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For a better intention inference, we often try to figure out the emotional states of other people in social communications. Many studies on affective computing have been carried out to infer emotions through perceiving human states, i.e., facial expression and body posture. Such methods are skillful in a controlled environment. However, it often leads to misestimation due to the deficiency of effective inputs in unconstrained circumstances, that is, where context-aware emotion recognition appeared. We take inspiration from the advanced reasoning pattern of humans in perceived emotion recognition and propose the hierarchical context-based emotion recognition method with scene graphs. We propose to extract three contexts from the image, i.e., the entity context, the global context, and the scene context. The scene context contains abstract information about entity labels and their relationships. It is similar to the information processing of the human visual sensing mechanism. After that, these contexts are further fused to perform emotion recognition. We carried out a bunch of experiments on the widely used context-aware emotion datasets, i.e., CAER-S, EMOTIC, and BOdy Language Dataset (BoLD). We demonstrate that the hierarchical contexts can benefit emotion recognition by improving the accuracy of the SOTA score from 84.82% to 90.83% on CAER-S. The ablation experiments show that hierarchical contexts provide complementary information. Our method improves the F1 score of the SOTA result from 29.33% to 30.24% (C-F1) on EMOTIC. We also build the image-based emotion recognition task with BoLD-Img from BoLD and obtain a better emotion recognition score (ERS) score of 0.2153.

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Lower limb ankle exoskeletons have been used to improve walking efficiency and assist the elderly and patients with motor dysfunction in daily activities or rehabilitation training, while the assistance patterns may influence the wearer's lower limb muscle activities and coordination patterns. In this paper, we aim to evaluate the effects of different ankle exoskeleton assistance patterns on wearer's lower limb muscle activities and coordination patterns. A tethered ankle exoskeleton with nine assistance patterns that combined with differenet actuation timing values and torque magnitude levels was used to assist human walking. Lower limb muscle surface electromyography signals were collected from 7 participants walking on a treadmill at a speed of 1.25 m/s. Results showed that the soleus muscle activities were significantly reduced during assisted walking. In one assistance pattern with peak time in 49% of stride and peak torque at 0.7 N·m/kg, the soleus muscle activity was decreased by (38.5 ± 10.8)%. Compared with actuation timing, the assistance torque magnitude had a more significant influence on soleus muscle activity. In all assistance patterns, the eight lower limb muscle activities could be decomposed to five basic muscle synergies. The muscle synergies changed little under assistance with appropriate actuation timing and torque magnitude. Besides, co-contraction indexs of soleus and tibialis anterior, rectus femoris and semitendinosus under exoskeleton assistance were higher than normal walking. Our results are expected to help to understand how healthy wearers adjust their neuromuscular control mechanisms to adapt to different exoskeleton assistance patterns, and provide reference to select appropriate assistance to improve walking efficiency.

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Lower limb robotic exoskeletons have shown the capability to enhance human locomotion for healthy individuals or to assist motion rehabilitation and daily activities for patients. Recent advances in human-in-the-loop optimization that allowed for assistance customization have demonstrated great potential for performance improvement of exoskeletons. In the optimization process, subjects need to experience multiple types of assistance patterns, thus, leading to a long evaluation time. Besides, some patterns may be uncomfortable for the wearers, thereby resulting in unpleasant optimization experiences and inaccurate outcomes. In this study, we investigated the effectiveness of a series of ankle exoskeleton assistance patterns on improving walking economy prior to optimization. We conducted experiments to systematically evaluate the wearers' biomechanical and physiological responses to different assistance patterns on a lightweight cable-driven ankle exoskeleton during walking. We designed nine patterns in the optimization parameters range which varied peak torque magnitude and peak torque timing independently. Results showed that metabolic cost of walking was reduced by 17.1 ± 7.6% under one assistance pattern. Meanwhile, soleus (SOL) muscle activity was reduced by 40.9 ± 19.8% with that pattern. Exoskeleton assistance changed maximum ankle dorsiflexion and plantarflexion angle and reduced biological ankle moment. Assistance pattern with 48% peak torque timing and 0.75 N·m·kg -1 peak torque magnitude was effective in improving walking economy and can be selected as an initial pattern in the optimization procedure. Our results provided a preliminary understanding of how humans respond to different assistances and can be used to guide the initial assistance pattern selection in the optimization.

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Stimulus-driven attention can improve working memory (WM) when drawn to behaviorally relevant information, but the neural mechanisms underlying this effect are unclear. The present study used functional magnetic resonance imaging (fMRI) to test competing hypotheses regarding the nature of the benefits of stimulus-driven attention to WM: that stimulus-driven attention benefits WM directly via salience detection, that stimulus-driven attention benefits WM incidentally via cognitive control mechanisms recruited to reduce interference from salient features, or that both mechanisms are co-involved in enhancing WM for salient information. To test these hypotheses, we observed activation in brain regions associated with cognitive control and salience detection. We found 2 cognitive control regions that were associated with enhanced memory for salient stimuli: a region in the right superior parietal lobule and a region in the right inferior frontal junction. No regions associated with salience detection were found to show this effect. These fMRI results support the hypothesis that benefits to WM from stimulus-driven attention occur primarily as a result of cognitive control and top-down factors rather than pure bottom-up aspects of stimulus-driven attention.

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Disabilities after neural injury, such as stroke, bring tremendous burden to patients, families and society. Besides the conventional constrained-induced training with a paretic arm, bilateral rehabilitation training involves both the ipsilateral and contralateral sides of the neural injury, fitting well with the fact that both arms are needed in common activities of daily living (ADLs), and can promote good functional recovery. In this work, the fusion of a gesture sensor and a haptic sensor with force feedback capabilities has enabled a bilateral rehabilitation training therapy. The Leap Motion gesture sensor detects the motion of the healthy hand, and the omega.7 device can detect and assist the paretic hand, according to the designed cooperative task paradigm, as much as needed, with active force feedback to accomplish the manipulation task. A virtual scenario has been built up, and the motion and force data facilitate instantaneous visual and audio feedback, as well as further analysis of the functional capabilities of the patient. This task-oriented bimanual training paradigm recruits the sensory, motor and cognitive aspects of the patient into one loop, encourages the active involvement of the patients into rehabilitation training, strengthens the cooperation of both the healthy and impaired hands, challenges the dexterous manipulation capability of the paretic hand, suits easy of use at home or centralized institutions and, thus, promises effective potentials for rehabilitation training.

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