Intelligent Optimization Method of Piezoelectric Ejection System Design Based on Finite Element Simulation and Neural Network.

This study describes an intelligent method for modeling and optimization of piezoelectric ejection system design for additive manufacturing. It is a combination of neural network (NN) techniques and finite element simulation (FES) that allows designing each parameter of a piezoelectric ejection system faster and more reliably than conventional methods. Using experimental and literature data, a FE model of the droplet ejection process was developed and validated to predict two indexes of droplet ejection behavior (DEB): jetting velocity and droplet diameter. Two artificial neural network (ANN) models based on feed-forward back propagation were developed and optimized by genetic algorithm (GA). A database was established by FE calculations, and the models were trained to establish the relationship between the piezoelectric ejection system design input parameters and each DEB indicator. The results show that both NN models can independently predict the droplet jetting velocity and droplet diameter values from the training and testing data with high accuracy to determine the optimal piezoelectric ejection system design. Finally, the accuracy of the prediction results of the FES and ANN-GA models was verified experimentally. It was found that the errors between the predicted and experimental results were 4.48% and 3.18% for the jetting velocity and droplet diameter, respectively, verifying that the optimization method is reliable and robust for piezoelectric ejection system design optimization.

A case report of system configuration issue in medical imaging due to system upgrade- changes in hardware and software.

Although the rapid growth in the efficiency of medical imaging is undeniable, the expansion of health information technology (HIT) into medical imaging has not been as seamless or well-integrated as it was thought to be. The socio-technical complexities in medical imaging associated with HIT systems can cause risks to patient harm and inconvenience, both individually and collectively, often in new, unforeseen, and unexpected ways. This study reflects a retrospectively collected single incident report related to medical imaging HIT systems, aiming to develop a set of preventive and corrective strategies. A combination of multiple deductive approaches (existing frameworks), i.e., HIT Classification Systems and 18-step medical imaging process workflow and inductive method (content analysis), were used to analyze the incident. The incident was identified as a "system configuration"-related software issue, contributed by system upgrade- changes in hardware and software. The incident was determined to occur during steps 10-12, i.e., "study selection and retrieval," "calling up of patient's referral," and "image review and interpretation," causing severe disruptions in the clinical workflow for several weeks. We propose 16 preventive and corrective strategies grouped under four key areas based on the socio-technical aspects associated with HIT systems. The key areas are (i) preparation and integration for upgraded systems, (ii) training for medical imaging specialists, (iii) contingency planning/immediate backup system, and (iv) system design and configuration. These strategies are expected to help healthcare staff, analysts, reporters, researchers, and relevant stakeholders improve care delivery and patient safety in medical imaging in the context of any system upgrades.

A Model-Based Systematic Innovative Design for Sonic Logging Instruments in Natural Gas Wells.

With the continued development of natural gas extraction technologies, the accurate determination of downhole temperature and pressure has become increasingly important. It is crucial for the optimization of gas well production and an important measure to prevent accidents. However, existing logging instruments have a series of deficiencies in measurement and cannot adequately monitor modern natural gas. In response to these problems, in this paper, we propose a new model-based systematic innovation design method for designing logging instruments and simulations using finite element software. Our research results confirm the theoretical and practical utility of this model-based design method and provide a novel approach to designing logging instruments.

Design and implementation of college students' physical education teaching information management system by data mining technology.

This study intends to improve the efficiency of physical education teaching management, accelerate the normal teaching process, and meet the modern management requirements that traditional teaching management methods cannot meet. Based on data mining technology, this study designs a college student physical education teaching information management system, and makes a detailed design of each functional module. The main task of this study is to investigate how to effectively integrate data mining techniques with existing university student physical education teaching databases. Then, this study finds useful data information from massive data information to provide information support for university student physical education teaching. In order to effectively mine the relevant information of the data, the student evaluation module in the system is designed based on decision trees, and the teacher-student related data analysis module in the system is designed based on association rules. The research results indicate that 1039 records and 8205 student records are extracted from the teaching management database as mining objects. Rule 1: The support rate for "a professor's degree is a doctoral degree" is 20.4 %, indicating that there are 20.4 % of records in the teacher database that "the title is a professor and a doctoral degree"; the confidence level of Rule 1 is 78.2 %, indicating that 78.2 % of professors have a doctoral degree. Through the analysis of the rules that evaluate teaching as good, it can be found that the three attributes of professional title, education level, and teaching experience are the most important relevant factors affecting teaching effectiveness. Research has shown that the longer and richer the teaching experience, the stronger the teaching ability. Secondly, the mining results obtained through data mining techniques are analyzed. The maximum difference between the original algorithm's support mining results and the true values is 0.08, while the maximum difference between the improved algorithm's support mining results and the true values is 0.01. Compared to the original algorithm, the improved algorithm's mining results are accurate and effective. The application of data mining ideas in this system has laid a solid foundation for the development of physical education and teaching. Moreover, a three-layer system architecture model is adopted to better adapt to the development of school physical education, which is beneficial for later system maintenance and greatly reduces the work pressure of teachers. The system has been successfully launched and running in universities, and it is in good working condition.

Preferences for Text Messaging Supports During Youth Transition to Adult Mental Health Services: Theory-Informed Modified e-Delphi Study.

BACKGROUND: For many young people, the transition from child to adult mental health services is a vulnerable time associated with treatment disengagement and illness progression. Providing service information and options to youth, appealing to them, and tailoring to their needs during this period could help overcome systematic barriers to a successful transition. We know little about how SMS text message-based interventions might be leveraged to support the motivational, informational, and behavioral needs of youth during this time. Ascertaining youth preferences for the content and functionality of an SMS text message service could inform prototype development. OBJECTIVE: This study investigated consensus preferences among youth on important content, technology features, and engagement supports to inform a transition-focused SMS text message service. METHODS: A modified e-Delphi survey design was used to collect demographics, current levels of technology use, importance ratings on message content, preferred technical features, and barriers and enablers to engagement for youth in Canada aged 16-26 years who have accessed mental health services within the past 5 years. Survey items on content were categorized according to the information-motivation-behavioral skills (IMB) model. Survey items on technical features were categorized according to the persuasive system design (PSD) model. A predefined consensus rating matrix and descriptive statistics were used to characterize the sample. The high consensus threshold was 70%. RESULTS: A total of 100 participants, predominantly non-White (n=47, 47%), aged 20-26 years (n=59, 59%), and who had first accessed mental health services between the ages of 13 and 19 years (n=60, 60%), were selected. The majority (n=90, 90%) identified as daily SMS text message users. A high level of consensus on importance ratings was reported in 45% (9/20) of content items based on the IMB model. There were higher levels of consensus on importance ratings related to behavior domain items (3/3, 100%) than information domain items (4/9, 44%) or motivation domain items (2/8, 25%). A high level of consensus on importance ratings was reported in only 19% (4/21) of feature and functionality items based on the PSD model. Among PSD model categories, there was a high level of consensus on importance ratings in 8% (1/12) of the primary task support domain items and 100% (3/3) of the system credibility support domain items. None of the dialogue-support and social-support domain items met the high level of consensus thresholds. In total, 27% (27/100) of youth indicated that the most significant enabler for engaging with a transition-focused SMS text message intervention was the personalization of text messages. CONCLUSIONS: Scientists developing next-generation SMS text messaging interventions for this population need to consider how levels of consensus on different features may impact feasibility and personalization efforts. Youth can (and should) play an integral role in the development of these interventions.

A generic approach to developing human factors-quality assessment tools exemplified by the warehouse error prevention tool.

This study proposes a generic approach for creating human factors-based assessment tools to enhance operational system quality by reducing errors. The approach was driven by experiences and lessons learned in creating the warehouse error prevention (WEP) tool and other system engineering tools. The generic approach consists of 1) identifying tool objectives, 2) identifying system failure modes, 3) specifying design-related quality risk factors for each failure mode, 4) designing the tool, 5) conducting user evaluations, and 6) validating the tool. The WEP tool exemplifies this approach and identifies human factors related to design flaws associated with quality risk factors in warehouse operations. The WEP tool can be used at the initial stage of design or later for process improvement and training. While this process can be adapted for various contexts, further study is necessary to support the teams in creating tools to identify design-related human factors contributing to quality issues.

This paper describes a generic approach to creating human factors­based quality assessment tools. The approach is illustrated with the Warehouse Error Prevention (WEP) tool, which is designed to help users identify HF-related quality risk factors in warehouse system designs (available for free: Setayesh et al. 2022b).

A Survey of Visible-Light-Communication-Based Indoor Positioning Systems.

There is a growing demand for indoor positioning systems (IPSs) in a wide range of applications. However, traditional solutions such as GPS face many technical challenges. In recent years, a promising alternative has been emerging, the visible light communication (VLC)-based IPS, which offers a combination of high accuracy, low cost, and energy efficiency. This article presents a comprehensive review of VLC-based IPSs, providing a tutorial-like overview of the system. It begins by comparing various positioning systems and providing background information on their inherent limitations. Experimental results have demonstrated that VLC-based systems can achieve localization accuracy to within 10 cm in controlled environments. The mechanisms of VLC-based IPSs are then discussed, including a comprehensive examination of their performance metrics and underlying assumptions. The complexity, operating range, and efficiency of VLC-based IPSs are examined by analyzing factors such as channel modeling, signal processing, and localization algorithms. To optimize VLC-based IPSs, various strategies are explored, including the design of efficient modulation schemes, the development of advanced encoding and decoding algorithms, the implementation of adaptive power control, and the application of state-of-the-art localization algorithms. In addition, system parameters are carefully examined. These include LED placement, receiver sensitivity, and transmit power. Their impact on energy efficiency and localization accuracy is highlighted. Altogether, this paper serves as a comprehensive guide to VLC IPSs, providing in-depth insights into their vast potential and the challenges that they present.

A review of incidents related to health information technology in Swedish healthcare to characterise system issues as a basis for improvement in clinical practice.

This study examined health information technology-related incidents to characterise system issues as a basis for improvement in Swedish clinical practice. Incident reports were collected through interviews together with retrospectively collected incidents from voluntary incident databases, which were analysed using deductive and inductive approaches. Most themes pertained to system issues, such as functionality, design, and integration. Identified system issues were dominated by technical factors (74%), while human factors accounted for 26%. Over half of the incidents (55%) impacted on staff or the organisation, and the rest on patients - patient inconvenience (25%) and patient harm (20%). The findings indicate that it is vital to choose and commission suitable systems, design out "error-prone" features, ensure contingency plans are in place, implement clinical decision-support systems, and respond to incidents on time. Such strategies would improve the health information technology systems and Swedish clinical practice.

Health system description and assessment: a scoping review of templates for systematic analyses.

BACKGROUND: Understanding and comparing health systems is key for cross-country learning and health system strengthening. Templates help to develop standardised and coherent descriptions and assessments of health systems, which then allow meaningful analyses and comparisons. Our scoping review aims to provide an overview of existing templates, their content and the way data is presented. MAIN BODY: Based on the WHO building blocks framework, we defined templates as having (1) an overall framework, (2) a list of indicators or topics, and (3) instructions for authors, while covering (4) the design of the health system, (5) an assessment of health system performance, and (6) should cover the entire health system. We conducted a scoping review of grey literature published between 2000 and 2023 to identify templates. The content of the identified templates was screened, analyzed and compared. We found 12 documents that met our inclusion criteria. The building block `health financing´ is covered in all 12 templates; and many templates cover ´service delivery´ and ´health workforce'. Health system performance is frequently assessed with regard to 'access and coverage', 'quality and safety', and 'financial protection'. Most templates do not cover 'responsiveness' and 'efficiency'. Seven templates combine quantitative and qualitative data, three are mostly quantitative, and two are primarily qualitative. Templates cover data and information that is mostly relevant for specific groups of countries, e.g. a particular geographical region, or for high or for low and middle-income countries (LMICs). Templates for LMICs rely more on survey-based indicators than administrative data. CONCLUSIONS: This is the first scoping review of templates for standardized descriptions of health systems and assessments of their performance. The implications are that (1) templates can help analyze health systems across countries while accounting for context; (2) template-guided analyses of health systems could underpin national health policies, strategies, and plans; (3) organizations developing templates could learn from approaches of other templates; and (4) more research is needed on how to improve templates to better achieve their goals. Our findings provide an overview and help identify the most important aspects and topics to look at when comparing and analyzing health systems, and how data are commonly presented. The templates were created by organizations with different agendas and target audiences, and with different end products in mind. Comprehensive health systems analyses and comparisons require production of quantitative indicators and complementing them with qualitative information to build a holistic picture. CLINICAL TRIAL REGISTRATION:   Not applicable.

System Design for Sensing in Manufacturing to Apply AI through Hierarchical Abstraction Levels.

Activity recognition combined with artificial intelligence is a vital area of research, ranging across diverse domains, from sports and healthcare to smart homes. In the industrial domain, and the manual assembly lines, the emphasis shifts to human-machine interaction and thus to human activity recognition (HAR) within complex operational environments. Developing models and methods that can reliably and efficiently identify human activities, traditionally just categorized as either simple or complex activities, remains a key challenge in the field. Limitations of the existing methods and approaches include their inability to consider the contextual complexities associated with the performed activities. Our approach to address this challenge is to create different levels of activity abstractions, which allow for a more nuanced comprehension of activities and define their underlying patterns. Specifically, we propose a new hierarchical taxonomy for human activity abstraction levels based on the context of the performed activities that can be used in HAR. The proposed hierarchy consists of five levels, namely atomic, micro, meso, macro, and mega. We compare this taxonomy with other approaches that divide activities into simple and complex categories as well as other similar classification schemes and provide real-world examples in different applications to demonstrate its efficacy. Regarding advanced technologies like artificial intelligence, our study aims to guide and optimize industrial assembly procedures, particularly in uncontrolled non-laboratory environments, by shaping workflows to enable structured data analysis and highlighting correlations across various levels throughout the assembly progression. In addition, it establishes effective communication and shared understanding between researchers and industry professionals while also providing them with the essential resources to facilitate the development of systems, sensors, and algorithms for custom industrial use cases that adapt to the level of abstraction.

HELPeR: Interface Design Decision and Evaluation.

Inequities in health information access contribute to disparities in health outcomes. Health recommender systems have emerged as a promising solution to help users find the right information. Despite their various applications, it remains understudied how these systems can aid cancer patients. In this paper, we introduce HELPeR, a recommender system designed to assist ovarian cancer patients with their information needs. The design addresses cold-start challenges, drawing input from health experts and ovarian cancer forum posts. We evaluated HELPeR with nurse practitioners in a cold-start scenario, highlighting its benefits and areas for future improvement.

Design of Path-Planning System for Interventional Thermal Ablation of Liver Tumors Based on CT Images.

OBJECTIVE: Aiming at the shortcomings of artificial surgical path planning for the thermal ablation of liver tumors, such as the time-consuming and labor-consuming process, and relying heavily on doctors' puncture experience, an automatic path-planning system for thermal ablation of liver tumors based on CT images is designed and implemented. METHODS: The system mainly includes three modules: image segmentation and three-dimensional reconstruction, automatic surgical path planning, and image information management. Through organ segmentation and three- dimensional reconstruction based on CT images, the personalized abdominal spatial anatomical structure of patients is obtained, which is convenient for surgical path planning. The weighted summation method based on clinical constraints and the concept of Pareto optimality are used to solve the multi-objective optimization problem, screen the optimal needle entry path, and realize the automatic planning of the thermal ablation path. The image information database was established to store the information related to the surgical path. RESULTS: In the discussion with clinicians, more than 78% of the paths generated by the planning system were considered to be effective, and the efficiency of system path planning is higher than doctors' planning efficiency. CONCLUSION: After improvement, the system can be used for the planning of the thermal ablation path of a liver tumor and has certain clinical application value.

Biochar imparted constructed wetlands (CWs) for enhanced biodegradation of organic and inorganic pollutants along with its limitation.

The remediation of polluted soil and water stands as a paramount task in safeguarding environmental sustainability and ensuring a dependable water source. Biochar, celebrated for its capacity to enhance soil quality, stimulate plant growth, and adsorb a wide spectrum of contaminants, including organic and inorganic pollutants, within constructed wetlands, emerges as a promising solution. This review article is dedicated to examining the effects of biochar amendments on the efficiency of wastewater purification within constructed wetlands. This comprehensive review entails an extensive investigation of biochar's feedstock selection, production processes, characterization methods, and its application within constructed wetlands. It also encompasses an exploration of the design criteria necessary for the integration of biochar into constructed wetland systems. Moreover, a comprehensive analysis of recent research findings pertains to the role of biochar-based wetlands in the removal of both organic and inorganic pollutants. The principal objectives of this review are to provide novel and thorough perspectives on the conceptualization and implementation of biochar-based constructed wetlands for the treatment of organic and inorganic pollutants. Additionally, it seeks to identify potential directions for future research and application while addressing prevailing gaps in knowledge and limitations. Furthermore, the study delves into the potential limitations and risks associated with employing biochar in environmental remediation. Nevertheless, it is crucial to highlight that there is a significant paucity of data regarding the influence of biochar on the efficiency of wastewater treatment in constructed wetlands, with particular regard to its impact on the removal of both organic and inorganic pollutants.

Operational disruption in healthcare associated with software functionality issue due to software security patching: a case report.

Despite many benefits, the extensive deployment of Health Information Technology (HIT) systems by healthcare organizations has encountered many challenges, particularly in the field of telemetry concerning patient monitoring and its operational workflow. These challenges can add more layers of complexity when an unplanned software security patching is performed, affecting patient monitoring and causing disruption in daily clinical operations. This study is a reflection on what happened associated with software security patching and why it happened through the lens of an incident report to develop potential preventive and corrective strategies using qualitative analyses-inductive and deductive approaches. There is a need for such analyses to identify the underlying mechanism behind such issues since very limited research has been conducted on the study of software patching. The incident was classified as a "software functionality" issue, and the consequence was an "incident with a noticeable consequence but no patient harm", and the contributing factor was a software update, i.e., software security patching. This report describes how insufficient planning of software patching, lack of training for healthcare professionals, contingency planning on unplanned system disruption, and HIT system configuration can compromise healthcare quality and cause risks to patient safety. We propose 15 preventive and corrective strategies grouped under four key areas based on the system approach and social-technical aspects of the patching process. The key areas are (i) preparing, developing, and deploying patches; (ii) training the frontline operators; (iii) ensuring contingency planning; and (iv) establishing configuration and communication between systems. These strategies are expected to minimize the risk of HIT-related incidents, enhance software security patch management in healthcare organizations, and improve patient safety. However, further discussion should be continued about general HIT problems connected to software security patching.

MedLingua: A conceptual framework for a multilingual medical conversational agent.

This study introduces a hybrid model for an advanced medical chatbot addressing crucial healthcare communication challenges. Leveraging a hybrid ML model, the chatbot aims to provide accurate and prompt responses to users' health-related queries. The proposed model will overcome limitations observed in previous medical chatbots by integrating a dual-stemming approach, P-Stemmer and NLTK-Stemmer, accommodating both semitic and non-semitic languages. The system prioritizes the analysis of cognates, identification of symptoms, doctor recommendations, and prescription generation. It integrates an automatic translation module to facilitate a smooth multilingual diagnostic experience. Following the Scrum methodology for agile development, the framework ensures adaptability to evolving research needs and stays current with recent medical discoveries. This groundbreaking idea aims to improve the effectiveness and availability of healthcare services by introducing an intelligent, multilingual chatbot. This technology enables patients to communicate with doctors from diverse linguistic backgrounds through an automated language translation model, eliminating language barriers and extending healthcare access to rural regions worldwide.•A simple but efficient hybrid conceptual model for advancement in smart medical assistance.•This conceptual model can be applied to implement a medical chatbot that can understand multiple languages.•This method can be utilized to address medical chatbot limitations and enhance accuracy in response generation.

Exploring the Use of Persuasive System Design Principles to Enhance Medication Incident Reporting and Learning Systems: Scoping Reviews and Persuasive Design Assessment.

BACKGROUND: Medication incidents (MIs) causing harm to patients have far-reaching consequences for patients, pharmacists, public health, business practice, and governance policy. Medication Incident Reporting and Learning Systems (MIRLS) have been implemented to mitigate such incidents and promote continuous quality improvement in community pharmacies in Canada. They aim to collect and analyze MIs for the implementation of incident preventive strategies to increase safety in community pharmacy practice. However, this goal remains inhibited owing to the persistent barriers that pharmacies face when using these systems. OBJECTIVE: This study aims to investigate the harms caused by medication incidents and technological barriers to reporting and identify opportunities to incorporate persuasive design strategies in MIRLS to motivate reporting. METHODS: We conducted 2 scoping reviews to provide insights on the relationship between medication errors and patient harm and the information system-based barriers militating against reporting. Seven databases were searched in each scoping review, including PubMed, Public Health Database, ProQuest, Scopus, ACM Library, Global Health, and Google Scholar. Next, we analyzed one of the most widely used MIRLS in Canada using the Persuasive System Design (PSD) taxonomy-a framework for analyzing, designing, and evaluating persuasive systems. This framework applies behavioral theories from social psychology in the design of technology-based systems to motivate behavior change. Independent assessors familiar with MIRLS reported the degree of persuasion built into the system using the 4 categories of PSD strategies: primary task, dialogue, social, and credibility support. RESULTS: Overall, 17 articles were included in the first scoping review, and 1 article was included in the second scoping review. In the first review, significant or serious harm was the most frequent harm (11/17, 65%), followed by death or fatal harm (7/17, 41%). In the second review, the authors found that iterative design could improve the usability of an MIRLS; however, data security and validation of reports remained an issue to be addressed. Regarding the MIRLS that we assessed, participants considered most of the primary task, dialogue, and credibility support strategies in the PSD taxonomy as important and useful; however, they were not comfortable with some of the social strategies such as cooperation. We found that the assessed system supported a number of persuasive strategies from the PSD taxonomy; however, we identified additional strategies such as tunneling, simulation, suggestion, praise, reward, reminder, authority, and verifiability that could further enhance the perceived persuasiveness and value of the system. CONCLUSIONS: MIRLS, equipped with persuasive features, can become powerful motivational tools to promote safer medication practices in community pharmacies. They have the potential to highlight the value of MI reporting and increase the readiness of pharmacists to report incidents. The proposed persuasive design guidelines can help system developers and community pharmacy managers realize more effective MIRLS.

Steady-Hand Eye Robot 3.0: Optimization and Benchtop Evaluation for Subretinal Injection.

Subretinal injection methods and other procedures for treating retinal conditions and diseases (many considered incurable) have been limited in scope due to limited human motor control. This study demonstrates the next generation, cooperatively controlled Steady-Hand Eye Robot (SHER 3.0), a precise and intuitive-to-use robotic platform achieving clinical standards for targeting accuracy and resolution for subretinal injections. The system design and basic kinematics are reported and a deflection model for the incorporated delta stage and validation experiments are presented. This model optimizes the delta stage parameters, maximizing the global conditioning index and minimizing torsional compliance. Five tests measuring accuracy, repeatability, and deflection show the optimized stage design achieves a tip accuracy of < 30 µm, tip repeatability of 9.3 µm and 0.02°, and deflections between 20-350 µm/N. Future work will use updated control models to refine tip positioning outcomes and will be tested on in vivo animal models.

Characterizing patient details-related challenges from health information technology-related incident reports from Swedish healthcare.

Introduction: Despite many benefits offered by Health Information Technology (HIT) systems, new technology brings new and unforeseen risks to healthcare quality and patient safety if they're not properly planned, designed, implemented, and managed. This study examined health information technology-related (HIT) incidents to identify patient details-related issues, their association with contributing factors, and outcomes. Methods: Sources of information comprised retrospectively collected incident reports (n = 95) using two sampling methods, i.e., purposive and snowball sampling. The incident reports were analyzed using both the inductive method (thematic analysis) and the deductive approach using an existing framework, i.e., the International Classification for Patient Safety. Results: The studies identified 90 incidents with 120 patient details-related issues-categorized as either information-related (48%) or documentation-related (52%) problems; around two-thirds of the 120 issues were characterized by human factors. Of the total sample, 87 contributing factors were identified, of which "medical device/system" (45%) and "documentation" (20%) were the most common contributing factors. Of 90 incidents, more than half (59%) comprised patient-related outcomes-patient inconvenience (47%) and patient harm (12%) and the remaining 41% (n = 37) included staff or organization-related outcomes. Discussion: More than half of the incidents resulted in patient-related outcomes, namely patient inconvenience and patient harm, including disease risks, severe health deterioration, injury, and even patient death. Incidents associated with patient details can cause deleterious effects; therefore, characterizing them should be a routine part of clinical practice to improve the constantly changing healthcare system.

Design and sequential jumping experimental validation of a musculoskeletal bipedal robot based on the spring-loaded inverted pendulum model.

To effectively control a robot's motion, it is common to employ a simplified model that approximates the robot's dynamics. Nevertheless, discrepancies between the actual mechanical properties of the robot and the simplified model can result in motion failures. To address this issue, this study introduces a pneumatic-driven bipedal musculoskeletal robot designed to closely match the mechanical characteristics of a simplified spring-loaded inverted pendulum (SLIP) model. The SLIP model is widely utilized in robotics due to its passive stability and dynamic properties resembling human walking patterns. A musculoskeletal bipedal robot was designed and manufactured to concentrate its center of mass within a compact body around the hip joint, featuring low leg inertia in accordance with SLIP model principles. Furthermore, we validated that the robot exhibits similar dynamic characteristics to the SLIP model through a sequential jumping experiment and by comparing its performance to SLIP model simulation.

Elderly users' perceptions of signage systems from tertiary hospitals in Guangzhou.

Wayfinding in hospitals today is a significant challenge for urban residents, especially for the elderly. This study investigated the perceptions and attitudes of the elderly toward existing hospital signage systems to identify the wayfinding needs in the healthcare environment. This study collected 762 elderly participants' perceptions and personal preferences regarding 12 features of the existing signage systems in three hospitals in the Yuexiu, Haizhu, and Liwan districts of Guangzhou using a questionnaire methodology. The study further explored the differences in perceptions and preferences for signage based on the gender, age, and educational level of the elderly participants. The findings indicate that most of the elderly participants experienced becoming lost in the hospital; they typically chose to ask others for directions first, followed by using the signage system. Most of the elderly participants had positive attitudes toward the current hospital signage system. Furthermore, they emphasized the importance of the signage system's graphics, texts, colors, and updates, which directly affects the readability and comprehensibility of signs. We found gender differences in perceptions and attitudes toward signage; male participants had more positive attitudes toward the hospital signage systems than female participants. Additionally, consistent with previous findings, the older the age of participants, the less comprehension they had regarding signage graphic symbols. We also found that the more educated elderly participants were, the more understanding of signage they had. At the same time, however, they were less satisfied, which is possibly because the more educated they were, the more aware they were of signage issues.