable in passive touch, when the finger is constrained to be stationary and only cutaneous responses from mechanosensitive afferents are perceptible. However, these spheres become readily discriminable when explored volitionally with musculoskeletal proprioception available. We subsequently exploit this phenomenon to dissociate relative contributions from cutaneous and proprioceptive signals in encoding our percept of material softness. Our findings shed light on how we volitionally explore soft objects, i.e., by controlling surface contact force to optimally elicit and integrate proprioceptive inputs amidst indiscriminable cutaneous contact cues. Moreover, in passive touch, e.g., for touch-enabled displays grounded to the finger, we find those spheres are discriminable when rates of change in cutaneous contact are varied between the stimuli, to supplant proprioceptive feedback.

Modeling of a Soft-Rigid Gripper Actuated by a Linear-Extension Soft Pneumatic Actuator

Soft robot has been one significant study in recent decades and soft gripper is one of the popular research directions of soft robot. In a static gripping system, excessive gripping force and large deformation are the main reasons for damage of the object during the gripping process. For achieving low-damage gripping to the object in static gripping system, we proposed a soft-rigid gripper actuated by a linear-extension soft pneumatic actuator in this study. The characteristic of the gripper under a no loading state was measured. When the pressure was >70 kPa, there was an approximately linear relation between the pressure and extension length of the soft actuator. To achieve gripping force and fingertip displacement control of the gripper without sensors integrated on the finger, we presented a non-contact sensing method for gripping state estimation. To analyze the gripping force and fingertip displacement, the relationship between the pressure and extension length of the soft actuator in loading state was compared with the relationship under a no-loading state. The experimental results showed that the relative error between the analytical gripping force and the measured gripping force of the gripper was ≤2.1%. The relative error between analytical fingertip displacement and theoretical fingertip displacement of the gripper was ≤7.4%. Furthermore, the low damage gripping to fragile and soft objects in static and dynamic gripping tests showed good performance of the gripper. Overall, the results indicated the potential application of the gripper in pick-and-place operations.

Effects of holding soft objects during Cyberball tasks under frequent positive feedback

A previous study suggested that holding soft objects enhanced expectations of uncertain events and increased social pain under frequent negative feedback; i.e., higher expectations might have induced more disappointment. The present study examined the effects of holding a soft cushion under frequent positive feedback. Participants (n = 42) performed fair-play and over-inclusion blocks in the Cyberball task. Amplitudes of the contingent negative variation (CNV) of event-related brain potentials and subjective ratings of social pain were measured to estimate participants’ expectations and emotions, respectively. CNV amplitudes were higher in the over-inclusion block when participants held the soft than the hard cushion. There was a statistically marginal trend (p = .095) for lower social pain scores in the soft cushion condition than the hard cushion condition in contrast to previous findings. These results suggest that holding a soft object does not directly modulate emotions but instead acts through the mediation of enhanced expectations.