Investigating cortical activity during cybersickness by fNIRS.

This study investigated brain responses during cybersickness in healthy adults using functional near-infrared spectroscopy (fNIRS). Thirty participants wore a head-mounted display and observed a virtual roller coaster scene that induced cybersickness. Cortical activation during the virtual roller coaster task was measured using fNIRS. Cybersickness symptoms were evaluated using a Simulator Sickness Questionnaire (SSQ) administered after the virtual rollercoaster. Pearson correlations were performed for cybersickness symptoms and the beta coefficients of hemodynamic responses. The group analysis of oxyhemoglobin (HbO) and total hemoglobin (HbT) levels revealed deactivation in the bilateral angular gyrus during cybersickness. In the Pearson correlation analyses, the HbO and HbT beta coefficients in the bilateral angular gyrus had a significant positive correlation with the total SSQ and disorientation. These results indicated that the angular gyrus was associated with cybersickness. These findings suggest that the hemodynamic response in the angular gyrus could be a biomarker for evaluating cybersickness symptoms.

Preact to lower the risk of falling by customized rehabilitation across Europe: the feasibility study protocol of the PRECISE project in Italy.

Introduction: Falls are a major worldwide health problem in older people. Several physical rehabilitation programs with home-based technologies, such as the online DigiRehab platform, have been successfully delivered. The PRECISE project combines personalized training delivered through the application with an artificial intelligence-based predictive model (AI-DSS platform) for fall risk assessment. This new system, called DigiRehab, will enable early identification of significant risk factors for falling and propose an individualized physical training plan to attend to these critical areas. Methods: The study will test the usability of the DigiRehab platform in generating personalized physical rehabilitation programs at home. Fifty older adults participants will be involved, 20 of them testing the beta version prototype, and 30 participants testing the updated version afterwards. The inclusion criteria will be age ≥65, independent ambulation, fall risk (Tinetti test), Mini Mental State Examination ≥24, home residents, familiarity with web applications, ability and willingness to sign informed consent. Exclusion criteria will be unstable clinical condition, severe visual and/or hearing impairment, severe impairment in Activities of Daily Living and absence of primary caregiver. Discussion: The first part of the screening consists in a structured questionnaire of 10 questions regarding the user's limitations, including the risk of falling, while the second consists in 10 physical tests to assess the functional status. Based on the results, the program will help define the user's individual profile upon which the DSS platform will rate the risk of falling and design the personalized exercise program to be carried out at home. All measures from the initial screening will be repeated and the results will be used to optimize the predictive algorithms in order to prepare the tool in its final version. For the usability assessment, the System Usability Scale will be administered. The follow-up will take place after the 12-week intervention at home. A semi-structured satisfaction questionnaire will also be administered to verify whether the project will meet the needs of older adults and their family caregiver. Conclusion: We expect that personalized training prescribed by DigiRehab platform could help to reduce the need for care in older adults subjects and the care burden.Clinical trial registration: [https://clinicaltrials.gov/], identifier [NCT05846776].

MaRGE: A graphical environment for MaRCoS.

The open-source console MaRCoS, which stands for "Magnetic Resonance Control System", combines hardware, firmware and software elements for integral control of Magnetic Resonance Imaging (MRI) scanners. Previous developments have focused on making the system robust and reliable, rather than on users, who have been somewhat overlooked. This work describes a Graphical User Interface (GUI) designed for intuitive control of MaRCoS, as well as compatibility with clinical environments. The GUI is based on an arrangement of tabs and a renewed Application Program Interface (API). Compared to the previous versions, the MaRGE package ("MaRCoS Graphical Environment") includes new functionalities such as the possibility to export images to standard DICOM formats, create and manage clinical protocols, or display and process image reconstructions, among other features conceived to simplify the operation of MRI scanners. All prototypes in our facilities are commanded by MaRCoS and operated with the new GUI. Here we report on its performance on an experimental 0.2 T scanner designed for hard-tissue, as well as a 72 mT portable scanner presently installed in the radiology department of a large hospital. The possibility to customize, adapt and streamline processes has substantially improved our workflows and overall experience.

PTVR - A software in Python to make virtual reality experiments easier to build and more reproducible.

Researchers increasingly use virtual reality (VR) to perform behavioral experiments, especially in vision science. These experiments are usually programmed directly in so-called game engines that are extremely powerful. However, this process is tricky and time-consuming as it requires solid knowledge of game engines. Consequently, the anticipated prohibitive effort discourages many researchers who want to engage in VR. This paper introduces the Perception Toolbox for Virtual Reality (PTVR) library, allowing visual perception studies in VR to be created using high-level Python script programming. A crucial consequence of using a script is that an experiment can be described by a single, easy-to-read piece of code, thus improving VR studies' transparency, reproducibility, and reusability. We built our library upon a seminal open-source library released in 2018 that we have considerably developed since then. This paper aims to provide a comprehensive overview of the PTVR software for the first time. We introduce the main objects and features of PTVR and some general concepts related to the three-dimensional (3D) world. This new library should dramatically reduce the difficulty of programming experiments in VR and elicit a whole new set of visual perception studies with high ecological validity.

Patient and Caregiver Perceptions of an Interface Design to Communicate Artificial Intelligence-Based Prognosis for Patients With Advanced Solid Tumors.

PURPOSE: Use of artificial intelligence (AI) in cancer care is increasing. What remains unclear is how best to design patient-facing systems that communicate AI output. With oncologist input, we designed an interface that presents patient-specific, machine learning-based 6-month survival prognosis information designed to aid oncology providers in preparing for and discussing prognosis with patients with advanced solid tumors and their caregivers. The primary purpose of this study was to assess patient and caregiver perceptions and identify enhancements of the interface for communicating 6-month survival and other prognosis information when making treatment decisions concerning anticancer and supportive therapy. METHODS: This qualitative study included interviews and focus groups conducted between November and December 2022. Purposive sampling was used to recruit former patients with cancer and/or former caregivers of patients with cancer who had participated in cancer treatment decisions from Utah or elsewhere in the United States. Categories and themes related to perceptions of the interface were identified. RESULTS: We received feedback from 20 participants during eight individual interviews and two focus groups, including four cancer survivors, 13 caregivers, and three representing both. Overall, most participants expressed positive perceptions about the tool and identified its value for supporting decision making, feeling less alone, and supporting communication among oncologists, patients, and their caregivers. Participants identified areas for improvement and implementation considerations, particularly that oncologists should share the tool and guide discussions about prognosis with patients who want to receive the information. CONCLUSION: This study revealed important patient and caregiver perceptions of and enhancements for the proposed interface. Originally designed with input from oncology providers, patient and caregiver participants identified additional interface design recommendations and implementation considerations to support communication about prognosis.

OmicNavigator: open-source software for the exploration, visualization, and archival of omic studies.

BACKGROUND: The results of high-throughput biology ('omic') experiments provide insight into biological mechanisms but can be challenging to explore, archive and share. The scale of these challenges continues to grow as omic research volume expands and multiple analytical technologies, bioinformatic pipelines, and visualization preferences have emerged. Multiple software applications exist that support omic study exploration and/or archival. However, an opportunity remains for open-source software that can archive and present the results of omic analyses with broad accommodation of study-specific analytical approaches and visualizations with useful exploration features. RESULTS: We present OmicNavigator, an R package for the archival, visualization and interactive exploration of omic studies. OmicNavigator enables bioinformaticians to create web applications that interactively display their custom visualizations and analysis results linked with app-derived analytical tools, graphics, and tables. Studies created with OmicNavigator can be viewed within an interactive R session or hosted on a server for shared access. CONCLUSIONS: OmicNavigator can be found at https://github.com/abbvie-external/OmicNavigator.

Shaoxia: a web-based interactive analysis platform for single cell RNA sequencing data.

BACKGROUND: In recent years, Single-cell RNA sequencing (scRNA-seq) is increasingly accessible to researchers of many fields. However, interpreting its data demands proficiency in multiple programming languages and bioinformatic skills, which limited researchers, without such expertise, exploring information from scRNA-seq data. Therefore, there is a tremendous need to develop easy-to-use software, covering all the aspects of scRNA-seq data analysis. RESULTS: We proposed a clear analysis framework for scRNA-seq data, which emphasized the fundamental and crucial roles of cell identity annotation, abstracting the analysis process into three stages: upstream analysis, cell annotation and downstream analysis. The framework can equip researchers with a comprehensive understanding of the analysis procedure and facilitate effective data interpretation. Leveraging the developed framework, we engineered Shaoxia, an analysis platform designed to democratize scRNA-seq analysis by accelerating processing through high-performance computing capabilities and offering a user-friendly interface accessible even to wet-lab researchers without programming expertise. CONCLUSION: Shaoxia stands as a powerful and user-friendly open-source software for automated scRNA-seq analysis, offering comprehensive functionality for streamlined functional genomics studies. Shaoxia is freely accessible at http://www.shaoxia.cloud , and its source code is publicly available at https://github.com/WiedenWei/shaoxia .

Evaluating the Usability of an mHealth App for Empowering Cancer Survivors With Disabilities: Heuristic Evaluation and Usability Testing.

BACKGROUND: More than 18 million cancer survivors are living in the United States. The effects of cancer and its treatments can have cognitive, psychological, physical, and social consequences that many survivors find incredibly disabling. Posttreatment support is often unavailable or underused, especially for survivors living with disabilities. This leaves them to deal with new obstacles and struggles on their own, oftentimes feeling lost during this transition. Mobile health (mHealth) interventions have been shown to effectively aid cancer survivors in dealing with many of the aftereffects of cancer and its treatments; these interventions hold immense potential for survivors living with disabilities. We developed a prototype for WeCanManage, an mHealth-delivered self-management intervention to empower cancer survivors living with disabilities through problem-solving, mindfulness, and self-advocacy training. OBJECTIVE: Our study conducted a heuristic evaluation of the WeCanManage high-fidelity prototype and assessed its usability among cancer survivors with known disabilities. METHODS: We evaluated the prototype using Nielsen's 10 principles of heuristic evaluation with 22 human-computer interaction university students. On the basis of the heuristic evaluation findings, we modified the prototype and conducted usability testing on 10 cancer survivors with a variety of known disabilities, examining effectiveness, efficiency, usability, and satisfaction, including a completion of the modified System Usability Scale (SUS). RESULTS: The findings from the heuristic evaluation were mostly favorable, highlighting the need for a help guide, addressing accessibility concerns, and enhancing the navigation experience. After usability testing, the average SUS score was 81, indicating a good-excellent design. The participants in the usability testing sample expressed positive reactions toward the app's design, educational content and videos, and the available means of connecting with others. They identified areas for improvement, such as improving accessibility, simplifying navigation within the community forums, and providing a more convenient method to access the help guide. CONCLUSIONS: Overall, usability testing showed positive results for the design of WeCanManage. The course content and features helped participants feel heard, understood, and less alone.

Evaluation of power wheelchair driving performance in simulator compared to driving in real-life situations: the SIMADAPT (simulator ADAPT) project-a pilot study.

OBJECTIVE: The objective of this study was to evaluate users' driving performances with a Power Wheelchair (PWC) driving simulator in comparison to the same driving task in real conditions with a standard power wheelchair. METHODS: Three driving circuits of progressive difficulty levels (C1, C2, C3) that were elaborated to assess the driving performances with PWC in indoor situations, were used in this study. These circuits have been modeled in a 3D Virtual Environment to replicate the three driving task scenarios in Virtual Reality (VR). Users were asked to complete the three circuits with respect to two testing conditions during three successive sessions, i.e. in VR and on a real circuit (R). During each session, users completed the two conditions. Driving performances were evaluated using the number of collisions and time to complete the circuit. In addition, driving ability by Wheelchair Skill Test (WST) and mental load were assessed in both conditions. Cybersickness, user satisfaction and sense of presence were measured in VR. The conditions R and VR were randomized. RESULTS: Thirty-one participants with neurological disorders and expert wheelchair drivers were included in the study. The driving performances between VR and R conditions were statistically different for the C3 circuit but were not statistically different for the two easiest circuits C1 and C2. The results of the WST was not statistically different in C1, C2 and C3. The mental load was higher in VR than in R condition. The general sense of presence was reported as acceptable (mean value of 4.6 out of 6) for all the participants, and the cybersickness was reported as acceptable (SSQ mean value of 4.25 on the three circuits in VR condition). CONCLUSION: Driving performances were statistically different in the most complicated circuit C3 with an increased number of collisions in VR, but were not statistically different for the two easiest circuits C1 and C2 in R and VR conditions. In addition, there were no significant adverse effects such as cybersickness. The results show the value of the simulator for driving training applications. Still, the mental load was higher in VR than in R condition, thus mitigating the potential for use with people with cognitive disorders. Further studies should be conducted to assess the quality of skill transfer for novice drivers from the simulator to the real world. Trial registration Ethical approval n ∘ 2019-A001306-51 from Comité de Protection des Personnes Sud Mediterranée IV. Trial registered the 19/11/2019 on ClinicalTrials.gov in ID: NCT04171973.

Exploring Gaze Dynamics in Virtual Reality through Multiscale Entropy Analysis.

This study employs Multiscale Entropy (MSE) to analyze 5020 binocular eye movement recordings from 407 college-aged participants, as part of the GazeBaseVR dataset, across various virtual reality (VR) tasks to understand the complexity of user interactions. By evaluating the vertical and horizontal components of eye movements across tasks such as vergence, smooth pursuit, video viewing, reading, and random saccade, collected at 250 Hz using an ET-enabled VR headset, this research provides insights into the predictability and complexity of gaze patterns. Participants were recorded up to six times over a 26-month period, offering a longitudinal perspective on eye movement behavior in VR. MSE's application in this context aims to offer a deeper understanding of user behavior in VR, highlighting potential avenues for interface optimization and user experience enhancement. The results suggest that MSE can be a valuable tool in creating more intuitive and immersive VR environments by adapting to users' gaze behaviors. This paper discusses the implications of these findings for the future of VR technology development, emphasizing the need for intuitive design and the potential for MSE to contribute to more personalized and comfortable VR experiences.

Evaluating Technicians' Workload and Performance in Diagnosis for Corrective Maintenance.

The advancement in digital technology is transforming the world. It enables smart product-service systems that improve productivity by changing tasks, processes, and the ways we work. There are great opportunities in maintenance because many tasks require physical and cognitive work, but are still carried out manually. However, the interaction between a human and a smart system is inevitable, since not all tasks in maintenance can be fully automated. Therefore, we conducted a controlled laboratory experiment to investigate the impact on technicians' workload and performance due to the introduction of smart technology. Especially, we focused on the effects of different diagnosis support systems on technicians during maintenance activity. We experimented with a model that replicates the key components of a computer numerical control (CNC) machine with a proximity sensor, a component that requires frequent maintenance. Forty-five participants were evenly assigned to three groups: a group that used a Fault-Tree diagnosis support system (FTd-system), a group that used an artificial intelligence diagnosis support system (AId-system), and a group that used neither of the diagnosis support systems. The results show that the group that used the FTd-system completed the task 15% faster than the group that used the AId-system. There was no significant difference in the workload between groups. Further analysis using the NGOMSL model implied that the difference in time to complete was probably due to the difference in system interfaces. In summary, the experimental results and further analysis imply that adopting the new diagnosis support system may improve maintenance productivity by reducing the number of diagnosis attempts without burdening technicians with new workloads. Estimates indicate that the maintenance time and the cognitive load can be reduced by 8.4 s and 15% if only two options are shown in the user interface.

A qualitative analysis of algorithm-based decision support usability testing for symptom management across the trajectory of cancer care: one size does not fit all.

BACKGROUND: Adults with cancer experience symptoms that change across the disease trajectory. Due to the distress and cost associated with uncontrolled symptoms, improving symptom management is an important component of quality cancer care. Clinical decision support (CDS) is a promising strategy to integrate clinical practice guideline (CPG)-based symptom management recommendations at the point of care. METHODS: The objectives of this project were to develop and evaluate the usability of two symptom management algorithms (constipation and fatigue) across the trajectory of cancer care in patients with active disease treated in comprehensive or community cancer care settings to surveillance of cancer survivors in primary care practices. A modified ADAPTE process was used to develop algorithms based on national CPGs. Usability testing involved semi-structured interviews with clinicians from varied care settings, including comprehensive and community cancer centers, and primary care. The transcripts were analyzed with MAXQDA using Braun and Clarke's thematic analysis method. A cross tabs analysis was also performed to assess the prevalence of themes and subthemes by cancer care setting. RESULTS: A total of 17 clinicians (physicians, nurse practitioners, and physician assistants) were interviewed for usability testing. Three main themes emerged: (1) Algorithms as useful, (2) Symptom management differences, and (3) Different target end-users. The cross-tabs analysis demonstrated differences among care trajectories and settings that originated in the Symptom management differences theme. The sub-themes of "Differences between diseases" and "Differences between care trajectories" originated from participants working in a comprehensive cancer center, which tends to be disease-specific locations for patients on active treatment. Meanwhile, participants from primary care identified the sub-theme of "Differences in settings," indicating that symptom management strategies are care setting specific. CONCLUSIONS: While CDS can help promote evidence-based symptom management, systems providing care recommendations need to be specifically developed to fit patient characteristics and clinical context. Findings suggest that one set of algorithms will not be applicable throughout the entire cancer trajectory. Unique CDS for symptom management will be needed for patients who are cancer survivors being followed in primary care settings.

From voice to ink (Vink): development and assessment of an automated, free-of-charge transcription tool.

BACKGROUND: Verbatim transcription of qualitative audio data is a cornerstone of analytic quality and rigor, yet the time and energy required for such transcription can drain resources, delay analysis, and hinder the timely dissemination of qualitative insights. In recent years, software programs have presented a promising mechanism to accelerate transcription, but the broad application of such programs has been constrained due to expensive licensing or "per-minute" fees, data protection concerns, and limited availability of such programs in many languages. In this article, we outline our process of adapting a free, open-source, speech-to-text algorithm (Whisper by OpenAI) into a usable and accessible tool for qualitative transcription. Our program, which we have dubbed "Vink" for voice to ink, is available under a permissive open-source license (and thus free of cost). RESULTS: We conducted a proof-of-principle assessment of Vink's performance in transcribing authentic interview audio data in 14 languages. A majority of pilot-testers evaluated the software performance positively and indicated that they were likely to use the tool in their future research. Our usability assessment indicates that Vink is easy-to-use, and we performed further refinements based on pilot-tester feedback to increase user-friendliness. CONCLUSION: With Vink, we hope to contribute to facilitating rigorous qualitative research processes globally by reducing time and costs associated with transcription and by expanding free-of-cost transcription software availability to more languages. With Vink running on standalone computers, data privacy issues arising within many other solutions do not apply.

DiGAlign: Versatile and Interactive Visualization of Sequence Alignment for Comparative Genomics.

With the explosion of available genomic information, comparative genomics has become a central approach to understanding microbial ecology and evolution. We developed DiGAlign (https://www.genome.jp/digalign/), a web server that provides versatile functionality for comparative genomics with an intuitive interface. It allows the user to perform the highly customizable visualization of a synteny map by simply uploading nucleotide sequences of interest, ranging from a specific region to the whole genome landscape of microorganisms and viruses. DiGAlign will serve a wide range of biological researchers, particularly experimental biologists, with multifaceted features that allow the rapid characterization of genomic sequences of interest and the generation of a publication-ready figure.

Design and development of a personalized virtual reality-based training system for vascular intervention surgery.

BACKGROUND AND OBJECTIVES: Virtual training has emerged as an exceptionally effective approach for training healthcare practitioners in the field of vascular intervention surgery. By providing a simulated environment and blood vessel model that enables repeated practice, virtual training facilitates the acquisition of surgical skills in a safe and efficient manner for trainees. However, the current state of research in this area is characterized by limitations in the fidelity of blood vessel and guidewire models, which restricts the effectiveness of training. Additionally, existing approaches lack the necessary real-time responsiveness and precision, while the blood vessel models suffer from incompleteness and a lack of scientific rigor. METHODS: To address these challenges, this paper integrates position-based dynamics (PBD) and its extensions, shape matching, and Cosserat elastic rods. By combining these approaches within a unified particle framework, accurate and realistic deformation simulation of personalized blood vessel and guidewire models is achieved, thereby enhancing the training experience. Furthermore, a multi-level progressive continuous collision detection method, leveraging spatial hashing, is proposed to improve the accuracy and efficiency of collision detection. RESULTS: Our proposed blood vessel model demonstrated acceptable performance with the reduced deformation simulation response times of 7 ms, improving the real-time capability at least of 43.75 %. Experimental validation confirmed that the guidewire model proposed in this paper can dynamically adjust the density of its elastic rods to alter the degree of bending and torsion. It also exhibited a deformation process comparable to that of real guidewires, with an average response time of 6 ms. In the interaction of blood vessel and guidewire models, the simulator blood vessel model used for coronary vascular intervention training exhibited an average response time of 15.42 ms, with a frame rate of approximately 64 FPS. CONCLUSIONS: The method presented in this paper achieves deformation simulation of both vascular and guidewire models, demonstrating sufficient real-time performance and accuracy. The interaction efficiency between vascular and guidewire models is enhanced through the unified simulation framework and collision detection. Furthermore, it can be integrated with virtual training scenarios within the system, making it suitable for developing more advanced vascular interventional surgery training systems.

MusiKeys: Exploring Haptic-to-Auditory Sensory Substitution to Improve Mid-Air Text-Entry.

Physical QWERTY keyboards are the current standard for performing precision text-entry with extended reality devices. Ideally, there would exist a comparable, self-contained solution that works anywhere, without requiring external keyboards. Unfortunately, when physical keyboards are recreated virtually, we currently lose critical haptic feedback information from the sense of touch, which impedes typing. In this paper, we introduce the MusiKeys Technique, which uses auditory feedback in virtual reality to communicate missing haptic feedback information typists normally receive when using a physical keyboard. To examine this concept, we conducted a user study with 24 participants which encompassed four mid-air virtual keyboards augmented with increasing amounts of feedback information, along with a fifth physical keyboard for reference. Results suggest that providing clicking feedback on key-press and key-release improves typing performance compared to not providing auditory feedback, which is consistent with the literature. We also found that audio can serve as a substitute for information contained in haptic feedback, in that users can accurately perceive the presented information. However, under our specific study conditions, this awareness of the feedback information did not yield significant differences in typing performance. Our results suggest this kind of feedback replacement can be perceived by users but needs more research to tune and improve the specific techniques.

Exploring the Influence of Virtual Avatar Heads in Mixed Reality on Social Presence, Performance and User Experience in Collaborative Tasks.

In Mixed Reality (MR), users' heads are largely (if not completely) occluded by the MR Head-Mounted Display (HMD) they are wearing. As a consequence, one cannot see their facial expressions and other communication cues when interacting locally. In this paper, we investigate how displaying virtual avatars' heads on-top of the (HMD-occluded) heads of participants in a Video See-Through (VST) Mixed Reality local collaborative task could improve their collaboration as well as social presence. We hypothesized that virtual heads would convey more communicative cues (such as eye direction or facial expressions) hidden by the MR HMDs and lead to better collaboration and social presence. To do so, we conducted a between-subject study ($\mathrm{n}=88$) with two independent variables: the type of avatar (CartoonAvatar/RealisticAvatar/NoAvatar) and the level of facial expressions provided (HighExpr/LowExpr). The experiment involved two dyadic communication tasks: (i) the "20-question" game where one participant asks questions to guess a hidden word known by the other participant and (ii) a urban planning problem where participants have to solve a puzzle by collaborating. Each pair of participants performed both tasks using a specific type of avatar and facial animation. Our results indicate that while adding an avatar's head does not necessarily improve social presence, the amount of facial expressions provided through the social interaction does have an impact. Moreover, participants rated their performance higher when observing a realistic avatar but rated the cartoon avatars as less uncanny. Taken together, our results contribute to a better understanding of the role of partial avatars in local MR collaboration and pave the way for further research exploring collaboration in different scenarios, with different avatar types or MR setups.

Breaking the Isolation: Exploring the Impact of Passthrough in Shared Spaces on Player Performance and Experience in VR Exergames.

VR exergames offer an engaging solution to combat sedentary behavior and promote physical activity. However, challenges emerge when playing these games in shared spaces, particularly due to the presence of bystanders. VR's passthrough functionality enables players to maintain awareness of their surrounding environment while immersed in VR gaming, rendering it a promising solution to improve users' awareness of the environment. This study investigates the passthrough's impact on player performance and experiences in shared spaces, involving an experiment with 24 participants that examines Space (Office vs. Corridor) and Passthrough Function (With vs. Without). Results reveal that Passthrough enhances game performance and environmental awareness while reducing immersion. Players prefer an open area to an enclosed room, whether with or without Passthrough, finding it more socially acceptable. Additionally, Passthrough appears to encourage participation among players with higher self-consciousness, potentially alleviating their concerns about being observed by bystanders. Our findings provide valuable insights for designing VR experiences in shared spaces, underscoring the potential of VR's passthrough to enhance user experiences and promote VR adoption in these environments.

In Case of Doubt, One Follows One's Self: The Implicit Guidance of the Embodied Self-Avatar.

The sense of embodiment in virtual reality (VR) is commonly understood as the subjective experience that one's physical body is substituted by a virtual counterpart, and is typically achieved when the avatar's body, seen from a first-person view, moves like one's physical body. Embodiment can also be experienced in other circumstances (e.g., in third-person view) or with imprecise or distorted visuo-motor coupling. It was moreover observed, in various cases of small or progressive temporal and spatial manipulations of avatars' movements, that participants may spontaneously follow the movement shown by the avatar. The present work investigates whether, in some specific contexts, participants would follow what their avatar does even when large movement discrepancies occur, thereby extending the scope of understanding of the self-avatar follower effect beyond subtle changes of motion or speed manipulations. We conducted an experimental study in which we introduced uncertainty about which movement to perform at specific times and analyzed participants' movements and subjective feedback after their avatar showed them an incorrect movement. Results show that, when in doubt, participants were influenced by their avatar's movements, leading them to perform that particular error twice more often than normal. Importantly, results of the embodiment score indicate that participants experienced a dissociation with their avatar at those times. Overall, these observations not only demonstrate the possibility of provoking situations in which participants follow the guidance of their avatar for large motor distortions, despite their awareness about the avatar movement disruption and on the possible influence it had on their choice, and, importantly, exemplify how the cognitive mechanism of embodiment is deeply rooted in the necessity of having a body.