Artificial intelligence (AI) is increasingly applied to healthcare decision-making; however, many persistent patient safety risks arise from sociotechnical conditions such as communication breakdowns, coordination failures, and organisational culture rather than diagnostic or decision error alone. While simulation can engage these dimensions of care, AI-supported simulation remains limited by heterogeneity and a lack of explicit conceptual structure. This study presents a narrative and conceptual review of the healthcare simulation and AI literature to identify structural barriers to coherent AI reasoning about simulation. Drawing on this synthesis, we introduce Transformative Simulation (TfS) as an intentional framework that can be formalised as an ontology for AI-supported simulation focused on cultural and systems-level change. TfS structures simulation through explicit Simulation-Based Intentions, an aligned design–delivery–data–debrief process, and foundational considerations of purpose, perspective, power, preparation, and possibility. Framed in this way, TfS enables AI systems to interpret simulation artefacts in relation to declared intent, sociotechnical context, and ethical boundaries. We further describe an Intentionality–Simulation–Intelligence triad and a continuous learning loop that align human values, simulation structure, and AI reasoning. The findings of this review suggest that an important challenge in applying AI to healthcare simulation may be ontological as well as technical, and that explicit representation of intention and context is necessary to support coherent, context-sensitive, and system-aligned AI reasoning in healthcare.

Ask any educator, and they will respond that engagement is an important factor in their teaching. However, engagement is a complex, multidimensional construct comprising behavioural, cognitive, emotional, and agentic dimensions. Despite growing interest in this area, the conceptualisation and measurement of engagement in medical education remain inconsistent. This systematic review aims to examine how engagement is defined, conceptualised, and measured in studies involving medical students. A systematic literature search was conducted in February 2025 across five databases for peer-reviewed studies published within the last decade. Studies were included if they focused on medical students, collected original data, and measured engagement within the context of a medical curriculum. Data extraction and screening were performed independently by two reviewers following PRISMA guidelines. Studies were analysed for their conceptual framework, dimensions of engagement measured, data collection methods, and study design. A total of 26 studies that met the eligibility criteria were included in this systematic review. Most studies measured behavioural (n=21), cognitive (n=19), and emotional engagement (n=17), while agentic engagement was least frequently measured (n=4). Most studies employed a quantitative approach, using survey instruments (n=14) and engagement metrics (n=5) to measure engagement, while a small number of studies adopted a qualitative approach, including interviews (n=4) and observations (n=4) to measure engagement. Engagement was mainly measured as a multidimensional construct, but some studies treated it as a unidimensional construct Engagement remains inconsistently and often poorly defined, as evidenced by the exclusion of more than half of initially screened studies for lacking rigorous measurement of engagement. The rise of technology-driven interventions has led to an increasing interest in ensuring that students are engaged in learning to achieve the desired learning outcomes successfully. Future research should systematically incorporate behavioural, cognitive, emotional, and agentic engagement dimensions to advance understanding and enhance educational practices. Not applicable

PURPOSE:Three-dimensional (3D)-printed models have been increasingly used in medical education, but most studies have focused on satisfaction or outcomes following isolated learning activities. This study aimed to explore students' perceptions of learning, engagement, usability, and learning strategies after completing a series of neuroanatomy-related coloring activities using a low-cost 3D-printed model. METHODS:This cross-sectional study involved Year 1 medical students at Duke-NUS Medical School. Students participated in 3 structured coloring activities using a modular 3D-printed brain model during a neuroanatomy session. An anonymous survey was administered 1 week after the third activity to assess students' perceived learning value, engagement (behavioral, cognitive, emotional, and agentic), usability, and learning strategies using Likert-scale items and open-ended questions. RESULTS:A total of 48 students completed the survey, and the instrument showed acceptable to high internal consistency. Students reported high perceived learning value, positive engagement across multiple domains during the coloring activity, and high usability of the model. Participation in the learning activities was associated with significantly higher behavioral and agentic engagement, perceived learning value, and greater use of learning strategies than non-participation. Overall, active manipulation and hands-on exploration were perceived as beneficial for learning. CONCLUSION:Low-cost 3D-printed brain models may serve as valuable learning tools to complement existing anatomy teaching approaches when paired with well-designed learning activities. Students reported positive learning experiences and high engagement during the activities. These findings highlight the importance of sound pedagogical design and curriculum integration to maximize learning.

Haptic interactions, such as touching an object in virtual reality, involve detecting a plethora of sensations through the skin. Whilst tactile displays exist to simulate and manipulate all of these cues individually, little progress has been made constructing devices that can control multiple cues simultaneously. This paper presents a tactile display technology that offers both softness and temperature change. A prototype display, based on particle jamming and the thermal transfer of heatd and cooled water, is evaluated in terms of its ability to change both stiffness and temperature. Mechanical evaluations demonstrate controllable stiffness increase of 300 ^∘ C up to 50 ^∘ C, with closed-loop control maintaining a ±0.2 ^∘ C error from a setpoint. This work advances the design of multimodal tactile displays with applications to perceptual research, medical simulation, and affective haptics.

BackgroundThe proliferation of educational technologies presents both opportunities and challenges for health professions educators. A prior institutional needs assessment found that educators across all professions struggle to adopt these technologies, as they must navigate not only technical requirements but also the pedagogical principles that govern their effective use. This descriptive study evaluated a 4-credit interprofessional Executive Certificate (EC) designed to equip educators with the technological tools and the underpinning pedagogical principles to support their use. The course participants include doctors, nurses, allied health professionals, and education support administrative staff actively involved in teaching and learning within the institution.MethodsGraduates across 5 years (2021–2025) of the Technology Enhanced Learning for Health Professions Education (TEL4HPE) were invited to complete an online survey that assesses the outcomes at Kirkpatrick Level 2 (self-efficacy), Level 3 (behavior), and Level 4 (results). The survey was designed to measure self-efficacy in TEL competencies, behavioral changes in teaching practice and organizational impact using Likert-scale and slider-scale items analyzed with descriptive statistics, Kruskal-Wallis test and one-way ANOVA.ResultsSeventy-one participants completed the survey (44.1% response rate) from across six professional groups. They reported high confidence in applying educational principles (M = 4.13) and using technology for teaching (M = 4.07). After completing the program, most respondents reported redesigning their courses (60.6%) or integrating new technology into their teaching practice (57.7%). About 60% of the respondents shared that their institution had adopted the TEL initiatives they introduced. No significant differences were found across cohorts or professional groups, suggesting an equitable impact.ConclusionThe TEL4HPE program was associated with high self-reported confidence, reported changes in teaching practice, and perceived organizational influence. The interprofessional cohort model provides a promising approach to faculty development for health professions educators, with implications for institutional design and support of TEL initiatives.

Myoelectric prosthetic hands are typically controlled to move between discrete positions and do not provide sensory feedback to the user. In this work, we present and evaluate a closed-loop, continuous myoelectric prosthetic hand controller, that can continuously control the position of multiple degrees of freedom of a prosthesis while rendering proprioceptive feedback to the user via a haptic feedback armband. Twenty-eight participants without and ten participants with upper limb difference (ULD) were recruited to holistically evaluate the physical and psychological effects of the controller via isolated control and sensory tasks, dexterity assessments, embodiment and task load questionnaires, and post-study interviews. The combination of proprioceptive feedback and continuous control enabled more accurate position and force modulation than without proprioceptive feedback, and restored blindfolded object identification ability to open-loop discrete controller levels. Dexterity assessment and embodiment questionnaire results revealed no significant physical performance or psychological embodiment differences between control types, with the exception of perceived sensation questions, which were significantly higher (p < 0.001) for closed-loop controllers. Key differences between participants with and without ULD were identified, including increasingly lower perceived body completeness and heterogeneity in frustration in participants with ULD, which can inform future development and rehabilitation.

An elastic rod is a long and thin body able to sustain large global deformations, even if local strains are small. The Cosserat rod is a non-linear elastic rod with an oriented centreline, which enables modelling of bending, stretching and twisting deformations. It can be used for physically-based computer simulation of threads, wires, ropes, as well as flexible surgical instruments such as catheters, guidewires or sutures. We present a massively-parallel implementation of the original CoRdE model as well as our inextensible variation. By superseding the CUDA Scalable Programming Model and using inter-block synchronization, we managed to simulate multiple physics time-steps per single kernel launch utilizing all the GPU's streaming multiprocessors. Under some constraints, this results in nearly constant computation time, regardless of the number of Cosserat elements simulated. When executing 10 time-steps per single kernel launch, our implementation of the original, extensible CoRdE was x40.0 faster. In a number of tests, the GPU implementation of our inextensible CoRdE modification achieved an average speed-up of x15.11 over the corresponding CPU version. Simulating a catheter/guidewire pair (2x512 Cosserat elements) in a cardiovascular application resulted in a 13.5 fold performance boost, enabling for accurate real-time simulation at haptic interactive rates (0.5-1kHz).

INTRODUCTION:The availability of different tools for teaching and learning has made it challenging for educators to determine which tools are more effective and appropriate for helping students achieve learning outcomes. This is particularly evident in teaching human anatomy, where a range of modalities is used to complement cadaveric dissection. Despite the positive reception of these tools, their impact on learning outcomes remains uncertain. To address this issue, we utilise the Activity Theory Framework to analyse students' interaction with two tools - a 3D-printed (3DP) model and a digital resource (DR) - to answer two clinical questions relating to the lower spine. METHOD:This study took place in a graduate medical school in Singapore. Forty-six students voluntarily signed up for the session. They were grouped in small teams of between 4 and 6 students, and interactions were video recorded. Using a cross-over design, five groups answered a clinical scenario using a 3DP lumbar spine model, while the other five groups used the DR. The teams then swapped the 3DP with the DR and vice versa to answer a second clinical scenario of similar difficulty. RESULTS:There was no significant performance difference in terms of scores. Using a case study approach, we found that students engaged in more authentic discussions using the 3DP compared to the DR. Despite having access to the system early in the semester, students appeared unfamiliar with using the DR, struggling initially to navigate the software. We found the 3DP model encouraged collaborative discussion as students could physically use it as a tool for discussion by pointing and manipulating the different components in three dimensions, which could not be done with the DR as it operates on a two-dimensional screen. CONCLUSION:This study used activity theory to understand the impact of two educational tools on learning. Activity theory allowed a better understanding of tools' dynamics in learning when looking beyond score performance. We found that 3DP better encouraged collaboration among students than DR. Educators must consider the ease of use of the learning tools when designing activities so that learners will utilise the system's affordances.

Background:With the growing use of technology in medical education, a framework is needed to evaluate learners' and educators' acceptance of these technologies. In this context, the Technology Acceptance Model (TAM) offers a valuable theoretical framework, providing insights into the determinants influencing users' acceptance and adoption of technology. Objective:This review aims to systematically synthesize the body of research in medical education that uses the TAM. Methods:An electronic literature search was conducted using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach in February 2024 on the Embase, MEDLINE, PsycINFO, PubMed, and Web of Science databases, yielding 680 articles. Upon elimination of duplicates and applying the exclusion criteria, a total of 39 articles were retained. To evaluate the quality of the study, the Medical Education Research Study Quality Instrument score was calculated for each analysis with a qualitative component. Results:Studies using TAM in medical education began in 2010, with the model's application relatively rare up to 2016. Most of the studies were quantitative, operationalizing the TAM as a survey instrument, but it was also used as a research framework in qualitative data analysis. Structural equation modeling, descriptive analysis, and correlation analysis were the most common data analysis approaches in the studies. E-learning and mobile learning were the predominant learning interventions explored, but there were indications that novel learning technologies such as augmented reality, virtual reality, and 3D printing were being investigated. Conclusions:The study's findings reveal an expanding scholarly engagement with using TAM in medical education. Although the TAM has been mostly used as a survey instrument, it can also be adapted as a qualitative research framework to analyze data. This systematic review provides a foundation for future research to understand the factors influencing users' acceptance of technology, especially in medical education.

Despite decades of research and development, myoelectric prosthetic hands lack functionality and are often rejected by users. This lack in functionality can be partially attributed to the widely accepted anthropomorphic design ideology in the field; attempting to replicate human hand form and function despite severe limitations in control and sensing technology. Instead, prosthetic hands can be tailored to perform specific tasks without increasing complexity by shedding the constraints of anthropomorphism. In this paper, we develop and evaluate four open-source modular non-humanoid devices to perform the motion required to replicate human flicking motion and to twist a screwdriver, and the functionality required to pick and place flat objects and to cut paper. Experimental results from these devices demonstrate that, versus a humanoid prosthesis, non-humanoid prosthesis design dramatically improves task performance, reduces user compensatory movement, and reduces task load. Case studies with two end users demonstrate the translational benefits of this research. We found that special attention should be paid to monitoring end-user task load to ensure positive rehabilitation outcomes.

Background Patients living with obesity continue to experience body image dissatisfaction following bariatric metabolic surgery. The underlying reasons are poorly understood but may be due to unmet expectations. Negative body image perception following metabolic surgery leads to poorer psychological and clinical outcomes. This study aims to establish the acceptability and feasibility of three-dimensional (3D) reconstruction and virtual reality (VR) as a method of providing psychological support to bariatric patients to improve body image satisfaction and interventional outcomes.Methods Seven participants were recruited from the Imperial Weight Centre. 3D photographs were captured and processed to produce two 3D reconstructed images with 15% and 25% total weight loss. Participants were shown their images using VR and participated in peer group workshops.Results Six participants were retained until the end of the study. Five out of six participants agreed the images provided them with a more accurate representation of their body changes and overall appearance following bariatric metabolic surgery. All participants strongly agreed with the group setting and felt VR facilitated discussions on body image. Overall, all participants felt that the use of VR and 3D reconstruction is beneficial in supporting patients to adjust to changes in their body image after bariatric metabolic surgery.Conclusions This is the first study to explore and demonstrate that 3D reconstruction and VR is an acceptable and feasible method providing patients with a realistic expectation of how their body will change following significant weight loss, potentially improving body image satisfaction after surgery, as well as psychological and interventional outcomes.

OBJECTIVES There is an increasing availability of digital technologies for teaching and learning of human anatomy. Studies have shown that such applications allow for better spatial awareness than traditional methods. These digital human anatomy platforms offer users myriad features, such as the ability to manipulate 3D models, conduct prosection, investigate anatomical regions through virtual reality, or perform knowledge tests on themselves. This study examined what faculty members’ value when using digital human anatomy platforms for teaching and what students value when using these platforms for learning. METHODS Six anatomy faculty members and 21 students were selected to participate in this study. After using the three digital anatomy platforms for at least 1 week, a survey was conducted to record their feedback in 4 categories: usability, interactive features, level of detail, and learning support. Respondents’ Qualitative feedback within each category was also analyzed to strengthen the study's findings. RESULTS The study's findings showed that faculty members and students have different priorities when evaluating digital anatomy platforms. Faculty members valued platforms that provided better accuracy and detailed anatomical structures, while students prioritized usability above the rest of the features. CONCLUSION Given that faculty and students have different preferences when selecting digital anatomy platforms, this article proposed that educators maximize the specific affordances offered by the technology by having a clear pedagogy and strategy on how the technology will be incorporated into the curriculum to help students achieve the desired learning outcomes.

Rectal examination through proctoscopy or rigid sigmoidoscopy is a common investigation in clinical practice. It is an important diagnostic tool for the workup and management of anorectal pathologies. Performing the examination can be daunting not only for patients but also for junior doctors. There are associated risks with the procedure, such as pain, diagnostic failure, and perforation of the bowel. Simulation-based training is recognised as an important adjunct in clinical education. It allows students and doctors to practice skills and techniques at their own pace in a risk-free environment. These skills can then be transferred to and developed further in clinical practice. There is extensive research published regarding the role of simulation-based training in endoscopy, however, we identified no published study regarding simulation-based training in rigid sigmoidoscopy or proctoscopy. This study aims to establish the initial face, content, and construct validity of a tool-based visual anorectal examination advanced simulator model for proctoscopy and rigid sigmoidoscopy. This innovative, highly realistic simulated environment aims to enhance the training of healthcare professionals and improve the efficiency of detecting and diagnosing distal colorectal disease.

Anatomical education is transitioning from the time-honored cadaveric dissection to a blend of learner-centered and technology-enhanced learning approaches. In view of the increased use of various technologies for teaching and learning human anatomy, the aim of this study is to explore students' acceptance of four learning technologies using the technology acceptance model (TAM). This work was conducted at a graduate medical school in Singapore with first-year MD Program students. The acceptances of the four learning technologies were compared in two studies. In Study 1 (n = 46), we compared a 3D-printed (3DP) model with Primal Pictures to answer a clinical question in a Spine Anatomy Tutorial; in Study 2 (n = 55), we compared the Anatomage Table and Primal VR for a Brain Anatomy tutorial. There was a statistically significant preference (p < 0.05) for 3DP models over Primal Pictures for learning Spine Anatomy, and for Primal VR over Anatomage for learning Brain Anatomy. The perceived ease of use of any technology does not appear to influence the behavioral intention to use it. Qualitative feedback suggests that visualization and spatial relationships were among the most important facilitators of learning. Technology should be an enabler in learning but some technologies have a steeper learning curve than others. Therefore, to increase its perceived usefulness, educators must leverage the affordances of the technology when designing learning activities.

Human hands are able to grasp a wide range of object sizes, shapes, and weights, achieved via reshaping and altering their apparent grasping stiffness between compliant power and rigid precision. Achieving similar versatility in robotic hands remains a challenge, which has often been addressed by adding extra controllable degrees of freedom, tactile sensors, or specialised extra grasping hardware, at the cost of control complexity and robustness. We introduce a novel reconfigurable four-fingered two-actuator underactuated gripper—the Hydra Hand—that switches between compliant power and rigid precision grasps using a single motor, while generating grasps via a single hydraulic actuator—exhibiting adaptive grasping between finger pairs, enabling the power grasping of two objects simultaneously. The mode switching mechanism and the hand's kinematics are presented and analysed, and performance is tested on two grasping benchmarks: one focused on rigid objects, and the other on items of clothing. The Hydra Hand is shown to excel at grasping large and irregular objects, and small objects with its respective compliant power and rigid precision configurations. The hand's versatility is then showcased by executing the challenging manipulation task of safely grasping and placing a bunch of grapes, and then plucking a single grape from the bunch.

Particle jamming is an emergent technology widely used to create haptic devices that can change their physical stiffness to render hard or soft surfaces. Conventional implementations of particle jamming-based interfaces have relied on bulky and expensive vacuum systems to force the particles together. This paper presents designs for two alternative, mechatronic approaches to activating a particle jamming-based haptic interface. Each design is subjected to a battery of mechanical tests to evaluate the range and uniformity of the achievable hardness change and response time. Results are presented and the effectiveness of these designs is considered against established pneumatic approaches.

Physical interaction with patients, for example conducted as part of a diagnostic examination or surgical procedure, provides clinicians with a wealth of information about their condition. Simulating this interaction is of great interest to researchers in both haptics and medical education, and the development of softness changing tactile interfaces is important in recreating the feel of different soft tissues. This paper presents designs for a variety of novel electromechanical and electromagnetic mechanisms for controlling particle jamming-based, hardness changing tactile displays, intended to allow medical trainees to experience these physical interactions in a range of simulation settings such as clinical skills teaching laboratories. Each design is then subjected to a battery of mechanical tests to evaluate its effectiveness compared to the state of the art, as well as their suitability for simulating the physical hardness of different types of soft tissues, previously characterised in established literature. These results demonstrate that all of the technologies presented are able to exhibit a measurable hardness change, with Shore hardness values between 3A and 57A achieved by the most effective constriction-based device. The electromechanical devices based on constriction and compression, and the state-of-the-art pneumatic device, were able to achieve hardness changes within a range that is useful for replicating the softness of organic tissue. The electromechanical and electromagnetic devices were also found to effect their full range of hardness change in less than a second, compared to several seconds for the state-of-the-art. These results show that the performance of softness changing tactile displays can be improved with the electromechanical actuation techniques proposed in this paper, and that such displays are able to replicate the physical characteristics of soft tissues and may therefore be of benefit in medical training and simulation scenarios.

Automated industries lead to high quality production, lower manufacturing cost and better utilization of human resources. Robotic manipulator arms have major role in the automation process. However, for complex manipulation tasks, hard coding efficient and safe trajectories is challenging and time consuming. Machine learning methods have the potential to learn such controllers based on expert demonstrations. Despite promising advances, better approaches must be developed to improve safety, reliability, and efficiency of ML methods in both training and deployment phases. This survey aims to review cutting edge technologies and recent trends on ML methods applied to real-world manipulation tasks. After reviewing the related background on ML, the rest of the paper is devoted to ML applications in different domains such as industry, healthcare, agriculture, space, military, and search and rescue. The paper is closed with important research directions for future works.

Transcranial Magnetic Stimulation (TMS) is a non-invasive and painless technique used in both clinical trials and research on cortical activity and brain networks. TMS involves the use of an electromagnetic coil, which can induce powerful but brief magnetic pulses. When the coil is headed against the scalp, it can induce electrical activity in underlying brain tissue. For effective results, the TMS coil should be in appropriate contact with patients' scalp and positioned for consistent stimulation. In many cases, it requires researchers and clinicians to not only hold and position the coil on subjects' head, also to take care to ensure appropriate and consistent contact between the TMS coil and subject's scalp. This task is noticeably tiresome for the operators considering weight of the coil and a dense cable attached to it. On the other side, the patient or participant has to sit motionless; otherwise, the contact will be lost and the stimulation will have a reduced impact. In this paper, we propose and develop a haptically-enabled teleoperated robotic platform that removes all those limitations and burdensome from both TMS operators and patients/participants. The operator, through a haptic interface, remotely controls a robotic arm holding the coil. This system provides the operator with the sense of touch to feel the contact force between the coil and patient/participant's head. Therefore, operators and patients/participants do not need to be in the same location while conducting TMS, including the “motor thresholding” procedure. This will offer a huge benefit to the healthcare services in rural areas. Experimental evaluations carried out to demonstrate the effectiveness of the proposed robotic system.