双电机同步控制技术综述

双电机驱动系统在运动控制领域有着广泛的应用,研究双电机同步控制技术对提升系统性能至关重要。随着工业生产对电机同步控制精度的要求不断提高,研究者们针对传统的控制方案进行了许多改进,并结合智能算法提出了许多新的控制策略。综述了近几年学界对双电机同步控制技术的研究成果,涵盖了并行控制、主从控制、交叉耦合控制等控制结构,以及模糊控制、滑模控制、神经网络控制等控制算法,分析了引起同步误差的各项因素,总结了未来的研究方向。

吸气肌训练对慢性心力衰竭患者影响的系统评价再评价

目的将吸气肌训练对慢性心力衰竭患者临床结局影响的系统评价进行再评价。方法计算机检索PubMed、Embase、CINAHL、Cochrane Library、中国知网、万方数据库、中国生物医学文献数据库、维普数据库,查找关于吸气肌训练对慢性心力衰竭患者干预效果的系统评价/Meta分析,检索时限为建库至2023年1月。由2名接受过循证护理学系统培训的研究人员独立进行文献筛选和资料提取,并应用系统评价方法学质量评价工具2(assessment of mutiple system reviews 2,AMSTAR 2)进行方法学质量评价后,采用推荐分级的评估、制订与评价(grades of recom-mendations assessment,development and evaluation,GRADE)系统进行证据的汇总与分级。结果共纳入14篇系统评价,AMSTAR 2评价结果显示,高等及中等质量文献各有1篇,其余12篇为低质量或极低质量。采用GRADE系统对14篇系统评价的40条结局指标的证据质量评价结果显示,3条证据为中等质量,31条证据为低质量,6条证据为极低质量。重新Meta分析结果显示,吸气肌训练有助于改善慢性心力衰竭患者最大吸气压、6 min步行距离、峰值摄氧量及呼吸困难(P<0.05),但对生活质量的干预效果仍需进一步证实。结论吸气肌训练对慢性心力衰竭患者的临床结局起到积极作用,但考虑到目前纳入系统评价的整体研究质量和结局指标证据质量普遍偏低,未来仍需严格、规范开展高质量的随机对照试验为慢性心力衰竭患者的吸气肌训练效果提供更有力的证据支持。

金线莲多糖协同ConA对小鼠脾淋巴细胞分泌Th1、Th2型细胞因子及其mRNA表达量的影响

目的:研究金线莲多糖(ARP)调节Con A刺激小鼠脾淋巴细胞细胞因子分泌水平及其m RNA表达影响,探讨其免疫调节作用机制。方法:小鼠脾淋巴细胞经不同质量浓度的金线莲多糖协同Con A体外刺激,ELISA法检测小鼠脾淋巴细胞上清液中Th1(IL-2、IFN-γ)、Th2(IL-4、IL-6)细胞因子的含量;q RT-PCR检测上述细胞因子及其转录因子T-bet、GATA-3 m RNA表达量。结果:在试验质量浓度范围,ARP能显著提高小鼠脾淋巴细胞Th1、Th2细胞因子的分泌量,促进Th1、Th2细胞因子及转录因子(T-bet、GATA-3)m RNA表达(P<0.01)。结论 :ARP能协同Con A促进小鼠脾淋巴细胞分泌Th1、Th2型细胞因子及其m RNA表达,从而发挥免疫调节的作用,作用机制可能与上调核转录因子T-bet、GATA-3的m RNA表达水平有关。

Development of an invasive brain machine interface with a monkey model

Brain-machine interfaces (BMIs) translate neural activities of the brain into specific instructions that can be carried out by external devices. BMIs have the potential to restore or augment motor functions of paralyzed patients suffering from spinal cord damage. The neural activities have been used to predict the 2D or 3D movement trajectory of monkey's arm or hand in many studies. However, there are few studies on decoding the wrist movement from neural activities in center-out paradigm. The present study developed an invasive BMI system with a monkey model using a 10×10-microelectrode array in the primary motor cortex. The monkey was trained to perform a two-dimensional forelimb wrist movement paradigm where neural activities and movement signals were simultaneous recorded. Results showed that neuronal firing rates highly correlated with forelimb wrist movement; > 70% (105/149) neurons exhibited specific firing changes during movement and > 36% (54/149) neurons were used to discriminate directional pairs. The neuronal firing rates were also used to predict the wrist moving directions and continuous trajectories of the forelimb wrist. The four directions could be classified with 96% accuracy using a support vector machine, and the correlation coefficients of trajectory prediction using a general regression neural network were above 0.8 for both horizontal and vertical directions. Results showed that this BMI system could predict monkey wrist movements in high accuracy through the use of neuronal firing information.

Decoding grasp movement from monkey premotor cortex for real-time prosthetic hand control

Brain machine interfaces (BMIs) have demonstrated lots of successful arm-related reach decoding in past decades, which provide a new hope for restoring the lost motor functions for the disabled. On the other hand, the more sophisticated hand grasp movement, which is more fundamental and crucial for daily life, was less referred. Current state of arts has specified some grasp related brain areas and offline decoding results; however, online decoding grasp movement and real-time neuroprosthetic control have not been systematically investigated. In this study, we obtained neural data from the dorsal premotor cortex (PMd) when monkey reaching and grasping one of four differently shaped objects following visual cues. The four grasp gesture types with an additional resting state were classified asynchronously using a fuzzy k-nearest neighbor model, and an artificial hand was controlled online using a shared control strategy. The results showed that most of the neurons in PMd are tuned by reach and grasp movement, us- ing which we get a high average offline decoding accuracy of 97.1%. In the online demonstration, the instantaneous status of monkey grasping could be extracted successfully to control the artificial hand, with an event-wise accuracy of 85.1%. Overall, our results inspect the neural firing along the time course of grasp and for the first time enables asynchronous neural control of a prosthetic hand, which underline a feasible hand neural prosthesis in BMIs.

Modeling columnar spatiotemporal dynamics of nitric oxide as a primary controlling element of arteriole dilation during neurovascular coupling

Although the mechanism of neurovascular coupling remains inadequately understood,physiological research has indicated that the dilation of arterioles located within the cerebral cortex column might represent the primary mechanism of hemodynamic response during neurovascular coupling.This study examined the spatiotemporal pattern of NO diffusion induced by functional stimuli at column spatial resolution.Our modeling makes it possible to explore the responses of mediating factors to functional stimuli from a four-dimensional view,which may lead the way to decoding the mechanism of neurovascular coupling.