Real Feedback Research Articles

Management of urban air mobility for sustainable and smart cities: Vertiport networks using a user-centred design

Purpose: Urban mobility is all about people as well as the climate change issue is a human issue. Thus, this research envisions to provide conditions and practical tools through the innovation in urban mobility by bringing urban air mobility (UAM) to cities worldwide, contributing to change lives for the better and reversing the global issue of climate change.Design/methodology/approach: This study goes through two phases: social feasibility and technical feasibility. Moreover, it incorporates a user-centred design based on the systematic engagement of people in the decision-making process alongside a parallel interaction with several stakeholders. An innovative roadmap based on real data and feedback is obtained to implement a vertiport network in Lisbon, Portugal.Findings: By tackling people and stakeholders’ concerns related to vertiport networks implementation (e.g., safety, security, environmental, travel costs, and noise pollution concerns), the people’s needs (e.g., time savings, contribution to less air pollution, enjoyment, and sending and purchasing merchandise) and stakeholders' needs (e.g., adaptation related to airspace and ground integration and capacity, enabling technology, and real-time update and share of data) might be addressed, as by-products. Plus, we could minimize concerns by maximizing opportunities, like optimizing the airspace architecture and enhancing current airspace operations, a chance for businesses to develop on-demand, innovative, and green technologies, and higher employment opportunities. Finally, we have discovered that driving positive global change requires inspiring others by addressing people’s needs and concerns and, by then, calling them to action.Originality/value: UAM’s market reveals a gap in engaging this technology with the people, which is the key enabler to success in the long run. Empathic communication is, therefore, an integral tool to bring urban air mobility to our lives and our world. So, this investigation thrives on humanizing technology to narrow the gap between the science community, public authorities, the industry, and consumers.

A Bias Toward Kindness Goals in Performance Feedback to Women (vs. Men).

While research has documented positivity biases in workplace feedback to women versus men, this phenomenon is not fully understood. We take a motivational perspective, theorizing that the gender stereotype of warmth shapes feedback givers' goals, amplifying the importance placed on kindness when giving critical feedback to a woman versus a man. We found support for this hypothesis in a survey of professionals giving real developmental feedback (Study 1, N = 4,842 raters evaluating N = 423 individuals) and five experiments with MBA students, lab participants, and managers (Studies 2-5, N = 1,589). Across studies, people prioritized the goal of kindness more when they gave, or anticipated giving, critical feedback to a woman versus a man. Studies 1, 3, and 5 suggest that this kindness bias relates to gendered positivity biases, and Studies 4a and 4b tested potential mechanisms and supported an indirect effect through warmth. We discuss implications for the study of motivation and workplace gender bias.

Virtual reality-based and eye tracking-assisted attention refocusing training for adult Attention-Deficit/Hyperactivity Disorder

IntroductionNeurofeedback regimes in the treatment of adult ADHD are commonly EEG-based and have several shortcomings, including a weak signal-to-noise ratio, low transfer rates from laboratory to everyday environments and ambiguous evidence in respect to adequate brain signals of interest.ObjectivesTo investigate, if an eyetracking-based real-time feedback in a virtual environment can enhance attentional performance, as measured by behavioral, EEG and eyetracking parameters.MethodsOverall, n=18 adult patients with ADHD and n=18 healthy controls (HC) performed a continuous performance task (CPT) in a virtual seminar room, while distracting virtual events occurred. In case the participant’s gaze drifted away from the task an automated audiovisual feedback indicated the participant to refocus on the task. Three 20-minutes blocks were presented in counter-balanced order, that differed in respect to whether real feedback, sham feedback or no feedback was additionally provided.ResultsMixed ANOVAs with within-subject factors ‘Condition’ (real feedback, sham feedback, no feedback) and ‘Phase’ (distractor phases vs. non-distractor phases) and a between-factor ‘Group’ (ADHD patients vs. HC) revealed better task performances in HC than ADHD patients in respect to omission errors (p = .023), mean reaction times (p = .042) and reaction time variabilities (p = .007; cf. Figure 1). Moreover, omission errors turned to be higher during distractor-present than distractor-absent trials (p = .007), especially in ADHD.Figure 1.CPT results. DP=distractor-phases, NDP=non-distractor-phasesConclusionsWhile the virtual CPT turns out to discriminate well between patients with ADHD and HC, the behavioral results do not indicate an attentional performance enhancement based on the gaze-dependent feedback.DisclosureNo significant relationships.

P75: The Next Generation of Cardiac BioSimulators: Model-Based Venticular Behaviour with Pressure Feedback Control

Study: Physical cardiac simulators are widely used in surgical training as well as in preclinical device testing. Their fidelity rapidly advances, but often lacks patient-specific cardiac responses. On the other hand, computational simulations of the complete cardiovascular system are being investigated for years but rarely come together in a physical lab model. This study will show our progress in implementing real-time responsive models in a physical cardiac biosimulator. Methods: In this work we implemented a ventricular contraction model combined with a baroreflex response in LifeTec Group’s Cardiac BioSimulator. This BioSimulator generates flow through hearts obtained from abattoirs using a piston pump. We programmed the pump to mimic the heart’s contraction, and to respond to real-time pre- and afterload changes. The contraction model describes the ventricular behavior based on experimental data of myocardial fibers. Next, we will perform experiments with a pump connected to the left ventricle mimicking LVAD functionality and demonstrate ventricular unloading responses. Results: Contraction behavior and baroreflex response were implemented successfully in the pump model, thus representing contractile functionality. Preliminary tests on a simple benchtop model already showed real-time response in PV-loops by adjusting afterload resistance. Recently we added baroreflex functionality that describes heart rate response. Next results will focus on LVAD support simulations on the Cardiac Biosimulator. Conclusion: By combining a state-of-the-art cardiac simulator with a model that describes physiological contraction behavior of the heart, we are one step closer to a realistic simulator that comprises both anatomy and real tissue feedback as well as the correct physiological response that could even be used to assess and train the effect of an intervention.

Fully Convolutional Neural Network-Based CSI Limited Feedback for FDD Massive MIMO Systems

Due to the lack of channel reciprocity in frequency division duplexity (FDD) massive multiple-input multiple-output (MIMO) systems, it is impossible to infer the downlink channel state information (CSI) directly from its reciprocal uplink CSI. Hence, the estimated downlink CSI needs to be continuously fed back to the base station (BS) from the user equipment (UE), consuming valuable bandwidth resources. This is exacerbated, in massive MIMO, with the increase of the antennas at the BS. This paper propose a fully convolutional neural network (FullyConv) to compress and decompress the downlink CSI. FullyConv will improve the reconstruction accuracy of downlink CSI and reduce the training parameters and computational resources. Besides, we add a quantization module in the encoder and a dequantization module in the decoder of the FullyConv to simulate a real feedback scenario. Experimental results demonstrate that the proposed FullyConv is better than the baseline on reconstruction performance and reduction of the storage and computational overhead. Furthermore, the FullyConv added quantization and dequantization modules is robust to quantization error in real feedback scenarios.

The Use of Students’ Portfolio within the Assessment Process at University Level during the Covid-19 Pandemic

The formative assessment that is increasingly required in the context of a competency-focused university is supported by various assessment methods and tools. One of these is the student's learning portfolio, an evaluation method that can maximize the potential and individuality of each student. If correctly applied in the university practice, the portfolio is an objective tool for assessing the level of knowledge and skills in the field of the discipline. At the same time, it offers real feedback and the possibility of optimizing the educational activity, both for the student and the teacher. This article presents a quantitative interpretation of students' views on how the portfolio used during a semester, in the context of online teaching, has contributed to the acquisition of knowledge and skills specific to the discipline, personal, and professional skills. Based on the students' responses positive and negative aspects of the teaching, learning, and evaluation specific to the discipline were identified in the current pandemic context, to valorize and optimize them.

Insight into the intrinsic time-varying aerodynamic properties of a truss girder undergoing a flutter with subcritical Hopf bifurcation

In this study, the investigation on the intrinsic time-varying nonlinear aerodynamic properties and actual energy feedback mechanism of limit cycle oscillation (LCO) and subcritical Hopf bifurcation, which is of great importance of the flutter design of bridges, but once rarely be conducted, was comprehensively carried out. The response characteristics of the nonlinear flutter were experimentally investigated. The dynamic mechanism of the subcritical Hopf bifurcation was firstly introduced in terms of the equivalent modal damping ratio as a function of amplitude. Further, a modified nonlinear self-excited force model was proposed to investigate the intrinsic time-varying characteristics of the aerodynamic properties and the real energy feedback mechanism of the subcritical Hopf bifurcation. Based on the model, the characteristics of nonlinear self-excited forces and nonlinear aerodynamic damping coefficients, as well as their contribution to the energy exchange behaviors, were studied. Subsequently, the energy feedback mechanisms of LCO and subcritical Hopf bifurcation were qualitatively discussed in detail considering the hysteresis loop of nonlinear self-excited forces (NSEF), which highlighted the important role of the linear self-excited-moment (including damping and stiffness) in the generation of a subcritical Hopf bifurcation, and the higher-order force components on the generation of stable LCO. Finally, the driving mechanisms of LCO and subcritical Hopf bifurcation were also quantitatively explained via an energy budget analysis, wherein the total work applied by structural and aerodynamic forces was presented as a function of amplitude and time.

Open-source FlexNIRS: A low-cost, wireless and wearable cerebral health tracker

Currently, there is great interest in making neuroimaging widely accessible and thus expanding the sampling population for better understanding and preventing diseases. The use of wearable health devices has skyrocketed in recent years, allowing continuous assessment of physiological parameters in patients and research cohorts. While most health wearables monitor the heart, lungs and skeletal muscles, devices targeting the brain are currently lacking. To promote brain health in the general population, we developed a novel, low-cost wireless cerebral oximeter called FlexNIRS. The device has 4 LEDs and 3 photodiode detectors arranged in a symmetric geometry, which allows for a self-calibrated multi-distance method to recover cerebral hemoglobin oxygenation (SO2) at a rate of 100 Hz. The device is powered by a rechargeable battery and uses Bluetooth Low Energy (BLE) for wireless communication. We developed an Android application for portable data collection and real-time analysis and display. Characterization tests in phantoms and human participants show very low noise (noise-equivalent power <70 fW/√Hz) and robustness of SO2 quantification in vivo. The estimated cost is on the order of $50/unit for 1000 units, and our goal is to share the device with the research community following an open-source model. The low cost, ease-of-use, smart-phone readiness, accurate SO2 quantification, real time data quality feedback, and long battery life make prolonged monitoring feasible in low resource settings, including typically medically underserved communities, and enable new community and telehealth applications.

Global asymptotic stabilization of autonomous bilinear complex systems

We consider bilinear autonomous control systems in the complex space. To solve the problem of stabilization of these systems, we apply the method of Lyapunov functions to complex-valued systems. The Jurdjevic–Quinn approach is used which is based on the Barbashin–Krasovsky–La Salle theorem on global asymptotic stability. We obtain sufficient conditions for global asymptotic stabilization of a bilinear complex system by real state feedback. Finally, examples of using the obtained results are presented.

579 Outcomes of an Independent Burn Advanced Practice Provider Peer Review Process

IntroductionBurn peer review (PR) is an important process for quality assurance and process improvement. Our division consists of five burn surgeons, seven advanced practice providers (APPs) and four night house officer (NHO) APPs. As the APPs are intimately integrated within the burn service - both on the inpatient (IP) and outpatient (OP) settings, a subsequent need to create an independent peer review process for the APPs was identified. We describe our process and evaluate the results after two years of a monthly APP PR meeting.MethodsAll data is entered into a quality management software. Triggers for APP PR include complex discharge, inappropriate OP referral, delay in treatment, OP treatment greater than three weeks without surgical intervention, pressure wound, patient discharge with greater than 30 morphine equivalent dose (MED) of narcotic, readmission or unexpected admission from OP clinic, substance abuse, and self referral. Cases with individual improvement opportunities result in real time direct feedback from the director, lead APP, and peers. These may be escalated to the provider’s ongoing professional performance evaluation (OPPE) or trigger a focused professional performance evaluation (FPPE). Systemic issues identified are referred for multidisciplinary discussion in our Performance Improvement/Quality Assurance (PI/QA) process. Complicated issues involving multiple disciplines may trigger a root cause analysis. If an individual or system issue is not identified, a group discussion about process improvement and standardization of practice ensues.ResultsFrom initiation of the Burn APP PR process in May of 2019, to September 2021, there were 37 cases reviewed. Twelve were for indicated triggers and 25 for self-referrals. Breakdown of these cases is as follows: outpatient treatment greater than three weeks without surgical intervention (3), readmission or unexpected admission from outpatient clinic (4), delay in treatment impacting clinic course (5). Self referred cases included graft loss (8), cellulitis (3), venous thromboembolic event (2), and wound dressing discussion (2). There were three cases where clinical issues were identified of which one was referred for root cause analysis, and the other two led to real-time education and feedback from the director.ConclusionsPR is important to ensure that high quality patient care standards are met. Autonomous APP practice is important for the function of a team, quality of care delivered, professional satisfaction of the APP, and enables financial optimization for burn centers. Creating an independent burn APP peer review process allows for time-sensitive feedback to patient care related events, improves collaboration and practice standardization, and provides an important educational opportunity for the team.

Developing Affordable, Portable and Simplistic Diagnostic Sensors to Improve Access to Care.

Ophthalmology is a highly technical specialty, especially in the area of diagnostic equipment. While the field is innovative, the access to cutting-edge technology is limited with reference to the global population. A significant way to improve overall healthcare is to understand the needs and possibilities of all possible consumers when developing sophisticated and accurate medical devices. The Smartphone-based Keratograph (SBK), is an example of a new project that uses real world feedback, addresses an unmet medical need, and implements commercially available components to create a device that is affordable, portable and simplistic to operate. The long-term goal of the SBK is to collect data from users for supervised machine-learning. This machine-learning aspect will ultimately aid in the development of an artificial intelligence device to enable even earlier detection of keratoconus, especially in children and adolescents. Again, the ultimate goal of any medical device should be to improve patient care, and to make a significant improvement on vision healthcare for the global population, providing access to this technology is essential.

Synergistic Immediate Cortical Activation on Mirror Visual Feedback Combined With a Soft Robotic Bilateral Hand Rehabilitation System: A Functional Near Infrared Spectroscopy Study.

BackgroundMirror visual feedback (MVF) has been widely used in neurological rehabilitation. Due to the potential gain effect of the MVF combination therapy, the related mechanisms still need be further analyzed.MethodsOur self-controlled study recruited 20 healthy subjects (age 22.150 ± 2.661 years) were asked to perform four different visual feedback tasks with simultaneous functional near infrared spectroscopy (fNIRS) monitoring. The right hand of the subjects was set as the active hand (performing active movement), and the left hand was set as the observation hand (static or performing passive movement under soft robotic bilateral hand rehabilitation system). The four VF tasks were designed as RVF Task (real visual feedback task), MVF task (mirror visual feedback task), BRM task (bilateral robotic movement task), and MVF + BRM task (Mirror visual feedback combined with bilateral robotic movement task).ResultsThe beta value of the right pre-motor cortex (PMC) of MVF task was significantly higher than the RVF task (RVF task: -0.015 ± 0.029, MVF task: 0.011 ± 0.033, P = 0.033). The beta value right primary sensorimotor cortex (SM1) in MVF + BRM task was significantly higher than MVF task (MVF task: 0.006 ± 0.040, MVF + BRM task: 0.037 ± 0.036, P = 0.016).ConclusionOur study used the synchronous fNIRS to compare the immediate hemodynamics cortical activation of four visual feedback tasks in healthy subjects. The results showed the synergistic gain effect on cortical activation from MVF combined with a soft robotic bilateral hand rehabilitation system for the first time, which could be used to guide the clinical application and the future studies.

Does Real Age Feedback Really Motivate Us to Change our Lifestyle? Results from an Online Experiment

ABSTRACT We set out to research the causal impact of Real Age feedback, a popular tool on health and lifestyle platforms, on health behaviors. We ran an online experiment where participants were randomly assigned a Real Age that differed in both direction (older or younger) and magnitude (much or slightly) from their passport age, or to a control condition where they received no Real Age feedback. We measured the impact of Real Age feedback on motivation to begin a healthier lifestyle, interest in taking a Real Age test, and percentage click-rate on an optional health link. We found that younger Real Age feedback was associated with higher interest. In addition, participants who received a slightly older Real Age were significantly less motivated to begin a healthier lifestyle compared to not only those who received a much younger or much older Real Age, but also to those in the control condition, suggesting a backfire effect. This effect remained even after accounting for participant health, demographics, and other psychological correlates to motivation. Real Age tests may backfire and demotivate people, and the positive effects they may have on psychological states may not outweigh the negative effects. Though promising, we caution using Real Age tests in their current form as stand-alone interventions to get people motivated.

A modified Q-learning algorithm for robot path planning in a digital twin assembly system

Product assembly is an important stage in complex product manufacturing. How to intelligently plan the assembly process based on dynamic product and environment information has become a pressing issue that needs to be addressed. For this reason, this research has constructed a digital twin assembly system, including virtual and real interactive feedback, data fusion analysis, and decision-making iterative optimization modules. In the virtual space, a modified Q-learning algorithm is proposed to solve the path planning problem in product assembly. The proposed algorithm speeds up the convergence speed by adding a dynamic reward function, optimizes the initial Q table by introducing knowledge and experience through the case-based reasoning algorithm, and prevents entry into the trapped area through the obstacle avoiding method. Finally, the six-joint robot UR10 is taken as an example to verify the performance of the algorithm in the three-dimensional pathfinding space. The experimental results show that the performance of the modified Q-learning algorithm is significantly better than the original Q-learning algorithm in both convergence efficiency and the optimization effect.

Manufacturing Service Network of Digital Twin Systems Under Cloud Computing Environment

With the promotion and application of the digital twin system in the industrial Internet platform, and around the "intelligent, integrated, and service-oriented" manufacturing characteristics, a digital twin system manufacturing service network with full-process, full-object, and full-factor coverage of virtual and real resources has gradually formed. In a typical cloud computing environment, this paper defines the manufacturing service network of the digital twin system based on the virtual and real mapping, simulation calculation, feedback control and other characteristic requirements of the digital twin system, and constructs the network model from the network nodes and network connections. Based on this, the optimization steps for resource allocation of manufacturing service network based on the digital twin system, and the key technologies for the construction of the manufacturing service network of the digital twin system are analyzed.

UVC-PURGE: A Novel Cost-Effective Disinfection Robot for Combating COVID-19 Pandemic.

During the COVID-19 pandemic, surface disinfection using prevailing chemical disinfection methods had several limitations. Due to cost-inefficiency and the inability to disinfect shaded places, static UVC lamps cannot address these limitations properly. Moreover, the average market price of the prevailing UVC robots is huge, approximately 55,165 USD. In this research firstly, a requirement elicitation study was conducted using a semi-structured interview approach to reveal the requirements to develop a cost-effective UVC robot. Secondly, a semi-autonomous robot named UVC-PURGE was developed based on the revealed requirements. Thirdly, a two-phased evaluation study was undertaken to validate the effectiveness of UVC-PURGE to inactivate the SARS-CoV-2 virus and the capability of semi-autonomous navigation in the first phase and to evaluate the usability of the system through a hybrid approach of SUPR-Q forms and subjective evaluation of the user feedback in the second phase. Pre-treatment swab testing revealed the presence of both Gram-positive and Gram-Negative bacteria at 17 out of 20 test surfaces in the conducted tests. After the UVC irradiation of the robot, the microbial load was detected in only 2 (1D and 1H) out of 17 test surfaces with significant reductions (95.33% in 1D and 90.9% in 1H) of microbial load. Moreover, the usability evaluation yields an above-average SUPR-Q score of 81.91% with significant scores in all the criteria (usability, trust, loyalty, and appearance) and the number of positive themes from the subjective evaluation using thematic analysis is twice the number of negative themes. Additionally, compared with the prevailing UVC disinfection robots in the market, UVC-PURGE is cost-effective with a price of less than 800 USD. Moreover, small form factor along with the real time camera feedback in the developed system helps the user to navigate in congested places easily. The developed robot can be used in any indoor environment in this prevailing pandemic situation and it can also provide cost-effective disinfection in medical facilities against the long-term residual effect of COVID-19 in the post-pandemic era.

Reducing postural exposure in real manual sorting work by means of real time vibrotactile feedback training

Reducing postural exposure in real manual sorting work by means of real time vibrotactile feedback training

BPSS Award

BPSS Award

Sentiment analysis of users reviews in Facebook: comparison of TEXTBLOB and DOSTOEVSKY libraries

This article examines the work of two Python libraries TextBlob and Dostoevsky for determining the sentiment of reviews in Russian. The TextBlob library does not directly provide sentiment analysis of texts in Russian, but it has the ability to transfer such texts to the input of the Google Translate translator, in order to then evaluate the polarity of these texts based on the generated English translations. The second Dostoevsky library was created specifically for sentiment analysis of texts in Russian and is trained on the largest Russian-language sentiment corpus RuSentiment, which contains more than 30 thousand manually annotated messages. To compare these libraries, this article uses real feedback from residents of the city of Nur-Sultan about the quality of life in the capital, including about the activities of city services and the housing and communal sector, the work of service facilities, education, health care, culture, etc., posted on public Facebook groups. The results of the sentiment analysis carried out are evaluated using generally accepted metrics of accuracy, completeness and F-measure and demonstrate a slight superiority of the Dostoevsky library.

Biofeedback as an Adjunctive Treatment for Post-stroke Dysphagia: A Pilot-Randomized Controlled Trial.

Post-stroke dysphagia affects almost half of the survivors and severely influences quality of life, thus becoming swallowing rehabilitation of paramount importance. However, there is little adequate evidence on which the best rehabilitative strategy can be. Surface electromyography (sEMG) allows for recording swallowing muscles' activity and provides real time visual feedback, as a biofeedback adjunctive technique to improve treatment outcome. This study aimed to analyze the effectiveness of biofeedback rehabilitation of swallowing through sEMG compared to standard techniques, in post-stroke dysphagia. A pilot-randomized controlled trial included 17 patients diagnosed with post-stroke dysphagia. Nine underwent sEMG-biofeedback rehabilitation; seven controls were submitted to control treatment, one dropout. The primary outcome was the functional oral intake scale (FOIS), secondary outcomes was pharyngeal clearance and safe swallowing, assessed through fiberoptic endoscopic evaluation of swallowing (FEES). FOIS improved in all patients, regardless of treatment. sEMG-biofeedback rehabilitation led to improvements of the pharyngeal clearance and swallowing safety. The rehabilitative effects appeared stable at 2-months follow-up. The application of biofeedback based on sEMG in post-stroke dysphagia patients resulted in an effective rehabilitative technique, in particular for pharyngeal clearance improvements and safe swallowing, thus reducing the risk of aspiration and malnutrition.