Graphical Feedback Research Articles

Design of a teleoperated and mixed reality-based electric power live line working robot

This paper presents a novel teleoperation force feedback approach combining graphic and haptic feedback for enhanced telepresence. Visual force feedback is modeled through a fitting process, with the force direction established through coordinate transformations. To construct operational environments, a new scene recognition and reconstruction technique is proposed, based on the principles of binocular stereovision. This method is primarily designed for live-line work scenarios, focusing on power line wires. It involves image preprocessing, target image recognition and extraction, binocular stereo measurements, generating depth point clouds, and ultimately reconstructing three-dimensional models of the target objects. Ultimately, a novel electric power live line working robot system with a strong sense of telepresence is achieved, based on teleoperation and mixed reality.

ESMira: A decentralized open-source application for collecting experience sampling data.

This paper introduces ESMira, a server and mobile app (Android, iOS) developed for research projects using experience sampling method (ESM) designs. ESMira offers a very simple setup process and ease of use, while being free, decentralized, and open-source (source code is available on GitHub). The ongoing development of ESMira started in early 2019, with a focus on scientific requirements (e.g., informed consent, ethical considerations), data security (e.g., encryption), and data anonymity (e.g., completely anonymous data workflow). ESMira sets itself apart from other platforms by both being free of charge and providing study administrators with full control over study data without the need for specific technological skills (e.g., programming). This means that study administrators can have ESMira running on their own webspace without needing much technical knowledge, allowing them to remain independent from any third-party service. Furthermore, ESMira offers an extensive list of features (e.g., an anonymous built-in chat to contact participants; a reward system that allows participant incentivization without breaching anonymity; live graphical feedback for participants) and can deal with complex study designs (e.g., nested time-based sampling). In this paper, we illustrate the basic structure of ESMira, explain how to set up a new server and create studies, and introduce the platform's basic functionalities.

Patients' Experiences Using a Mobile Health App for Self-Care of Heart Failure in a Real-World Setting: Qualitative Analysis.

Publicly available patient-focused mobile health (mHealth) apps are being increasingly integrated into routine heart failure (HF)-related self-care. However, there is a dearth of research on patients' experiences using mHealth apps for self-care in real-world settings. The purpose of this study was to explore patients' experiences using a commercially available mHealth app, OnTrack to Health, for HF self-care in a real-world setting. Patient satisfaction, measured with a 5-point Likert scale, and an open-ended survey were used to gather data from 23 patients with HF who were provided the OnTrack to Health app as a part of routine HF management. A content analysis of patients' responses was conducted with the qualitative software Atlas.ti (version 8; ATLAS.ti Scientific Software Development GmbH). Patients (median age 64, IQR 57-71 years; 17/23, 74% male) used OnTrack to Health for a median 164 (IQR 51-640) days before the survey. All patients reported excellent experiences related to app use and would recommend the app to other patients with HF. Five themes emerged from the responses to the open-ended questions: (1) features that enhanced self-care of HF (medication tracker, graphic performance feedback and automated alerts, secured messaging features, and HF self-care education); (2) perceived benefits (provided assurance of safety, improved HF self-care, and decreased hospitalization rates); (3) challenges with using apps for self-care (giving up previous self-care strategies); (4) facilitators (perceived ease of use and availability of technical support); and (5) suggested improvements (streamlining data entry, integration of apps with an electronic medical record, and personalization of app features). Patients were satisfied with using OnTrack to Health for self-care. They perceived the features of the app as valuable tools for improving self-care ability and decreasing hospitalization rates. The development of apps in collaboration with end users is essential to ensure high-quality patient experiences related to app use for self-care.

Engineering Rehabilitation: Blending Two Tool-supported Approaches to Close the Loop from Tasks-based Rehabilitation to Exercises and Back Again

Post-stroke or post-brain injuries rehabilitation is a long-term process defined by therapists and tuned to the specific damages and their consequences for each patient. This process requires the definition of well-defined multiple exercises to be performed multiple times by each patient over a long period of time. One of the key findings in the rehabilitation domain is that exercises should be tasks and goals oriented to increase functional independence, enhance development and prevent disability [24]. Patients performing the exercises must be carefully monitored to identify progress, possible regression and prevent damages due to the inadequate performance of the exercises. The SIVIRE tool [20] provides interactive graphical feedback to patients about the performance of their exercises and deviations from nominal, planed practice but fails at providing high-level descriptions of exercises and at connecting them to high-level rehabilitation goals (e.g. gain autonomy in cleaning a room). The HAMSTERS-XLE tool [16] provides a tuneable editor and a simulator to describe goals and task models including low-level tasks covering perception of the various senses, cognition and motoric actions. This paper presents the integration of these two tools and the benefits it brings both to the patients and to the therapists. The resulting tool and its engineering are presented in detail highlighting some generic integration mechanisms. On a case study, we show how exercises can be defined in HAMSTERS-XLE, transferred to SIVRE for fine tuning, monitored by SIVRE during the multiple practices of the patient and transferred back again to HAMSTERS-XLE to monitor progress, identify issues with the exercises and provide therapists with goal and task-based data about patients' evolutions

TreatEEM—A Software Tool for the Interpretation of Fluorescence Excitation-Emission Matrices (EEMs) of Dissolved Organic Matter in Natural Waters

Fluorescence excitation-emission matrices (EEMs) are a useful tool in aquatic sciences for monitoring and studying the biogeochemistry of organic matter in natural waters and engineered systems. Yet, the interpretation of the wealth of information available in EEMs requires the use of appropriate software. Existing software tools for the analysis of EEMs, offered by instrument producers, have limited treatment capabilities, while other freely available tools are based on the MATLAB or R programming languages, which require a certain level of programming skills and a pre-installation of MATLAB or R. Here, we present TreatEEM, the first non-commercial, stand-alone Windows-based software tool that provides comprehensive treatment of EEMs. Its greatest advantage is its user-friendly and interactive graphical user interface, providing a convivial and responsive graphical feedback on any action performed on either a single spectrum (recorded at one excitation wavelength) or EEM. The capabilities of TreatEEM, including (a) basic EEM treatment, such as simple inner filter correction, scatter removal, blank subtraction, Raman normalisation, smoothing, drift alignment etc., (b) extraction of useful parameters for DOM characterisation (Coble peaks and fluorescence indices) and (c) preparation of data for PARAFAC analysis plus presentation/manipulation of obtained PARAFAC components, are described in detail, along with a basic theoretical background on these most commonly used treatment steps of EEMs.

Development and Validation of a Mixed-Reality Simulator for Reducing Biopsy Core Deviation During Simulated Freehand Systematic Prostate Biopsy.

We describe the development and validation of a mixed-reality prostate biopsy (PBx) simulator with built-in guidance aids and real-time 3-dimensional visualization. We evaluated our simulator during one-on-one training sessions with urology residents and attendings from 2018 to 2022. Participants performed freehand, side-fire, double-sextant transrectal ultrasound-guided systematic prostate biopsy (sPBx). After a baseline assessment (first set of 12 biopsy cores), participants trained for 25 minutes with visualization and cognitive aids activated. Training was followed by an exit set of 12 biopsy cores without visualization or cognitive aids and afterward, subjective assessment by trainees of the simulator. Deviation is the shortest distance of the center of a core from its intended template location. Baseline deviations (mean ± SD) for residents (n = 24) and attendings (n = 4) were 13.4 ± 8.9 mm and 8.5 ± 3.6 mm ( P < 0.001), respectively. Posttraining deviations were 8.7 ± 6.6 mm and 7.6 ± 3.7 mm ( P = 0.271), respectively. Deviations between baseline and exit were decreased significantly for residents ( P < 0.001) but not for attendings ( P = 0.093). Overall feedback from participants was positive. Confidence in performing a PBx increased in novices after training ( P = 0.011) and did not change among attendings ( P = 0.180). A new PBx simulator can quantify and improve accuracy during simulated freehand sPBx while providing visualization and graphical feedback. Improved simulated sPBx accuracy could lead to more even distribution of biopsy cores within the prostate when performed in clinical settings, possibly reducing the high risk of missing an existing lesion and thus decreasing the time to initiating treatment, if indicated.

ASAP: A Semi-Autonomous Precise System for Telesurgery During Communication Delays

In remote, rural, and disadvantaged areas, telesurgery can be severely hindered by limitations of communication infrastructure. In conventional telesurgery, delays as small as 300ms can produce fatal surgical errors. To mitigate the effect of communication delays during telesurgery, we introduce a semi-autonomous system that decouples the user interaction from the robot execution. This system uses a physics-based simulator where a surgeon can demonstrate individual surgical subtasks, with immediate graphical feedback. Each subtask is performed asynchronously, unaffected by communication latency, jitter, and packet loss. A surgical step recognition module extracts the intended actions from the observed surgeon-simulation interaction. The remote robot can perform each one of these actions autonomously. The action recognition system leveraged a transfer learning approach that minimized the data needed during training, and most of the learning is obtained from simulated data. We tested this system in two tasks: fluid-submerged peg transfer (resembling bleeding events) and surgical debridement. The system showed robustness to delays of up to 5 seconds, maintaining a performance rate of 87% for peg transfer and 88% for debridement. Also, the framework reduced the completion time under delays by 45% and 11% during peg transfer and debridement, respectively.

The Effect of Social Comparison Feedback and Value Statements in a Clinic

ABSTRACT This report from the field assessed the effects of graphic and verbal social comparison feedback on the number of end-of-shift cleaning tasks completed by behavior technicians in an autism clinic. Participants consisted of three individuals identified as exhibiting low performance relative to peers. Prior to the intervention, there was a notable difference between low-performers and high-performers. Following the intervention, the number of tasks increased for all three low-performers, reaching levels that were similar to their high-performing peers. Results suggest that for simple and straightforward tasks, certain applications of social comparison feedback can be useful for increasing performance in low-performers despite initial discrepancies in performance.

Rich data, poor information? Teachers’ perceptions of mean differences in graphical feedback from statewide tests

Data-based decision making in schools aims to address students’ needs and improve their performance by leveraging the information contained in data. However, to learn from data, teachers are required to transform them into actionable information. In two studies, we focused on how teachers can learn about the strengths and weaknesses of their class performance from statewide test data by investigating how sensitively, efficiently, and accurately they are able to judge the magnitude of mean differences. The results indicate that teachers can judge mean differences with very high accuracy (τ = .85) but only consider moderate and large effects to be meaningful, indicating low sensitivity. By systematically varying different graph types, we also found that participants quickly increased their efficiency in terms of dwell time when repeatedly confronted with a specific graph type and were most sensitive to the use of stacked or clustered bar graphs.

TiltWalker: Operating a Telepresence Robot with One-Hand by Tilt Controls on a Smartphone

Mobile clients for telepresence robots are cluttered with interactive elements that either leave a little room for the camera feeds or occlude them. Many do not provide meaningful feedback on the robot's state and most require the use of both hands. These make maneuvering telepresence robots difficult with mobile devices. TiltWalker enables controlling a telepresence robot with one hand using tilt gestures with a smartphone. In a series of studies, we first justify the use of a Web platform, determine how far and fast users can tilt without compromising the comfort and the legibility of the display content, and identify a velocity-based function well-suited for control-display mapping. We refine TiltWalker based on the findings of these studies, then compare it with a default method in the final study. Results revealed that TiltWalker is significantly faster and more accurate than the default method. Besides, participants preferred TiltWalker's interaction methods and graphical feedback significantly more than those of the default method.

Evaluation of a Telehealth Parent-Training Program in Japan: Collaboration with Parents to Teach Novel Mand Skills to Children Diagnosed with Autism Spectrum Disorder.

This study developed a telehealth parent-training program to teach parents of children with autism spectrum disorder the process of mand-training implementation in Japan, and to further the international dissemination of evidence-based training strategies. Parent-training sessions were based on a behavioral skills training (BST) model, combined with weekly graphic and video feedback. The sessions were conducted by a board-certified behavior analyst-doctoral residing in Japan. Four parents with children with autism spectrum disorder participated in this study. The results preliminarily support the effectiveness and social validity of the program. This study extends previous parent-training research conducted in Japan by comprising all of the following features: (1) online program design; (2) mand training; (3) BST model; (4) session-by-session data on children’s behavioral changes and procedural integrity; (5) within-subject experimental design; and (6) social validity evaluation.

Machine Learning-based Time-slot Time-varying Filtering for Mandarin Tone Processing

Tone is one of the biggest differences between Mandarin as a tonal language and English, meaning that changes in frequency will appear in every character and determine their meaning. Therefore, the accurate identification of intonation plays an important role in Chinese language processing and learning. In the learning and training process of Mandarin Chinese, graphical feedback can provide valuable assistance to linguists or learners, providing them with more insight than simple accuracy ratings as they can determined what to change to improve their intonation based on this feedback. In this paper, we refer to the process of generating Mel-frequency cepstrum coefficients and employ a machine learning-aided time-slot filtering approach to obtain an intuitive transformation of pitch from Mel spectrum to geometric graphs as feedback to Chinese language workers and learners, and to help them improve their mastery of Mandarin tones. Our preliminary results show that these illustrations can accurately represent frequency changes in relation to time. At the same time, the lower computational cost of the optimization allows it to be used as learning software on various mobile platforms.

Encoder-Controlled Functional Electrical Stimulator for Bilateral Wrist Activities-Design and Evaluation.

Upper limb impairment following stroke is often characterized by limited voluntary control in the affected arm. In addition, significant motor coordination problems occur on the unaffected arm due to avoidance of performing bilateral symmetrical activities. Rehabilitation strategies should, therefore, not only aim at improving voluntary control on the affected arm, but also contribute to synchronizing activity from both upper limbs. The encoder-controlled functional electrical stimulator, described in this paper, implements precise contralateral control of wrist flexion and extension with electrical stimulation. The stimulator is calibrated for each individual to obtain a table of stimulation parameters versus wrist angle. This table is used to set stimulation parameters dynamically, based on the difference in wrist angle between the set and stimulated side, which is continuously monitored. This allows the wrist on the stimulated side to follow flexion and extension patterns on the set side, thereby mirroring wrist movements of the normal side. This device also gives real-time graphical feedback on how the stimulated wrist is performing in comparison to the normal side. A study was performed on 25 normal volunteers to determine how closely wrist movements on the set side were being followed on the stimulated side. Graphical results show that there were minor differences, which were quantified by considering the peak angles of flexion and extension on the set and stimulated side for each participant. The mean difference in peak flexion and extension range of movement was 2.3 degrees and 1.9 degrees, respectively, with a mean time lag of 1 s between the set and the stimulated angle graphs.

PERSON-CENTREDNESS IN HYPERTENSION MANAGEMENT USING INFORMATION TECHNOLOGY (PERHIT): A RANDOMISED CONTROLLED TRIAL IN PRIMARY HEALTH CARE

Objective: Few studies address results from use of new technology and patient participation in hypertension management. The PERHIT Study is a multicentre randomised controlled trial with the aim to evaluate the effects of a person-centred approach using a web-based, interactive self-management system through the patient´s own mobile phone on blood-pressure and well-being. Primary aim is the degree of achieved blood pressure (BP) control after eight weeks and one year. In addition, person-centeredness, usefulness, daily life activities in relation to BP values, awareness of risk and health care costs are studied. Design and method: The PERHIT study was performed in four regions in southern Sweden. Following inclusion, more than 900 patients from 31 primary health care centres were randomised to two groups. In the intervention group (INT), patients were provided with a web-based self-management support system including a home-BP monitor. For eight consecutive weeks, they measured BP and performed self-reports regarding well-being, symptoms, lifestyle, medication intake and side effects every evening via their mobile phone. They could also receive motivational messages and reminders throughout the intervention period. Both patients and professionals had access to graphic feedback of reported values through a secure web portal. Patients in the control (CON) group received standard treatment as usual. Results: The primary outcome (BP &lt; 140/90 mmHg) was achieved by 48.5% and 47.1% in the INT, and by 40.4% and 40.9% in the CON group after 8 weeks (p = 0.016) and 12 months (p = 0.067), respectively. Both patients and professionals experienced the system as a useful resource for communication regarding BP and lifestyle. They described that it could be used to support a constructive and person-centred partnership between patients and professionals. Conclusions: Blood pressure control was significantly better after eight weeks, but not after one year, following an intervention based on use of mobile phones, feedback and interaction between patients and primary care professionals compared to standard care. The system can be a tool toward a new way of working and help patients reach a controlled BP and play a role in a more person-centred and individually adapted hypertension management.

Development of a maxillofacial virtual surgical system based on biomechanical parameters of facial soft tissue

PurposeLack of biomechanical force model of soft tissue hinders the development of virtual surgical simulation in maxillofacial surgery. In this study, a physical model of facial soft tissue based on real biomechanical parameters was constructed, and a haptics-enabled virtual surgical system was developed to simulate incision-making process on facial soft tissue and to help maxillofacial surgery training.MethodsCT data of a 25-year-old female patient were imported into Mimics software to reconstruct 3D models of maxillofacial soft and skeletal tissues. 3dMD stereo-photo of the patient was fused on facial surface to include texture information. Insertion and cutting parameters of facial soft tissue measured on fresh cadavers were integrated, and a maxillofacial biomechanical force model was established. Rapid deformation and force feedback were realized through localized deformation algorithm and axis aligned bounding box (AABB)-based collision detection. The virtual model was validated quantitatively and qualitatively.ResultsA patient-specific physical model composed of skeletal and facial soft tissue was constructed and embedded in the virtual surgical system. Insertion and cutting in different regions of facial soft tissue were simulated using omega 6, and real-time feedback force was recorded. The feedback force was consistent with acquired force data of experiments conducted on tissue specimen. Real-time graphic and haptic feedback were realized. The mean score of the system performance was 3.71 given by surgeons in evaluation questionnaires.ConclusionThe maxillofacial physical model enabled operators to simulate insertion and cutting on facial soft tissue with realization of realistic deformation and haptic feedback. The combination of localized deformation algorithm and AABB-based collision detection improved computational efficiency. The proposed virtual surgical system demonstrated excellent performance in simulation and training of incision-making process.

IMPROVING HUMAN AWARENESS DURING COLLABORATION WITH ROBOT: REVIEW

Human-robot collaboration is a widespread topic within the concept of Industry 4.0. Such collaboration brings new opportunities to improve ergonomics and innovative options for manufacturing automation; however, most of the modern collaborative industrial applications are limited by the fact that neither collaborative side is fully aware of the partner: the human operator may not see the robot movement due to own engagement in the work process, and the collaborative robot simply has no means of knowing the position of the operator. Dynamic replanning of the robot trajectory with respect to the operator's current position can increase the efficiency and safety of cooperation since the robot will be able to avoid collisions and proceed in task completion; however, the other side of communication remains unresolved. This paper provides a review of methods of improving human awareness during collaboration with a robot. Covered techniques include graphical, acoustic and haptic feedback implementations. The work is focused on the practical applicability of the approaches, and analyses present challenges associated with each method.

Early design phase energy predictions using a semi-dynamic approach as an accurate proxy for dynamic energy simulations

The building sector is well known as one of the significant contributors to climate change. The use of materials and energy are important drivers, both during construction and the whole life cycle. This study is part of a research to improve the Belgian national approach of life cycle environmental assessment for buildings. The current approach focusses mainly on material use, and the operational energy is estimated via the equivalent degree day method assuming a fixed value of 1200 equivalent heating degree days per year. This paper extends this widespread degree day approach to improve its accuracy by including the effect of various parameters (climate, building characteristics, obstructions by the environment, occupant behaviour). Step by step user-friendly input and graphical feedback is moreover considered necessary for designers and has been added. The annual heating energy estimated by our proposed semi-dynamic model has been validated by dynamic energy simulations using EnergyPlus of 8000 randomly generated cases. Both results have been plotted in a 2D graph. The slope of the linear regression through the origin is 0.8955, and the R-square value is 0.9058. Based on this comparison, it is concluded that the semi-dynamic model, with simplified input and fast results, has sufficient accuracy for the first design phases compared to the dynamic model.

Using spatial contiguity and signaling to optimize visual feedback on students’ written explanations.

Writing cohesive texts is a crucial but challenging skill to master. Recently, cognitive tools that provide students with a graphical representation of their texts in the form of concept-maps have been shown to support students’ writing. Despite its beneficial effects, the addition of a graphical representation may have the disadvantage that students have to process multiple isolated representations (i.e., text, graphic), which may increase cognitive load. By applying principles of multimedia learning, in two experiments, we investigated whether interrepresentational signaling and spatial contiguity would have differential effects on students’ subsequent writing performance and on the processing of the graphical feedback. In Experiment 1, students wrote an expository text and either received conventional concept-map feedback, correspondence-enhanced concept-map feedback with interrepresentational signaling, spatially contiguous feedback, or no feedback during text revision. Regarding local cohesion, we found that students profited most when they received spatially contiguous feedback. Contrarily, correspondence-enhanced concept-map feedback was most effective for improving global cohesion. In Experiment 2, we examined the attentional processes while using correspondence-enhanced concept-map feedback versus conventional concept-map feedback by means of eye-tracking. Students receiving correspondence-enhanced concept-map feedback had longer fixation times on the concept-maps, more transitions between their text and the concept-map and were more efficient in improving their text for global cohesion than students receiving concept-maps without signaling. The findings suggest that interrepresentational signaling and spatial contiguity differentially contributed to students’ writing. Therefore, choosing the adequate format of instructional support plays a critical role in scaffolding students’ writing. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Promoting HIV indicator condition-guided testing in hospital settings (PROTEST 2.0): study protocol for a multicentre interventional study

BackgroundLate presentation remains a key barrier towards controlling the HIV epidemic. Indicator conditions (ICs) are those that are AIDS-defining, associated with a prevalence of undiagnosed HIV > 0.1%, or whose clinical management would be impeded if an HIV infection were undiagnosed. IC-guided HIV testing is an effective strategy in identifying undiagnosed HIV, but opportunities for earlier HIV diagnosis through IC-guided testing are being missed. We present a protocol for an interventional study to improve awareness of IC-guided testing and increase HIV testing in patients presenting with ICs in a hospital setting.MethodsWe designed a multicentre interventional study to be implemented at five hospitals in the region of Amsterdam, the Netherlands. Seven ICs were selected for which HIV test ratios (proportion of patients with an IC tested for HIV) will be measured: tuberculosis, cervical/vulvar cancer or high-grade cervical/vulvar dysplasia, malignant lymphoma, hepatitis B and C, and peripheral neuropathy. Prior to the intervention, a baseline assessment of HIV test ratios across ICs will be performed in eligible patients (IC diagnosed January 2015 through May 2020, ≥18 years, not known HIV positive) and an assessment of barriers and facilitators for HIV testing amongst relevant specialties will be conducted using qualitative (interviews) and quantitative methods (questionnaires). The intervention phase will consist of an educational intervention, including presentation of baseline results as competitive graphical audit and feedback combined with discussion on implementation and opportunities for improvement. The effect of the intervention will be assessed by comparing HIV test ratios of the pre-intervention and post-intervention periods. The primary endpoint is the HIV test ratio within ±3 months of IC diagnosis. Secondary endpoints are the HIV test ratio within ±6 months of diagnosis, ratio ever tested for HIV, HIV positivity percentage, proportion of late presenters and proportion with known HIV status prior to initiating treatment for their IC.DiscussionThis protocol presents a strategy aimed at increasing awareness of the benefits of IC-guided testing and increasing HIV testing in patients presenting with ICs in hospital settings to identify undiagnosed HIV in Amsterdam, the Netherlands.Trial registrationDutch trial registry: NL7521. Registered 14 February 2019.

The daily Self-Weighing for Obesity Management in Primary Care Study: Rationale, design and methodology

BackgroundDaily self-weighing (DSW) may be an effective harm-reduction intervention to disrupt continued weight gain. Self-Weighing for Obesity Management in Primary Care (SWOP) is a 24-month randomized controlled trial in 400 adults with obesity (BMI: kg/m2 ≥ 30) receiving primary care through a clinical network affiliated with an academic medical center.ObjectiveTo test DSW as a potentially scalable way to deter age-related weight gain among primary care patients with obesity.MethodsRandomized-controlled trial with two conditions: DSW (instruction to weigh daily and provision of a web-enabled digital scale with graphical weight feedback) or Standard Care (receive a monetary gift card equivalent to value of the scale). Both groups receive standardized weight management educational material. SWOP will test the causal effect of assignment to DSW (Aim 1) and adherence to DSW (Aim 2) on weight (primary outcome) and adoption of weight management practices (secondary outcomes), as well as evaluate the cost-effectiveness of DSW compared to standard care (Aim 3). Findings may inform clinical guidelines for weight management by providing evidence that DSW attenuates continued age-related weight gain among adults with obesity. This trial is registered with ClinicalTrials.gov (NCT04044794).