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Objective. To explore the effects of different intervention methods on intestinal cleanliness in children undergoing colonoscopy. Methods. 61 children who underwent colonoscopy in our hospital from May 2020 to May 2021 were randomly divided into group A (n = 21), group B (n = 30), and group C (n = 10). The children in the three groups were intervened in different ways before the colonoscopy. Group A received a long-handled Kaiselu +1 cathartic intervention, while group B received a long-handled Kaiselu +2 cathartic intervention, and group C received an enema plus one cathartic intervention. The patients in the three groups were given the same diet before the examination until the examination was completed. The time-related indexes, cleanliness, adverse reactions, tolerance, and adaptability of the three groups under different dietary interventions and cleaning methods were evaluated. Results. The first defecation time in group C was lower than that in group A and group B, the hospital stay was longer than that in group A and group B (p > 0.05), and the colonoscopy time in group C was shorter than that in group A and group B (p < 0.05). The BBPS score of group C was (2.10 ± 0.32), which was significantly higher than that of group A (1.16 ± 0.19) and group B (1.77 ± 0.18) (p < 0.05). The BBPS scores of children with liquid food in the three groups were significantly higher than those of common food, and the BBPS scores of liquid food and common food in group C were significantly higher than those in group A and group B (p < 0.05). The incidence of adverse reactions in group C was 20.00%, which was significantly lower than 33.33% in group A and 23.33% in group B (p < 0.05). The proportion of grade I in group C was 50.00%, which was significantly higher than 38.10% in group A and 43.33% in group B (p < 0.05). Conclusion. Children undergoing colonoscopy take preintestinal preparation under different diets and intervention methods. The cleanliness of liquid food and enema + one-time laxative one day before colonoscopy is the best, which can significantly reduce adverse reactions and increase the acceptability and adaptability of children. It is worthy of clinical application. [ABSTRACT FROM AUTHOR]

Deformation prediction is significant to the safety of foundation pits. Against with low accuracy and limited applicability of a single model in forecasting, a PSO-GM-BP model was established, which used the PSO optimization algorithm to optimize and improve the GM (1, 1) model and the BP network model, respectively. Combining a small amount of measured data during the excavation of a bottomless foundation pit in a Changsha subway station, the calculations based on the PSO-GM model, the PSO-BP network model, and the PSO-GM-BP model compared. The results show that both the GM (1, 1) and BP neural network models can predict accurate results. The prediction optimized by the particle swarm algorithm is more accurate and has more substantial applicability. Due to its reliable accuracy and wide application range, the PSO-GM-BP model can effectively guide the construction of foundation pits, and it also has certain reference significance for other engineering applications. [ABSTRACT FROM AUTHOR]

Objective: A challenging task for an electroencephalography (EEG)-based asynchronous brain-computer interface (BCI) is to effectively distinguish between the idle state and the control state while maintaining a short response time and a high accuracy when commands are issued in the control state. This study proposes a novel hybrid asynchronous BCI system based on a combination of steady-state visual evoked potentials (SSVEPs) in the EEG signal and blink-related electrooculography (EOG) signals. Methods: Twelve buttons corresponding to 12 characters are included in the graphical user interface (GUI). These buttons flicker at different fixed frequencies and phases to evoke SSVEPs and are simultaneously highlighted by changing their sizes. The user can select a character by focusing on its frequency-phase stimulus and simultaneously blinking his/her eyes in accordance with its highlighting as his/her EEG and EOG signals are recorded. A multifrequency band-based canonical correlation analysis (CCA) method is applied to the EEG data to detect the evoked SSVEPs, whereas the EOG data are analyzed to identify the user's blinks. Finally, the target character is identified based on the SSVEP and blink detection results. Results: Ten healthy subjects participated in our experiments and achieved an average information transfer rate (ITR) of 105.52 bits/min, an average accuracy of 95.42%, an average response time of 1.34 s and an average false-positive rate (FPR) of 0.8%. Conclusion: The proposed BCI generates multiple commands with a high ITR and low FPR. Significance: The hybrid asynchronous BCI has great potential for practical applications in communication and control. [ABSTRACT FROM AUTHOR]

This paper presents a new asynchronous hybrid brain-computer interface (BCI) system that integrates a speller, a web browser, an e-mail client, and a file explorer using electroencephalographic (EEG) and electrooculography (EOG) signals. More specifically, an EOG-based button selection method, which requires the user to blink his/her eyes synchronously with the target button’s flashes during button selection, is first presented. Next, we propose a mouse control method by combining EEG and EOG signals, in which the left-/right-hand motor imagery (MI)-related EEG is used to control the horizontal movement of the mouse and the blink-related EOG is used to control the vertical movement of the mouse and to select/reject a target. These two methods are further combined to develop the integrated hybrid BCI system. With the hybrid BCI, users can input text, access the internet, communicate with others via e-mail, and manage files in their computer using only EEG and EOG without any body movements. Ten healthy subjects participated in a comprehensive online experiment, and superior performance was achieved compared with our previously developed P300- and MI-based BCI and some other asynchronous BCIs, therefore demonstrating the system’s effectiveness. [ABSTRACT FROM AUTHOR]

Objective: This paper presents an asyn-chronous electrooculography (EOG)-based human–machine interface (HMI) for smart home environmental control with the purpose of providing daily assistance for severe spinal cord injury (SCI) patients. Methods: The proposed HMI allows users to interact with a smart home environment through eye blinking. Specifically, several buttons, each corresponding to a control command, randomly flash on a graphical user interface. Each flash of the buttons functions as a visual cue for the user to blink. To issue a control command, the user can blink synchronously with the flashes of the corresponding button. Through detecting blinks based on the recorded EOG signal, the target button and its corresponding control command are determined. Seven SCI patients participated in an online experiment, during which the patients were required to control a smart home environment including household electrical appliances, an intelligent wheelchair, as well as a nursing bed via the proposed HMI. Results: The average false operation ratio in the control state was 4.1%, whereas during the idle state, no false operations occurred. Conclusion: All SCI patients were able to control the smart home environment using the proposed EOG-based HMI with satisfactory performance in terms of the false operation ratio in both the control and the idle states. Significance: The proposed HMI offers a simple and effective approach for patients with severe SCIs to control a smart home environment. Therefore, it is promising to assist severe SCI patients in their daily lives. [ABSTRACT FROM AUTHOR]

Objective: Nonmanual human–machine interfaces (HMIs) have been studied for wheelchair control with the aim of helping severely paralyzed individuals regain some mobility. The challenge is to rapidly, accurately, and sufficiently produce control commands, such as left and right turns, forward and backward motions, acceleration, deceleration, and stopping. In this paper, a novel electrooculogram (EOG) based HMI is proposed for wheelchair control. Methods: A total of 13 flashing buttons, each of which corresponds to a command, are presented in the graphical user interface. These buttons flash on a one-by-one manner in a predefined sequence. The user can select a button by blinking in sync with its flashes. The algorithm detects the eye blinks from a channel of vertical EOG data and determines the user's target button based on the synchronization between the detected blinks and the button's flashes. Results: For healthy subjects/patients with spinal cord injuries, the proposed HMI achieved an average accuracy of 96.7% / 91.7% and a response time of 3.53 s/3.67 s with 0 false positive rates (FPRs). Conclusion: Using one channel of vertical EOG signals associated with eye blinks, the proposed HMI can accurately provide sufficient commands with a satisfactory response time. Significance: The proposed HMI provides a novel nonmanual approach for severely paralyzed individuals to control a wheelchair. Compared with a newly established EOG-based HMI, the proposed HMI can generate more commands with higher accuracy, lower FPR, and fewer electrodes. [ABSTRACT FROM AUTHOR]

With prefabricated construction method deemed as an effective way to improve the environmental performance and sustainable development of the building industry, it is inevitably adopted in the scaled residence in the process of residential industrialization. However, the development of prefabricated residential buildings is still immature under the current market economy system, because the stakeholders involved in the process are not yet able to form a good cooperation mechanism and they are more inclined to keep their own interests. As a result, the market share of prefabricated residential buildings is relatively low. Therefore, it is necessary to conduct research on the stakeholders involved. By analyzing their costs and benefits, the reasons that really impede the population of prefabricated residential buildings can be found. In this paper, incremental cost allocation coefficient is introduced, the incremental cost difference under different assembly rates is considered, and the allocation ratio of the incremental cost input of the prefabricated building is analyzed based on game theory. The evolutionary game theory for government and real estate companies is established under the condition of bounded rationality with consumer participation. Then the effectiveness of the game theory is verified using empirical analysis, so as to provide reference for the authorities to promote the large-scale development of prefabricated residential buildings. [ABSTRACT FROM AUTHOR]

Prefabricated building constitutes the development trend of the construction industry in the future. However, many uncertainties in the construction process will surely lead to a higher cost. Therefore, it is necessary to study the cost risk evolution and transfer mechanism in the implementation process of this project. A dynamic evolution model for the cost risk of prefabricated buildings has been established in this paper. First of all, a matrix for cost risk of prefabricated buildings was established based on the WSR (Wuli-Shili-Renli) model, and all risk factors in the implementation stage were classified in accordance with the WSR principle. Second, a DBN-based dynamic evolution model was established based on the risk matrix, and the structure and node parameters of the Dynamic Bayesian Network were determined with the aid of the K2 structure learning algorithm and parameter learning method. In view of the probability change process of risks over time, the dynamic evolution path of risks was predicted in different cases through causal reasoning and diagnostic reasoning. Eventually, the model was applied into construction projects. The research results show that: because prefabricated components need to be made by prefabricated component factories, the management systems of prefabricated component factories are usually not perfect, and the probability of management risks is higher. The occurrence of management risks not only has an impact on other risks at the current time node, but also causes other risks to occur in the subsequent transportation and construction phases at the next moment, which eventually leads to the occurrence of risk events. [ABSTRACT FROM AUTHOR]

Prefabricated building is an objective requirement to achieve sustainable development of the construction industry. However, it should be noted that Chinese enterprises are characterized by an immature supply chain management mechanism, and weak environmental protection awareness and social responsibility awareness. Therefore, from the perspective of sustainable development, a performance evaluation system for a prefabricated building supply chain was established based on SEM (Structural Equation Model) and virtual frontier SBM–DEA (Slacks-Based Measure and Data Envelopment Analysis). Upon summarization of a great deal of literatures, the most influential 34 indexes were selected, after which the weight calculation and index screening were performed using SEM method. Second, the performance evaluation was conducted using the virtual SBM–DEA method. Horizontally, a comparison is made on the performance and total performance of the four sub-units (supply chain operation, economic benefit, environmental protection and social liabilities) in the supply chain; vertically, the dynamic changes of the supply chain in time dimension are assessed. After the evaluation system was applied into enterprises, research results show that factors affecting the performance of the corporate supply chain are ranked as: supply chain operation > economic benefits > environmental protection > social responsibility. At the same time, the performance of 14 supply chains was evaluated, in order to provide guidance for supply chain management in enterprises. [ABSTRACT FROM AUTHOR]

Biological signals, including electroencephalography (EEG) and electrooculography (EOG), are often used to develop switches, which represent a class of typical asynchronous human–computer interfaces (HCIs) in which control and idle states need to be distinguished based on a criterion. Determining a satisfactory criterion for rapid and accurate discrimination between control and idle states remains a challenging issue, as EEG signals are highly noisy and nonstationary, and EOG signals are highly affected by unintended/spontaneous eye movements. Therefore, most existing EEG- or EOG-based switches are characterized by disadvantages of long response times (RTs) or high false positive rates (FPRs). The primary contribution of this work is the development of a novel EOG-based switch design, in which a visual trigger mechanism is introduced to guide the users’ blinks and to assist in detecting blinks. Specifically, the graphical user interface (GUI) includes a switch button that flashes once per 1.2 s. The user is instructed to blink synchronously with the flashes of the switch button to issue an on/off command while a single-channel EOG signal is collected. A waveform detection algorithm is applied to the ongoing EOG signal, which discriminates the intended and unintended blinks mainly based on the synchrony between the blink and the switch buttons flash. Once an intended blink, i.e., a blink corresponding to a button’s flash, is detected, the system issues an on/off command. As one application, the proposed EOG-based switch is used to produce start/stop commands for a wheelchair. Several online experiments were conducted with ten healthy subjects. An average accuracy of 99.5%, an RT of 1.3 s for issuing a switch command in the control state, and an average FPR of 0.10/min in the idle state were achieved. The experimental results therefore demonstrate the effectiveness of the single-channel EOG-based switch. [ABSTRACT FROM AUTHOR]

Objective: In this study, we aimed to investigate whether and how the aperiodic component in electroencephalograms affects different quantitative processes of steady-state visually evoked potentials and the performance of corresponding brain-computer interfaces., Methods: We applied the Fitting Oscillations & One-Over-F method to parameterize power spectra as a combination of periodic oscillations and an aperiodic component. Electroencephalographic responses and system performance were measured and compared using four prevailing methods: power spectral density analysis, canonical correlation analysis, filter bank canonical correlation analysis and the state-of-the-art method, task discriminant component analysis., Results: We found that controlling for the aperiodic component prominently downgraded the performance of brain-computer interfaces measured by canonical correlation analysis (94.9% to 82.8%), filter bank canonical correlation analysis (94.1% to 87.6%), and task discriminant component analysis (96.5% to 70.3%). However, it had almost no effect on that measured by power spectral density analysis (80.4% to 78.7%). This was accompanied by a differential aperiodic impact between power spectral density analysis and the other three methods on the differentiation of the target and non-target stimuli., Conclusion: The aperiodic component distinctly impacts the quantification of steady-state visually evoked potentials and the performance of corresponding brain-computer interfaces., Significance: Our work underscores the significance of taking into account the dynamic nature of aperiodic activities in research related to the quantification of steady-state visually evoked potentials. The source code for our approach is available at https://github.com/didi226/scut&#95;ssvep&#95;aperiod.

Alterations in γ-aminobutyric acid (GABA) have been implicated in sensory differences in individuals with autism spectrum disorder (ASD). Visual signals are initially processed in the retina, and in this study, we explored the hypotheses that the GABA-dependent retinal response to light is altered in individuals with ASD. Light-adapted electroretinograms were recorded from 61 adults (38 males and 23 females; n  = 22 ASD) in response to three stimulus protocols: (1) the standard white flash, (2) the standard 30 Hz flickering protocol, and (3) the photopic negative response protocol. Participants were administered an oral dose of placebo, 15 or 30 mg of arbaclofen (STX209, GABA B agonist) in a randomized, double-blind, crossover order before the test. At baseline (placebo), the a-wave amplitudes in response to single white flashes were more prominent in ASD, relative to typically developed (TD) participants. Arbaclofen was associated with a decrease in the a-wave amplitude in ASD, but an increase in TD, eliminating the group difference observed at baseline. The extent of this arbaclofen-elicited shift significantly correlated with the arbaclofen-elicited shift in cortical responses to auditory stimuli as measured by using an electroencephalogram in our prior study and with broader autistic traits measured with the autism quotient across the whole cohort. Hence, GABA-dependent differences in retinal light processing in ASD appear to be an accessible component of a wider autistic difference in the central processing of sensory information, which may be upstream of more complex autistic phenotypes., Competing Interests: The authors declare no competing financial interests., (Copyright © 2024 Huang et al.)

Objective: A brain-computer interface (BCI) can be used to translate neuronal activity into commands to control external devices. However, using noninvasive BCI to control a robotic arm for movements in three-dimensional (3D) environments and accomplish complicated daily tasks, such as grasping and drinking, remains a challenge., Approach: In this study, a shared robotic arm control system based on hybrid asynchronous BCI and computer vision was presented. The BCI model, which combines steady-state visual evoked potentials (SSVEPs) and blink-related electrooculography (EOG) signals, allows users to freely choose from fifteen commands in an asynchronous mode corresponding to robot actions in a 3D workspace and reach targets with a wide movement range, while computer vision can identify objects and assist a robotic arm in completing more precise tasks, such as grasping a target automatically., Results: Ten subjects participated in the experiments and achieved an average accuracy of more than 92% and a high trajectory efficiency for robot movement. All subjects were able to perform the reach-grasp-drink tasks successfully using the proposed shared control method, with fewer error commands and shorter completion time than with direct BCI control., Significance: Our results demonstrated the feasibility and efficiency of generating practical multidimensional control of an intuitive robotic arm by merging hybrid asynchronous BCI and computer vision-based recognition.

Sensory atypicalities in autism spectrum disorder (ASD) are thought to arise at least partly from differences in γ-aminobutyric acid (GABA) receptor function. However, the evidence to date has been indirect, arising from correlational studies in patients and preclinical models. Here, we evaluated the role of GABA receptor directly, in 44 adults ( n = 19 ASD). Baseline concentration of occipital lobe GABA+ (GABA plus coedited macromolecules) was measured using proton magnetic resonance spectroscopy ( 1 H-MRS). Steady-state visual evoked potential (SSVEP) elicited by a passive visual surround suppression paradigm was compared after double-blind randomized oral administration of placebo or 15 to 30 mg of arbaclofen (STX209), a GABA type B (GABA B ) receptor agonist. In the placebo condition, the neurotypical SSVEP response was affected by both the foreground stimuli contrast and background interference (suppression). In ASD, however, all stimuli conditions had equal salience and background suppression of the foreground response was weaker. In the placebo condition, although there was no difference in GABA+ between groups, GABA+ concentration positively correlated with response to maximum foreground contrast during maximum background interference in neurotypicals, but not ASD. In neurotypicals, sensitivity to visual stimuli was disrupted by 30 mg of arbaclofen, whereas in ASD, it was made more “typical” and visual processing differences were abolished. Hence, differences in GABAergic function are fundamental to autistic (visual) sensory neurobiology and are modulated by GABA B activity.

Most existing brain-computer Interfaces (BCIs) are designed to control a single assistive device, such as a wheelchair, a robotic arm or a prosthetic limb. However, many daily tasks require combined functions which can only be realized by integrating multiple robotic devices. Such integration raises the requirement of the control accuracy and is more challenging to achieve a reliable control compared with the single device case. In this study, we propose a novel hybrid BCI with high accuracy based on electroencephalogram (EEG) and electrooculogram (EOG) to control an integrated wheelchair robotic arm system. The user turns the wheelchair left/right by performing left/right hand motor imagery (MI), and generates other commands for the wheelchair and the robotic arm by performing eye blinks and eyebrow raising movements. Twenty-two subjects participated in a MI training session and five of them completed a mobile self-drinking experiment, which was designed purposely with high accuracy requirements. The results demonstrated that the proposed hBCI could provide satisfied control accuracy for a system that consists of multiple robotic devices, and showed the potential of BCI-controlled systems to be applied in complex daily tasks., (Copyright © 2019 Huang, Zhang, Yu, He and Li.)

Objective: In this study, we combine a wheelchair and an intelligent robotic arm based on an electrooculogram (EOG) signal to help patients with spinal cord injuries (SCIs) accomplish a self-drinking task. The main challenge is to accurately control the wheelchair to ensure that the randomly located object is within a limited reachable space of the robotic arm (length: 0.8 m; width: 0.4 m; height: 0.6 m), which requires decimeter-level precision, and is still undemonstrated for EOG-based systems as well as EEG-based systems., Approach: A novel high-precision EOG-based human machine interface (HMI) is proposed which can effectively translate two kinds of eye movements (i.e. blinking and eyebrow raising) into various commands. For the wheelchair, positional precision can reach decimeter-level and the minimal steering angle is [Formula: see text]. For the intelligent robotic arm, shared control is implemented based on an EOG-based HMI, two cameras and the arm's own intelligence., Main Results: After brief training, five healthy subjects and five paralyzed patients with severe SCIs successfully completed three experiments. For the healthy subjects/patients with SCIs, the system achieved an average accuracy of 99.3%/97.3%, an average response time of 1.91 s/2.02 s per command and an average stop-response time of 1.30 s/1.36 s with a 0 false operation rate., Significance: The EOG-based HMI can provide sufficient precision control to integrate a wheelchair and a robotic arm into a system which can help patients with SCIs to accomplish a self-drinking task. (ChiCTR1800019764).