Post-Takeover Proficiency in Conditionally Automated Driving: Understanding Stabilization Time with Driving and Physiological Signals.

In the realm of conditionally automated driving, understanding the crucial transition phase after a takeover is paramount. This study delves into the concept of post-takeover stabilization by analyzing data recorded in two driving simulator experiments. By analyzing both driving and physiological signals, we investigate the time required for the driver to regain full control and adapt to the dynamic driving task following automation. Our findings show that the stabilization time varies between measured parameters. While the drivers achieved driving-related stabilization (winding, speed) in eight to ten seconds, physiological parameters (heart rate, phasic skin conductance) exhibited a prolonged response. By elucidating the temporal and cognitive dynamics underlying the stabilization process, our results pave the way for the development of more effective and user-friendly automated driving systems, ultimately enhancing safety and driving experience on the roads.

Healthcare system engagement and algorithm-identified cancer incidence following initiation of a new medication.

PURPOSE: Implausibly high algorithm-identified cancer incidence within a new user study after medication initiation may result from increased healthcare utilization (HU) around initiation ("catch-up care") that increases diagnostic opportunity. Understanding the relationships between HU prior to and around initiation and subsequent cancer rates and timing is important to avoiding protopathic bias. METHODS: We identified a cohort of 417 458 Medicare beneficiaries (2007-2014) aged ≥66 initiating an antihypertensive (AHT) after ≥180 days of non-use. Initiators were stratified into groups of 0, 1, 2-3, and ≥4 outpatient visits (OV) 60-360 days before initiation. We calculated algorithm-identified colorectal cancer (aiCRC) rates stratified by OVs and time since AHT initiation: (0-90, 91-180, 181-365, 366-730, and 731+ days). We summarized HU -360/+60 days around AHT initiation by aiCRC timing: (0-29, 30-89, 90-179, and ≥180 days). RESULTS: AiCRC incidence (311 per 100 000 overall) peaked in the first 0-90 days, was inversely associated with HU before initiation, and stabilized ≥180 days after AHT initiation. Catch-up care was greatest among persons with aiCRCs identified <30 days in follow-up. Catch-up care magnitude decreased as time to the aiCRC date increased, with aiCRCs identified ≥180 days after AHT initiation exhibiting similar HU compared with the full cohort. CONCLUSION: Lower HU before-and increased HU around AHT initiation-seem to drive excess short-term aiCRC incidence. Person-time and case accrual should only begin when incidence stabilizes. When comparison groups within a study differ by HU, outcome-detection bias may exist. Similar observations may exist in other settings when typical HU is delayed (e.g., cancer screening during SARS-CoV-2).

Dialogue Management and Language Generation for a Robust Conversational Virtual Coach: Validation and User Study.

Designing human-machine interactive systems requires cooperation between different disciplines is required. In this work, we present a Dialogue Manager and a Language Generator that are the core modules of a Voice-based Spoken Dialogue System (SDS) capable of carrying out challenging, long and complex coaching conversations. We also develop an efficient integration procedure of the whole system that will act as an intelligent and robust Virtual Coach. The coaching task significantly differs from the classical applications of SDSs, resulting in a much higher degree of complexity and difficulty. The Virtual Coach has been successfully tested and validated in a user study with independent elderly, in three different countries with three different languages and cultures: Spain, France and Norway.

A privacy calculus model for contact tracing apps: Analyzing the use behavior of the German Corona-Warn-App with a longitudinal user study.

The SARS-CoV-2 pandemic is a pressing societal issue today. The German government promotes a contract tracing app named Corona-Warn-App (CWA), aiming to change citizens' health behaviors during the pandemic by raising awareness about potential infections and enable infection chain tracking. Technical implementations, citizens' perceptions, and public debates around apps differ between countries, e. g., in Germany there has been a huge discussion on potential privacy issues of the app. Thus, we analyze effects of privacy concerns regarding the CWA, perceived CWA benefits, and trust in the German healthcare system to answer why citizens use the CWA. In our initial conference publication at ICT Systems Security and Privacy Protection - 37th IFIP TC 11 International Conference, SEC 2022, we used a sample with 1752 actual users and non-users of the CWA and and support for the privacy calculus theory, i. e., individuals weigh privacy concerns and benefits in their use decision. Thus, citizens privacy perceptions about health technologies (e. g., shaped by public debates) are crucial as they can hinder adoption and negatively affect future fights against pandemics. In this special issue, we adapt our previous work by conducting a second survey 10 months after our initial study with the same pool of participants (830 participants from the first study participated in the second survey). The goal of this longitudinal study is to assess changes in the perceptions of users and non-users over time and to evaluate the influence of the significantly lower hospitalization and death rates on the use behavior which we could observe during the second survey. Our results show that the privacy calculus is relatively stable over time. The only relationship which significantly changes over time is the effect of privacy concerns on the use behavior which significantly decreases over time, i. e., privacy concerns have a lower negative effect one the CWA use indicating that it did not play such an important role in the use decision at a later point in time in the pandemic. We contribute to the literature by introducing one of the rare longitudinal analyses in the literature focusing on the privacy calculus and changes over time in the relevant constructs as well as the relationships between the calculus constructs and target variables (in our case use behavior of a contact tracing app). We can see that the explanatory power of the privacy calculus model is relatively stable over time even if strong externalities might affect individual perceptions related to the model.

Automatic prediction of rejected edits in Stack Overflow.

The content quality of shared knowledge in Stack Overflow (SO) is crucial in supporting software developers with their programming problems. Thus, SO allows its users to suggest edits to improve the quality of a post (i.e., question and answer). However, existing research shows that many suggested edits in SO are rejected due to undesired contents/formats or violating edit guidelines. Such a scenario frustrates or demotivates users who would like to conduct good-quality edits. Therefore, our research focuses on assisting SO users by offering them suggestions on how to improve their editing of posts. First, we manually investigate 764 (382 questions + 382 answers) rejected edits by rollbacks and produce a catalog of 19 rejection reasons. Second, we extract 15 texts and user-based features to capture those rejection reasons. Third, we develop four machine learning models using those features. Our best-performing model can predict rejected edits with 69.1% precision, 71.2% recall, 70.1% F1-score, and 69.8% overall accuracy. Fourth, we introduce an online tool named EditEx that works with the SO edit system. EditEx can assist users while editing posts by suggesting the potential causes of rejections. We recruit 20 participants to assess the effectiveness of EditEx. Half of the participants (i.e., treatment group) use EditEx and another half (i.e., control group) use the SO standard edit system to edit posts. According to our experiment, EditEx can support SO standard edit system to prevent 49% of rejected edits, including the commonly rejected ones. However, it can prevent 12% rejections even in free-form regular edits. The treatment group finds the potential rejection reasons identified by EditEx influential. Furthermore, the median workload suggesting edits using EditEx is half compared to the SO edit system.

Immersive and desktop virtual reality in virtual fashion stores: a comparison between shopping experiences.

With the high growth and prosperity of e-commerce, the retail industry needs to explore new technologies that improve digital shopping experiences. In the current technological scenario, Virtual Reality (VR) emerges as a tool and an opportunity for enhancing shopping activities, especially for the fashion industry. This study explores whether using Immersive Virtual Reality (IVR) technologies enhances the shopping experience in the fashion industry compared to Desktop Virtual Reality (DVR). A within-subject experiment was carried out involving a sample of 60 participants who completed a simulated shopping experience. In the first mode (DVR), a desktop computer setup was used to test the shopping experience using a mouse and keyboard for navigation. The second mode (IVR) exploited a Head-Mounted Display (HMD), and controllers, that allowed navigation while seated on a workstation to avoid sickness. Participants had to find a bag in the virtual shop and explore its features until they were ready to purchase it. Post-hoc measures of time duration of the shopping experience, hedonic and utilitarian values, user experience, and cognitive load were compared. Results showed that participants experienced higher hedonism and utilitarianism in the IVR shop compared to DVR. The cognitive load was comparable in both modes, while user experience was higher in IVR. In addition, the time duration of the shopping experience was higher in IVR, where users stayed immersed and enjoyed it for longer. This study has implications for fashion industry research, as the use of IVR can potentially lead to novel shopping patterns by enhancing the shopping experience. Supplementary Information: The online version contains supplementary material available at 10.1007/s10055-023-00806-y.

Feasibility and psychophysical effects of immersive virtual reality-based mirror therapy.

BACKGROUND: Virtual reality (VR) has been used as a technological medium to deliver mirror therapy interventions with people after stroke in numerous applications with promising results. The recent emergence of affordable, off-the-shelf head-mounted displays (like the Oculus Rift or HTC Vive) has opened the possibility for novel and cost-effective approaches for immersive mirror therapy interventions. We have developed one such system, ART-VR, which allows people after stroke to carry out a clinically-validated mirror therapy protocol in an immersive virtual environment and within a clinical setting. METHODS: A case cohort of 11 people with upper limb paresis following first time stroke at an in-patient rehabilitation facility received three interventions over a one week period. Participants carried out the BeST mirror therapy protocol using our immersive VR system as an adjunct therapy to their standard rehabilitation program. Our clinical feasibility study investigated intervention outcomes, virtual reality acceptance and user experience. RESULTS: The results show that the combination of an immersive VR system and mirror therapy protocol is feasible for clinical use. 9 out of 11 participants showed some improvement of their affected hand after the intervention. The vast majority of the participants (9/11) reported experiencing some psycho-physical effects, such as tingling or paraesthesia, in the affected limb during the intervention. CONCLUSIONS: Our findings show that immersive VR-based mirror therapy is feasible and shows effects comparable to those of conventional mirror therapy. Trial Registration Trial was registered with the ISRCTN Registry (ISRCTN34011164) on December 3, 2021, retrospectively.

People-Centred Development of a Smart Waste Bin.

The study presented in this article focuses on the role of a smart waste bin (waste container) designed for waste management and explores what types of interventions people consider more appropriate in promoting environmentally responsible behaviour-based on norms or on an individual's emotions. The smart waste bin development process was people-centred and paid particular attention to human experiences, allowing for various interaction modalities. By incorporating various sensors for waste volume and weight measurement in conjunction with presence and user identification capabilities, the experience was personalised. User feedback was collected by an extensive survey, consisting of four systematic sections, where values, attitudes, norms, perceived behavioural control, behavioural intention and actual behaviour were examined. The survey was completed by 194 respondents. The results showed that participants at the declarative level show a high level of environmental awareness and are very much willing to handle waste appropriately. Additionally, the results of the R&D process indicated that relatively cheap and efficient technological solutions can be developed to support waste management and sustainable lifestyles if the human-centred approach is taken into account.

An Augmented Reality Serious Game for Learning Intelligent Wheelchair Control: Comparing Configuration and Tracking Methods.

This work proposes an augmented reality serious game (ARSG) for supporting individuals with motor disabilities while controlling robotic wheelchairs. A racing track was used as the game narrative; this included restriction areas, static and dynamic virtual objects, as well as obstacles and signs. To experience the game, a prior configuration of the environment, made through a smartphone or a computer, was required. Furthermore, a visualization tool was developed to exhibit user performance while using the ARSG. Two user studies were conducted with 10 and 20 participants, respectively, to compare (1) how different devices enable configuring the ARSG, and (2) different tracking capabilities, i.e., methods used to place virtual content on the real-world environment while the user interacts with the game and controls the wheelchair in the physical space: C1-motion tracking using cloud anchors; C2-offline motion tracking. Results suggest that configuring the environment with the computer is more efficient and accurate, in contrast to the smartphone, which is characterized as more engaging. In addition, condition C1 stood out as more accurate and robust, while condition C2 appeared to be easier to use.

Modelling the bioinformatics tertiary analysis research process.

BACKGROUND: With the advancements of Next Generation Techniques, a tremendous amount of genomic information has been made available to be analyzed by means of computational methods. Bioinformatics Tertiary Analysis is a complex multidisciplinary process that represents the final step of the whole bioinformatics analysis pipeline. Despite the popularity of the subject, the Bioinformatics Tertiary Analysis process has not yet been specified in a systematic way. The lack of a reference model results into a plethora of technological tools that are designed mostly on the data and not on the human process involved in Tertiary Analysis, making such systems difficult to use and to integrate. METHODS: To address this problem, we propose a conceptual model that captures the salient characteristics of the research methods and human tasks involved in Bioinformatics Tertiary Analysis. The model is grounded on a user study that involved bioinformatics specialists for the elicitation of a hierarchical task tree representing the Tertiary Analysis process. The outcome was refined and validated using the results of a vast survey of the literature reporting examples of Bioinformatics Tertiary Analysis activities. RESULTS: The final hierarchical task tree was then converted into an ontological representation using an ontology standard formalism. The results of our research provides a reference process model for Tertiary Analysis that can be used both to analyze and to compare existing tools, or to design new tools. CONCLUSIONS: To highlight the potential of our approach and to exemplify its concrete applications, we describe a new bioinformatics tool and how the proposed process model informed its design.

Suitability and Comparison of Questionnaires Assessing Virtual Reality-Induced Symptoms and Effects and User Experience in Virtual Environments.

Although virtual reality (VR) has already achieved technological maturity, there are still some significant drawbacks for technology acceptance and broader user adoption, presenting research challenges. Thus, there is a need for standard, reliable, and quick assessment tools for Virtual Reality-Induced Symptoms and Effects (VRISE) and user experience in VR Assessing VRISE and user experience could be time consuming, especially when using objective physiological measures. In this study, we have reviewed, compared, and performed a suitability assessment of existing standard measures for evaluating VRISE and user experience in VR We have developed a first-person VR game with different scenes and different conditions. For assessing VRISE symptoms, we have used the Simulator Sickness Questionnaire (SSQ) and Fast Motion Sickness Score (FMS). For assessing user experience, we have used the short version of the User Experience Questionnaire (UEQ-S). We have also used a novel Virtual Reality Neuroscience Questionnaire (VRNQ) for assessing VRISE and user experience aspects. The result has shown that FMS and VRNQ (VRISE section) are suitable for quick assessment of VRISE and that VRNQ (User experience section) is suitable for assessing user experience. The advantage of FMS and VRNQ questionnaires is that they are shorter to fulfill and easier to understand. FMS also enables to record the VRISE levels during the virtual experience and thus capturing its trend over time. Another advantage of the VRNQ is that it also provides the minimum and parsimonious cut-offs to appraise the suitability of VR software, which we have confirmed in our study to be adequate.

Using content-based image retrieval of dermoscopic images for interpretation and education: A pilot study.

BACKGROUND: Dermoscopic content-based image retrieval (CBIR) systems provide a set of visually similar dermoscopic (magnified and illuminated) skin images with a pathology-confirmed diagnosis for a given dermoscopic query image of a skin lesion. Although recent advances in machine learning have spurred novel CBIR algorithms, we have few insights into how end users interact with CBIRs and to what extent CBIRs can be useful for education and image interpretation. MATERIALS AND METHODS: We developed an interactive user interface for a CBIR system with dermoscopic images as a decision support tool and investigated users' interactions and decisions with the system. We performed a pilot experiment with 14 non-medically trained users for a given set of annotated dermoscopic images. RESULTS: Our pilot showed that the number of correct classifications and users' confidence levels significantly increased with the CBIR interface compared with a non-CBIR interface, although the timing also increased significantly. The users found the CBIR interface of high educational value, engaging and easy to use. CONCLUSION: Overall, users became more accurate, found the CBIR approach provided a useful decision aid, and had educational value for learning about skin conditions.

The instructor assistant system (iASSYST) - utilizing eye tracking for commercial aviation training purposes.

This work investigates the potential of providing commercial aviation flight instructors with an eye tracking enhanced observation system to support the training process. During training, instructors must deal with many parallel tasks, such as operating the flight simulator, acting as air traffic controllers, observing the pilots and taking notes. This can cause instructors to miss relevant information that is crucial for debriefing the pilots. To support instructors, the instructor ASsistant SYSTem (iASSYST) was developed. It includes video, audio, simulator and eye tracking recordings. iASSYST was evaluated in a study involving 7 instructors. The results show that with iASSYST, instructors were able to support their observations of errors, find new errors, determine that some previously identified errors were not errors, and to reclassify the types of errors that they had originally identified. Instructors agreed that eye tracking can help identifying causes of pilot error. Practitioner summary: This paper introduces an instructor assistant system, which is evaluated in a user study involving 7 airline flight instructors. The system can be used by airline flight instructors to complement their observations, as a basis for discussions with pilots during debriefing, and by airline pilots to improve their flight performance.

Suitability of Inexpensive Eye-Tracking Device for User Experience Evaluations.

We present the results of a study evaluating the suitability of an inexpensive eye-tracking device for the enhancement of user experience evaluations. Ensuring a comfortable user experience is an important part of the mobile application design process. Evaluation of user experience is usually done through questionnaires and interviews, but it can be improved using eye tracking sensors for user experience studies. We conducted a user experience study of DriveGreen, a mobile application devoted to ecodriving for a transition to a low-carbon society. We used an inexpensive eye-tracking device in addition to standard User Experience Questionnaire and Single Ease Question questionnaires. The results show that the inexpensive eye-tracking device data correlate with data from User Experience Questionnaire and Single Ease Question questionnaires and interviews with users. We conclude that an enhancement of user experience evaluations with inexpensive eye-tracking device is possible.

Stealing PINs via mobile sensors: actual risk versus user perception.

In this paper, we present the actual risks of stealing user PINs by using mobile sensors versus the perceived risks by users. First, we propose PINlogger.js which is a JavaScript-based side channel attack revealing user PINs on an Android mobile phone. In this attack, once the user visits a website controlled by an attacker, the JavaScript code embedded in the web page starts listening to the motion and orientation sensor streams without needing any permission from the user. By analysing these streams, it infers the user's PIN using an artificial neural network. Based on a test set of fifty 4-digit PINs, PINlogger.js is able to correctly identify PINs in the first attempt with a success rate of 74% which increases to 86 and 94% in the second and third attempts, respectively. The high success rates of stealing user PINs on mobile devices via JavaScript indicate a serious threat to user security. With the technical understanding of the information leakage caused by mobile phone sensors, we then study users' perception of the risks associated with these sensors. We design user studies to measure the general familiarity with different sensors and their functionality, and to investigate how concerned users are about their PIN being discovered by an app that has access to all these sensors. Our studies show that there is significant disparity between the actual and perceived levels of threat with regard to the compromise of the user PIN. We confirm our results by interviewing our participants using two different approaches, within-subject and between-subject, and compare the results. We discuss how this observation, along with other factors, renders many academic and industry solutions ineffective in preventing such side channel attacks.

On the utility of 3D hand cursors to explore medical volume datasets with a touchless interface.

Analyzing medical volume datasets requires interactive visualization so that users can extract anatomo-physiological information in real-time. Conventional volume rendering systems rely on 2D input devices, such as mice and keyboards, which are known to hamper 3D analysis as users often struggle to obtain the desired orientation that is only achieved after several attempts. In this paper, we address which 3D analysis tools are better performed with 3D hand cursors operating on a touchless interface comparatively to a 2D input devices running on a conventional WIMP interface. The main goals of this paper are to explore the capabilities of (simple) hand gestures to facilitate sterile manipulation of 3D medical data on a touchless interface, without resorting on wearables, and to evaluate the surgical feasibility of the proposed interface next to senior surgeons (N=5) and interns (N=2). To this end, we developed a touchless interface controlled via hand gestures and body postures to rapidly rotate and position medical volume images in three-dimensions, where each hand acts as an interactive 3D cursor. User studies were conducted with laypeople, while informal evaluation sessions were carried with senior surgeons, radiologists and professional biomedical engineers. Results demonstrate its usability as the proposed touchless interface improves spatial awareness and a more fluent interaction with the 3D volume than with traditional 2D input devices, as it requires lesser number of attempts to achieve the desired orientation by avoiding the composition of several cumulative rotations, which is typically necessary in WIMP interfaces. However, tasks requiring precision such as clipping plane visualization and tagging are best performed with mouse-based systems due to noise, incorrect gestures detection and problems in skeleton tracking that need to be addressed before tests in real medical environments might be performed.

A Spot Reminder System for the Visually Impaired Based on a Smartphone Camera.

The present paper proposes a smartphone-camera-based system to assist visually impaired users in recalling their memories related to important locations, called spots, that they visited. The memories are recorded as voice memos, which can be played back when the users return to the spots. Spot-to-spot correspondence is determined by image matching based on the scale invariant feature transform. The main contribution of the proposed system is to allow visually impaired users to associate arbitrary voice memos with arbitrary spots. The users do not need any special devices or systems except smartphones and do not need to remember the spots where the voice memos were recorded. In addition, the proposed system can identify spots in environments that are inaccessible to the global positioning system. The proposed system has been evaluated by two experiments: image matching tests and a user study. The experimental results suggested the effectiveness of the system to help visually impaired individuals, including blind individuals, recall information about regularly-visited spots.

Survey on multisensory feedback virtual reality dental training systems.

Compared with traditional dental training methods, virtual reality training systems integrated with multisensory feedback possess potentials advantages. However, there exist many technical challenges in developing a satisfactory simulator. In this manuscript, we systematically survey several current dental training systems to identify the gaps between the capabilities of these systems and the clinical training requirements. After briefly summarising the components, functions and unique features of each system, we discuss the technical challenges behind these systems including the software, hardware and user evaluation methods. Finally, the clinical requirements of an ideal dental training system are proposed. Future research/development areas are identified based on an analysis of the gaps between current systems and clinical training requirements.

Evaluation of augmented reality training for a navigation device used for CT-guided needle placement.

PURPOSE: Numerous navigation devices for percutaneous, CT-guided interventions exist and are, due to their advantages, increasingly integrated into the clinical workflow. However, effective training methods to ensure safe usage are still lacking. This study compares the potential of an augmented reality (AR) training application with conventional instructions for the Cube Navigation System (CNS), hypothesizing enhanced training with AR, leading to safer clinical usage. METHODS: An AR-tablet app was developed to train users puncturing with CNS. In a study, 34 medical students were divided into two groups: One trained with the AR-app, while the other used conventional instructions. After training, each participant executed 6 punctures on a phantom (204 in total) following a standardized protocol to identify and measure two potential CNS procedural user errors: (1) missing the coordinates specified and (2) altering the needle trajectory during puncture. Training performance based on train time and occurrence of procedural errors, as well as scores of User Experience Questionnaire (UEQ) for both groups, was compared. RESULTS: Training duration was similar between the groups. However, the AR-trained participants showed a 55.1% reduced frequency of the first procedural error (p > 0.05) and a 35.1% reduced extent of the second procedural error (p < 0.01) compared to the conventionally trained participants. UEQ scores favored the AR-training in five of six categories (p < 0.05). CONCLUSION: The AR-app enhanced training performance and user experience over traditional methods. This suggests the potential of AR-training for navigation devices like the CNS, potentially increasing their safety, ultimately improving outcomes in percutaneous needle placements.

Ergonomic RFID tag placement on surgical instruments - a preliminary user study.

OBJECTIVES: RFID tags on surgical instruments allow tracking of individual instruments. However, the tags on the instruments can restrict the handling, potentially increasing patient risks. Previous studies analyzed hand contact areas to identify potential locations for tags. However, the studies did not conduct interaction tests using instruments equipped with RFID tags, potentially neglecting the influence of haptic perception. In addition, previous studies required time-consuming evaluations by clinicians. METHODS: Therefore, the present study aims to verify the previous findings in interaction-centered tests with clinicians using real RFID tags on the instruments. Additionally, we had instrument design experts rate RFID tag positions and examined whether they could predict the clinician's preferred tag positions. RESULTS: We found that nearly all RFID tag positions decreased the user satisfaction of clinicians compared to a reference instrument. Compared to previous studies, our study shows that the RFID tag influences the orientations in which an instrument can be comfortably held, which was criticized by clinicians. Instrument design experts could only predict the clinician's preferred tag positions for some instruments. CONCLUSIONS: Therefore, we recommend investigating further changes to instrument design, for what the "ideal" positions proposed by the clinicians in this study can provide initial pointers.