Interface Prototype Research Articles

Electronic Co-design (ECO-design) Workshop for Increasing Clinician Participation in the Design of Health Services Interventions: Participatory Design Approach.

BackgroundParticipation from clinician stakeholders can improve the design and implementation of health care interventions. Participatory design methods, especially co-design methods, comprise stakeholder-led design activities that are time-consuming. Competing work demands and increasing workloads make clinicians’ commitments to typical participatory methods even harder. The COVID-19 pandemic further exacerbated barriers to clinician participation in such interventions.ObjectiveThe aim of this study was to explore a web-based participatory design approach to conduct economical, electronic co-design (ECO-design) workshops with primary care clinicians.MethodsWe adapted traditional in-person co-design workshops to web-based delivery and adapted co-design workshop series to fit within a single 1-hour session. We applied the ECO-design workshop approach to codevelop feedback interventions regarding abnormal test result follow-up in primary care. We conducted ECO-design workshops with primary care clinicians at a medical center in Southern Texas, using videoconferencing software. Each workshop focused on one of three types of feedback interventions: conversation guide, email template, and dashboard prototype. We paired electronic materials and software features to facilitate participant interactions, prototyping, and data collection. The workshop protocol included four main activities: problem identification, solution generation, prototyping, and debriefing. Two facilitators were assigned to each workshop and one researcher resolved technical problems. After the workshops, our research team met to debrief and evaluate workshops.ResultsA total of 28 primary care clinicians participated in our ECO-design workshops. We completed 4 parallel workshops, each with 5-10 participants. We conducted traditional analyses and generated a clinician persona (ie, representative description) and user interface prototypes. We also formulated recommendations for future ECO-design workshop recruitment, technology, facilitation, and data collection. Overall, our adapted workshops successfully enabled primary care clinicians to participate without increasing their workload, even during a pandemic.ConclusionsECO-design workshops are viable, economical alternatives to traditional approaches. This approach fills a need for efficient methods to involve busy clinicians in the design of health care interventions.

A Generic Approach towards Amharic Sign Language Recognition

In the day-to-day life of communities, good communication channels are crucial for mutual understanding. The hearing-impaired community uses sign language, which is a visual and gestural language. In terms of orientation and expression, it is separate from written and spoken languages. Despite the fact that sign language is an excellent platform for communication among hearing-impaired persons, it has created a communication barrier between hearing-impaired and non-disabled people. To address this issue, researchers have proposed sign language to text translation systems for English and other European languages as a solution. The goal of this research is to design and develop an Amharic digital text converter system using Ethiopian sign language. The proposed system was created with the help of two key deep learning algorithms: a pretrained deep learning model and a Long Short-Term Memory (LSTM). The LSTM was used to extract sequence information from a sequence of image frames of a specific sign language, while the pretrained deep learning model was used to extract features from single frame images. The dataset used to train the algorithms was gathered in video format from Addis Ababa University. Prior to feeding the obtained dataset to the deep learning models, data preprocessing activities such as cleaning and video to image frame segmentation were conducted. The system was trained, validated, and tested using 80%, 10%, and 10% of the 2475 images created during the preprocessing step. Two pretrained deep learning models, EfficientNetB0 and ResNet50, were used in this investigation, and they attained an accuracy of 72.79%. In terms of precision and f1-score, ResNet50 outperformed EfficientNetB0. For the proposed system, a graphical user interface prototype was created, and the best performing model was chosen and implemented. The proposed system can be utilized as a starting point for other researchers to improve upon, based on the outcomes of the experiment. More high-quality training datasets and high-performance training machines, such as GPU-enabled computers, can be added to the system to improve it.

Design Factors of Shared Situation Awareness Interface in Human–Machine Co-Driving

Automated vehicles can perceive their environment and control themselves, but how to effectively transfer the information perceived by the vehicles to human drivers through interfaces, or share the awareness of the situation, is a problem to be solved in human–machine co-driving. The four elements of the shared situation awareness (SSA) interface, namely human–machine state, context, current task status, and plan, were analyzed and proposed through an abstraction hierarchy design method to guide the output of the corresponding interface design elements. The four elements were introduced to visualize the interface elements and design the interface prototype in the scenario of “a vehicle overtaking with a dangerous intention from the left rear”, and the design schemes were experimentally evaluated. The results showed that the design with the four elements of an SSA interface could effectively improve the usability of the human–machine interface, increase the levels of human drivers’ situational awareness and prediction of dangerous intentions, and boost trust in the automatic systems, thereby providing ideas for the design of human–machine collaborative interfaces that enhance shared situational awareness in similar scenarios.

FUZZY ESTIMATION PROCEDURE OF THE CONCENTRATION OF THE COMPONENTS OF A SULFURIC ACID PICKLING SOLUTION

The article is devoted to the issue of determining the level of concentration of individual components of working solutions. The relevance of the topic lies in the fact that some impurities in solutions (for example, when pickling steel) cannot be measured automatically, which reduces the efficiency of the process and increases the load on the solution regeneration section. Also, impurities are hazardous waste for the environment and humans.
 The development of a method for the operational control of the composition of the pickling solution components in pickling baths is the main task of the work. A detailed substantiation of the choice of the mathematical apparatus of the method is given. The process of fuzzy identification of the composition of the components is carried out by the number of pixels with certain digital color RGB codes from digital images of the control doses of the solution. A set of technical means for providing the method for practical implementation in the technological process is described. A prototype of a graphical user interface (GUI) for the proposed method for identifying the composition of technological liquid solutions, developed in the Processing 3.0 integrated environment using applications from the Open Source Computer Vision Library, is presented.
 A technique for extracting experimental data for filling the base of a fuzzy classifier with model reference points is proposed. Its essence lies in simultaneous measurements of the concentration of the components of the pickling solution by classical methods of titration and dry residues and the proposed method with a step equal to the regulated accuracy. The results of approbation of the proposed method are presented.
 The presented technique for obtaining a fuzzy classifier can be used to develop IT tools for the operational control of the composition of various liquid solutions with opaque colored components and color identification of defects in various flat surfaces, provided that they are color distinguishable and determine the boundaries of RGB - intervals for assessing the color of individual component (defects).

Emulating Textures Using Vibrotactile Technology: HaptTech System and its Adaptation to a Commercial Kinesthetic Interface

This article presents the development and testing of a tactile interface prototype, HaptTech, that applies vibrotactile stimulation patterns to the fingertip, as well as an analysis of its performance when coupled to the commercial kinesthetic interface Novint Falcon. Its applicability in digital entertainment expects to improve the level of immersion into virtual reality scenarios. In the first experiment, a group of 75 subjects compared three different vibration stimuli that emulated different textures. They evaluated the stimuli on a 1 to 10 scale, where 1 means ‘non-perceivable differences’ and 10 means ‘entirely differentiable’. The obtained mean values were 9 (textures 1 and 3), 8,29 (textures 1 and 2), and 7,43 (textures 2 and 3), indicating HaptTech’s capability to reproduce differentiable stimuli. In the second experiment, 31 subjects evaluated the coupling between HaptTech and Novint Falcon. They perceived differences when the HaptTech system was activated in the context of a comparison between kinesthetic and vibrotactile plus kinesthetic stimuli. In the third experiment, the subjects evaluated the similarity between the perceived stimuli on the hand and a visualized texture pattern in a virtual environment. The resulting median values were 8, 8, and 9 for textures 1, 2, and 3, respectively, which demonstrate that the subjects perceived a high correspondence for each one.

Improving user experience of color palette extraction by using interactive visualization based on hierarchical color model

Extracting color palettes from an image is a common practice used by artists in different visual domains. In this study, we introduce a novel tool for extracting color palettes from an image. Based on the hierarchical color model (HCM) (Jeong et al. (2019)), we develop a prototype user interface system comprising novel interactions and visualization. Our visualization is a node-link diagram tailored for the HCM; the accompanying interactions originate from the hierarchical structure. We evaluate our prototype system by performing a usability test and comparing it with contemporary alternatives for professional usage. The results from the user study validate the effectiveness of the presented approach. We also find a few user requirements that can be useful in the further development of the related tools. Moreover, we expect that the proposed interactive visualization can facilitate additional studies on the HCM. The prototype is available in the following URL: https://int-vis-hcm.web.app.

Pathling: analytics on FHIR

BackgroundHealth data analytics is an area that is facing rapid change due to the acceleration of digitization of the health sector, and the changing landscape of health data and clinical terminology standards. Our research has identified a need for improved tooling to support analytics users in the task of analyzing Fast Healthcare Interoperability Resources (FHIR®) data and associated clinical terminology.ResultsA server implementation was developed, featuring a FHIR API with new operations designed to support exploratory data analysis (EDA), advanced patient cohort selection and data preparation tasks. Integration with a FHIR Terminology Service is also supported, allowing users to incorporate knowledge from rich terminologies such as SNOMED CT within their queries. A prototype user interface for EDA was developed, along with visualizations in support of a health data analysis project.ConclusionsExperience with applying this technology within research projects and towards the development of analytics-enabled applications provides a preliminary indication that the FHIR Analytics API pattern implemented by Pathling is a valuable abstraction for data scientists and software developers within the health care domain. Pathling contributes towards the value proposition for the use of FHIR within health data analytics, and assists with the use of complex clinical terminologies in that context.

Autonomous Transit Service Design For Riders with Vision Impairment

Automated transportation systems will become the trend in the future, while the design challenges in improving accessibility and usability for visually impaired passengers will have to be resolved. This paper aims to use human factors methods in designing a concept inclusive user interface for the Autonomous Driving System for Dedicated Vehicles (ADS-DV). The concept prototype design evaluated in this study, ‘Smart Autonomous Vehicle for Visually Impaired’ (SAVVI), is designed to accommodate the accessibility needs of visually challenged passengers. We broke down the autonomous transit service for the people with a visual impairment from six essential tasks, including booking a ride, navigating to the vehicle, entering and sitting assistance, initiating the ride, the car traveling to the destination, and exiting the vehicle. First, a hierarchical task analysis was conducted, and a user interface prototype was designed and tested by visually challenged participants. The responses collected from the testing and surveys were divided into qualitative and quantitative data for better comprehension and implementation.

Designing a System to Mimic Expert Cognition: An Initial Prototype

In this paper, we present a proof-of-concept system to highlight the potential benefits of mimicking higher-order cognitive processes involved in ‘insight seeking’ to create the necessary context for expert sensemaking. We draw upon data from a realistic investigation exercise undertaken by 14 experienced intelligence analysts and use this to develop our prototype to mimic behaviours demonstrated by expert analysts. Our prototype system evaluates different strategies and provides recommendations for an analyst to explore, through a prototype user interface. The recommended strategies, and associated information retrieved, aligns with the actual investigations. We propose that our system presents a novel and promising approach to design AI support systems for tasks that typically require human expert cognitive processes.

Innovating Walking Speed as a Vital Sign: An Interface Development and Usability Study

Measuring walking speed is becoming a more useful tool for assessing overall patient health along with the other five vital signs: temperature, blood pressure, pulse, respiratory rate, and pain. Clinicians consider walking speed to be the “sixth vital sign”. Standardization in measuring walking speed remains elusive and current methods may lead to inconsistent and inaccurate results. This study focused on testing an interface prototype that provides the user with a record-based platform for analyzing walking speed. Two usability studies were conducted with two separate iterations of interfaces. This paper focuses on the second interface, which was a refined version of the first interface. Data obtained through usability metrics and verbal protocol analyses (VPAs) was analyzed. Results from this study provided suggestions for improving the second interface’s ease of use and overall task interaction. Future work will address improving the interface prototype and converting it to a fully-programmed version.

Interface Design for Evaluation of Clinical Decision Support for Quality Improvement

Clinical decision support (CDS) is a process for enhancing health-related decisions and actions with pertinent, organized clinical knowledge and patient information that can significantly improve health outcomesand healthcare delivery. However, their impact on clinical outcomes has been inconsistent. Rigorous and continuous evaluation of CDS is necessary for improving CDS. An interface prototype designed based on User and Task analysis wasevaluated to measure its usability and effectiveness in evaluating CDSeffectiveness for improving quality outcomes based on the analysis. The results show that task of evaluating CDS effectiveness is relatively hard, and moreworkmay be needed to guide usersreach correct conclusions.

Design and Field Test of a Mobile Augmented Reality Human–Machine Interface for Virtual Stops in Shared Automated Mobility On-Demand

Shared automated mobility on-demand (SAMOD) is considered as a promising mobility solution in the future. Users book trips on-demand via a smartphone, and service algorithms set up virtual stops (vStop) where users then need to walk to board the automated shuttle. Navigation and identification of the virtual pickup location, which has no references in the real world, can be challenging. Providing users with an intuitive information system in that situation is essential to achieve high user acceptance of new automated mobility services. Our novel vStop human–machine interface (HMI) prototype for mobile augmented reality (AR) supports users with information in reference to the street environment. This work firstly presented the results of an online interview study (N = 21) to conceptualize an HMI. Secondly, the HMI was prototyped by means of AR and evaluated (N = 45) regarding user experience (UX), workload, and acceptance. The results show that the AR prototype provided high rates of UX especially in terms of high pragmatic quality. Furthermore, cognitive workload when using the HMI was low, and acceptance ratings were high. The results show the positive perception of AR for navigation tasks in general and the highly assistive character of the vStop prototype in particular. In the future, SAMOD services can provide customers with vStop HMIs to foster user acceptance and smooth operation of their service.

Metaverse Interface with Haptic and Rigid Sense Feedback at a Low Cost

In the metaverse era, anyone should be able to easily access the metaverse for non-discrimination. This study proposes a prototype of a metaverse interface that can be implemented at a low price. It shows reasonable performance. It includes the following 4 modules. 1. Haptic feedback: Piezo sensors have been used for tactile information of various textures, which is transported as an audio data format, and reconstructed at the fingertips by an actuator (LRA motor) attached to a glove. 2. Force feedback: The module was designed to control the servomotor through 3D modeling. It provides force feedback by controlling the servo motor to grab the hand as much as the thickness of the object on Unity, the game engine. 3. Controller: Reproduce finger movement in Unity by measuring resistance change according to finger bending using a Flex sensor. Implement Yawing/Pitching/Rolling movement in Unity through MPU-6050(IMU) sensor. 4. Pose estimation: The user's current movement captured by the webcam is used for pose estimation through the Mediapipe library. It is integrated with the hand posture received serially from the controller to render the user posture inside the Unity game. The developed interface can be applied to life logging service and mirror world service, which are one of the most important applications in the metaverse.

Software development system for creation adaptive user interfaces

To improve the efficiency of the design engineer, the use of design automation systems is required. Currently, computeraided design tools are multifunctional and have an expanded user interface. Depending on the scope of the task to be solved and the level of training, the design engineer does not need all the means of computer-aided design systems. In this case, an adaptive interface can serve as a means of increasing labor productivity, which can be customized for a particular user, taking into account his experience and physiological features (system experience, computer literacy, experience working with such programs, typing, color blindness, memory, hand motility). The characteristics by which a user system is evaluated have different degrees of uncertainty, ambiguity, and internal inconsistency. These characteristics are difficult to formalize and they are very specific. To perform the evaluation, it is advisable to use intelligent systems based on fuzzy logic and fuzzy sets. The most acceptable in this case is the Mamdani method which uses a minimax composition of fuzzy sets. The proposed mechanism includes a sequence of actions: fuzzification, fuzzy inference, composition, defazzification. A software development system has been developed that allows you to form an interface part of the software taking into account the capabilities of a particular user. The implementation of the developed software system allows you to select a set of elements individually for each design engineer and form an adaptive prototype of the application program interface. In this case, it becomes possible to improve the interaction between a person and a computer, make it more comfortable, reduce the time to search for the necessary functions and the number of erroneous actions, and improve the quality of the work done.

Design of Navigation Applications for People with Disabilities: A Review of Literature and Guideline Formulation

A mobile navigation application (App) can provide flexible wayfinding guidance, save time, and reduce stress for people in unfamiliar buildings or environments. Wayfinding is also a challenging task for individuals with disabilities. The objective of this study was to provide a comprehensive set of guidelines for designing navigation apps for individuals with disabilities. A review of the literature was conducted on scientific studies and commercially available navigation apps using Web of Science, Compendex, ACM Digital Library, IEEE Xplore, Wiley Online, Science Direct, SpringerLink, Taylor & Francis, Apple store, and Google Play. The findings led to 82 design guidelines categorized based on Nielsen’s usability principles. The guidelines were implemented in an interface prototype to help users navigate places within a shopping mall. The prototype demonstrated that the proposed design guidelines are easily applicable and provided a roadmap for the future design of navigation apps for people with different types of disabilities.

Engineering Annotations: A Generic Framework for Gluing Design Artefacts of Interactive Systems

Along the design process of interactive system multiple intermediate artefacts (such as user interface prototypes, task models, dialog models?) are created, tested, revised, and improved until the development team produces a full-fledged system. However, relevant information for describing the design solution and/or supporting design decisions (such as rational about the design, decisions made, recommendations, etc.) are not explicitly captured in the models/artefacts, hence the need for annotations. Many approaches argue against information duplication to increase maintainability of the artefacts. Nonetheless, annotations created on one artefact are usually relevant to other artefacts/models. So that, there is a need for tools and techniques to coordinate annotations across artefacts/models which is the contribution of the present work. In this paper, we propose a model-based approach that was conceived to handle annotations in a systematic way along the development process of interactive systems. As part of the solution, we propose an annotation model built upon the W3C's Web Annotation Data Model. The feasibility of the approach is demonstrated by means of a tool suite featuring a plugin, which has been deployed and tested over the multi-artefacts. The overall approach is illustrated on the design of an interactive cockpit application performing two design iterations. The contribution brings two main benefits for interactive systems engineering: i) it presents a generic pattern for integrating information in multiple usually heterogenous artefacts throughout the design process of interactive systems; and ii) it highlights the need for tools helping to rationalize and to document the various artefacts and the related decisions made during interactive systems design.

KidneyCloud: A Clinically-Codesigned Solution to Support Kidney Services with Assessing Patients for Transplantation.

There is a need for IT systems that support the complex needs of data management in kidney transplantation. The KidneyCloud project aims to inform a transplant-specific digital solution by exploring patient pathways and data journeys. This paper reports on the early prototyping of the KidneyCloud clinician interface using an iterative codesign methodology. User workshops identified that for making clinical decisions and adding patients to the national waiting list transplant teams relied heavily on manual processes to access data across systems and organisations. Based on the requirements gathered, a prototype interface was designed to provide a unified view on the available patient data, which aligned with clinical workflows. Interactive prototype screens allowed users to gain hands-on experience and provide rich real-time feedback. This informed the necessary functionalities of the interface, but also helped us understand the capabilities required of the back-end solution.

ROLEX: A Novel Method for Interpretable Machine Learning Using Robust Local Explanations

Recent developments in big data technologies are revolutionizing the field of healthcare predictive analytics (HPA), enabling researchers to explore challenging problems using complex prediction models. Nevertheless, healthcare practitioners are reluctant to adopt those models as they are less transparent and accountable due to their black-box structure. We believe that instance-level, or local, explanations enhance patient safety and foster trust by enabling patient-level interpretations and medical knowledge discovery. Therefore, we propose the RObust Local EXplanations (ROLEX) method to develop robust, instance-level explanations for HPA models in this study. ROLEX adapts state-of-the-art methods and ameliorates their shortcomings in explaining individual-level predictions made by black-box machine learning models. Our analysis with a large real-world dataset related to a prevalent medical condition called fragility fracture and two publicly available healthcare datasets reveals that ROLEX outperforms widely accepted benchmark methods in terms of local faithfulness of explanations. In addition, ROLEX is more robust since it does not rely on extensive hyperparameter tuning or heuristic algorithms. Explanations generated by ROLEX, along with the prototype user interface presented in this study, have the potential to promote personalized care and precision medicine by providing patient-level interpretations and novel insights. We discuss the theoretical implications of our study in healthcare, big data, and design science.

Affective Brain-Computer Music Interface in Emotion Regulation and Neurofeedback: A Research Protocol

Introduction: Emotion regulation is an integral part of mental health, dynamically impacting brain function as one’s emotions change continuously throughout the day. Impairments in emotion regulation are associated with a range of psychiatric disorders. Although the implications of emotion regulation are crucial to mental health, few studies have examined training emotion regulation strategies with respect to the brain. Thus, this manuscript will propose an affective brain-computer music interface (aBCMI) prototype for emotion regulation that continuously generates music by estimating emotions from real-time electroencephalography (EEG) signals. Methods: In this proposal, we describe our prototype consisting of an emotion classifier that detects the expression of emotions from EEG signals, and a music generator that generates music reflective of those emotions. We evaluate the prototype in three separate studies. In study 1, the accuracy of the music generator is tested. In study 2, the accuracy of the emotion classifier is tested by assessing its correlation with real-time, self-reported emotions. In study 3, the generative music algorithm is assessed to explore emotion regulation strategies. Discussion: The proposed BCMI is expected to accurately estimate emotions, provide musical feedback of participants’ emotions, and enable users to intentionally modulate their emotions from musical feedback. This involves capturing the listener’s emotions in real-time using EEG signals, providing the opportunity to regulate one’s emotional state with musical feedback. Thus, in addition to enabling greater neurofeedback training of emotions, our prototype can enhance the understanding of affective computing and emotions with EEG and machine learning. Conclusion: Clinical applications of this prototype may have a tremendous impact as a neurofeedback tool in music therapy for training emotion regulation. Future research may benefit from using the proposed BCMI as a neurofeedback treatment in mood disorders.

Ferrocenyl-containing silicone nanocomposites as materials for neuronal interfaces

A synthetic method involving hydrosilylation reactions was developed to produce nanocomposites of elastic ferrocenyl-containing silicone rubber (EFSR) and multi-walled carbon nanotubes (MWCNT). The EFSR-MWCNT nanocomposites have a satisfactory elongation at break ∼80%, tensile strength (2.4 MPa), as well as electrical conductivity comparable to that of semiconductors (7∙10 −5 S·cm −1 ), all of which are necessary for application as neuronal implants. A novel prototype of a spinal cord neuronal interface based on EFSR-MWCNT was created as a prosthetic for impaired neuronal functions and to access spinal sensorimotor networks. Ferrocenyl groups in nanocomposites increase the charge injection that declines the risks of negative effects of electrical stimulation including nerve tissue damage. • Ferrocenyl-containing silicone nanocomposites with carbon nanotubes were obtained. • The nanocomposites are semiconductors with suitable tensile properties. • A novel prototype of a spinal cord neural interface was created. • The nanocomposite electrodes promote spinal cord stimulation and locomotor circuitry.