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The medical system is facing the transformations with augmentation in the use of medical information systems, electronic records, smart, wearable devices, and handheld. The central nervous system function is to control the activities of the mind and the human body. Modern speedy development in medical and computational growth in the field of the central nervous system enables practitioners and researchers to extract and visualize insight from these systems. The function of augmented reality is to incorporate virtual and real objects, interactively running in a real-time and real environment. The role of augmented reality in the central nervous system becomes a thought-provoking task. Gesture interaction approach-based augmented reality in the central nervous system has enormous impending for reducing the care cost, quality refining of care, and waste and error reducing. To make this process smooth, it would be effective to present a comprehensive study report of the available state-of-the-art-work for enabling doctors and practitioners to easily use it in the decision making process. This comprehensive study will finally summarise the outputs of the published materials associate to gesture interaction-based augmented reality approach in the central nervous system. This research uses the protocol of systematic literature which systematically collects, analyses, and derives facts from the collected papers. The data collected range from the published materials for 10 years. 78 papers were selected and included papers based on the predefined inclusion, exclusion, and quality criteria. The study supports to identify the studies related to augmented reality in the nervous system, application of augmented reality in the nervous system, technique of augmented reality in the nervous system, and the gesture interaction approaches in the nervous system. The derivations from the studies show that there is certain amount of rise-up in yearly wise articles, and numerous studies exist, related to augmented reality and gestures interaction approaches to different systems of the human body, specifically to the nervous system. This research organises and summarises the existing associated work, which is in the form of published materials, and are related to augmented reality. This research will help the practitioners and researchers to sight most of the existing studies subjected to augmented reality-based gestures interaction approaches for the nervous system and then can eventually be followed as support in future for complex anatomy learning. [ABSTRACT FROM AUTHOR]

This umbrella review is motivated to understand the shift in research themes on brain-computer interfacing (BCI) and it determined that a shift away from themes that focus on medical advancement and system development to applications that included education, marketing, gaming, safety, and security has occurred. The background of this review examined aspects of BCI categorisation, neuroimaging methods, brain control signal classification, applications, and ethics. The specific area of BCI software and hardware development was not examined. A search using One Search was undertaken and 92 BCI reviews were selected for inclusion. Publication demographics indicate the average number of authors on review papers considered was 4.2 ± 1.8. The results also indicate a rapid increase in the number of BCI reviews from 2003, with only three reviews before that period, two in 1972, and one in 1996. While BCI authors were predominantly Euro-American in early reviews, this shifted to a more global authorship, which China dominated by 2020–2022. The review revealed six disciplines associated with BCI systems: life sciences and biomedicine (n = 42), neurosciences and neurology (n = 35), and rehabilitation (n = 20); (2) the second domain centred on the theme of functionality: computer science (n = 20), engineering (n = 28) and technology (n = 38). There was a thematic shift from understanding brain function and modes of interfacing BCI systems to more applied research novel areas of research-identified surround artificial intelligence, including machine learning, pre-processing, and deep learning. As BCI systems become more invasive in the lives of "normal" individuals, it is expected that there will be a refocus and thematic shift towards increased research into ethical issues and the need for legal oversight in BCI application. [ABSTRACT FROM AUTHOR]

Electroencephalography-(EEG-) based control is a noninvasive technique which employs brain signals to control electrical devices/circuits. Currently, the brain-computer interface (BCI) systems provide two types of signals, raw signals and logic state signals. The latter signals are used to turn on/off the devices. In this paper, the capabilities of BCI systems are explored, and a survey is conducted how to extend and enhance the reliability and accuracy of the BCI systems. A structured overview was provided which consists of the data acquisition, feature extraction, and classification algorithm methods used by different researchers in the past few years. Some classification algorithms for EEG-based BCI systems are adaptive classifiers, tensor classifiers, transfer learning approach, and deep learning, as well as some miscellaneous techniques. Based on our assessment, we generally concluded that, through adaptive classifiers, accurate results are acquired as compared to the static classification techniques. Deep learning techniques were developed to achieve the desired objectives and their real-time implementation as compared to other algorithms. [ABSTRACT FROM AUTHOR]

Piano performance requires not only skillful and excellent playing skills, but also good psychological quality and improvisation. The perfect performance is the natural language of a pianist's usual skill and mood. The various emotional activities and expressions of the overall situation in relation to the player's performance, mental issues such as the intensity and horror of the scene, seriously affect the pianist's actual performance while playing. The piano is therefore very important for mind control. Based on this, this paper attempts to apply the current hot VR technology to piano performance and simulate the virtual piano performance scene through VR technology, so as to enhance the on-the-spot experience for piano players and continuously improve their psychological quality, so that they can better adjust their nervous bad mentality in actual combat. This article first has carried on the 3D virtual reality piano stage modeling experiment, and then selected the 20 young pianist piano training involved in day-to-day contrast test, the test group of 10 people for daily training, virtual piano stage under the environment of normal control group of 10 people ordinary daily training, training time four hours a day, for three months, all participants will take part in The Provincial Youth Piano Competition since the end of the training. The final test results showed that in the competition site, the performance level of 10 players in the test group was generally better than that of the control group. Among them, there were 2 subjects in the test group who played for a long time, while one of the control groups gave up playing in the middle. In addition, in the horizontal comparison, it is found that subjects who are older and have been learning piano for a long time have better on-the-spot mental adjustment ability and more stable performance. Boys performed better than girls, and subjects with positive, optimistic, and confident personalities performed better than those with introverted and low self-confidence. [ABSTRACT FROM AUTHOR]

Due to their profusion, high durability, and rigidity, lesser weight and biodegradable nature nanocellulose (NC) is observed as the challenging tasks for the aspirants in making of the green composites. The continuous network of the cellulose nanoparticle connected through hydrogen bonding is happened mainly due to the reinforcing effect allocated to the mechanical reoccurrence phenomenon of the NC. When comparing with the nanocrystalline cellulose, the NC has significant convincing progress in the durability and rigidity, and the aspect ratio of the NC is higher than that of the NC crystal. The reinforcement effect of NC is the characteristic of the NC polymer interaction as well as the reinforcement effect eventualizing through stress transfer at the NC–polymer interface. Thus, the concentration of the reinforcement particle rises to the saturation level due to the frailty of the NC reinforcement constituent and due to surface compliance between the matrix and the filler. Due to its structural firmness and mechanical behaviors, the NC compounds are used in many industrial applications like tissue engineering, food packaging, and electronic applications. The stretchable electronic systems and instruments are awaiting the maximal attention due to its essential applications in certain domains, such as robotics artificial intelligence, brain control and machine interface, clinical devices, and health care electronic monitoring devices. In addition to that, when realizing the operational performance of electronic devices, the electronic instruments and systems must be physically expandable and flexible. The proposed study deems the technique of reinforcing the NC compounds as green agent in electronic applications, which has been associated with the composites of polymer matrix. The elongation could be achieved through the formulation of composition via elastomers. In addition, it is being focused on the illustration of functional soft development of materials that is inclusive of the conductive intrinsic polymers for the elongated electrodes and electrothermal conversion and vice versa, occupying the maximal area along with tactile sensing elements. [ABSTRACT FROM AUTHOR]

Objective. Cerebral edema is a common complication of brain tumors in the perioperative period. However, there is currently no reliable and convenient method to evaluate the extent of brain edema. The objective is to explore the effectiveness of serum occludin on predicting the extent of perioperative brain edema and outcome in patients with brain tumors. Methods. This prospective study enrolled 55 patients with brain tumors and 24 healthy controls in Sanbo Brain Hospital from June 2019 through November 2019. Serum occludin levels were measured preoperatively and on postoperative day 1. Peritumoral edema was assessed preoperatively using MRI. Pericavity brain edema on postoperative day 1 was evaluated using CT. Results. Compared with healthy controls, the serum occludin level was higher in patients with brain tumors both preoperatively and postoperatively (P < 0.001). The serum occludin level correlated positively with the degree of brain edema preoperatively (r = 0.78 , P < 0.001) and postoperatively (r = 0.59 , P < 0.001). At an optimal cutoff of 3.015 ng/mL, the preoperative serum occludin level discriminated between mild and severe preoperative brain edema with a sensitivity of 90.48% and specificity of 84.62%. At an optimal cutoff value of 3.033 ng/mL, the postoperative serum occludin level distinguished between mild and severe postoperative brain edema with a sensitivity of 97.30% and specificity of 55.56%. Conclusions. The serum occludin level is associated with cerebral edema and could potentially be used as a biomarker for perioperative cerebral edema. This trial is registered with ChiCTR1900023742. [ABSTRACT FROM AUTHOR]

In this study, a closed-loop brain stimulation control system scheme for epilepsy seizure abatement is designed by brain-machine interface (BMI) technique. In the controller design process, the practical parametric uncertainties involving cerebral blood flow, glucose metabolism, blood oxygen level dependence, and electromagnetic disturbances in signal control are considered. An appropriate transformation is introduced to express the system in regular form for design and analysis. Then, sufficient conditions are developed such that the sliding motion is asymptotically stable. Combining Caputo fractional order definition and neural network (NN), a finite time fractional order sliding mode (FFOSM) controller is designed to guarantee reachability of the sliding mode. The stability and reachability analysis of the closed-loop tracking control system gives the guideline of parameter selection, and simulation results based on comprehensive comparisons are carried out to demonstrate the effectiveness of proposed approach. [ABSTRACT FROM AUTHOR]