The incidence and prevalence of asthma have increased remarkably in recent years. There are lots of factors contributing to the occurrence and development of asthma. With the improvement of sequencing technology, it has been found that the microbiome plays an important role in the formation of asthma in early life. The roles of the microbial environment and human microbiome in the occurrence and development of asthma have attracted more and more attention. The environmental microbiome influences the occurrence of asthma by shaping the human microbiome. The specific mechanism may be related to the immune regulation of Toll-like receptors and T cells (special Tregs). Intestinal microbiome is formed and changed by regulating diet and lifestyle in early life, which may affect the development and maturation of the pulmonary immune system through the intestinal-pulmonary axis. It is well-recognized that both environmental microbiomes and human microbiomes can influence the onset of asthma. This review aims to summarize the recent advances in the research of microbiome, its relationship with asthma, and the possible mechanism of the microbiome in the occurrence and development of asthma. The research of the microbial environment and human microbiome may provide a new target for the prevention of asthma in children who have high-risk factors to allergy. However, further study of “when and how” to regulate microbiome is still needed.

Effective bilateral hand training is desired in rehabilitation programs to restore hand function for people with unilateral hemiplegia, so that they can perform daily activities independently. However, owing to limited human resources, the hand function training available in current clinical settings is significantly less than the adequate amount needed to drive optimal neural reorganization. In this study, we designed a lightweight and portable hand exoskeleton with a hand-sensing glove for bilateral hand training and home-based rehabilitation. The hand-sensing glove measures the hand movement of the less-affected hand using a flex sensor. Thereafter, the affected hand is driven by the hand exoskeleton using the measured hand movements. Compared with the existing hand exoskeletons, our hand exoskeleton improves the flexible mechanism for the back of the hand for better wearing experience and the thumb mechanism to make the pinch gesture possible. We designed a virtual reality game to increase the willingness of repeated movement practice for rehabilitation. Our system not only facilitates bilateral hand training but also assists in activities of daily living. This system could be beneficial for patients with hemiplegia for starting correct and sufficient hand function training in the early stages to optimize their recovery.

An exoskeleton, a wearable device, was designed based on the user’s physical and cognitive interactions. The control of the exoskeleton uses biomedical signals reflecting the user intention as input, and its algorithm is calculated as an output to make the movement smooth. However, the process of transforming the input of biomedical signals, such as electromyography (EMG), into the output of adjusting the torque and angle of the exoskeleton is limited by a finite time lag and precision of trajectory prediction, which result in a mismatch between the subject and exoskeleton. Here, we propose an EMG-based single-joint exoskeleton system by merging a differentiable continuous system with a dynamic musculoskeletal model. The parameters of each muscle contraction were calculated and applied to the rigid exoskeleton system to predict the precise trajectory. The results revealed accurate torque and angle prediction for the knee exoskeleton and good performance of assistance during movement. Our method outperformed other models regarding the rate of convergence and execution time. In conclusion, a differentiable continuous system merged with a dynamic musculoskeletal model supported the effective and accurate performance of an exoskeleton controlled by EMG signals.