Abstract: The use of CAD and 3D printing of surgical guides (SGs) for osteotomies is a widely developed practice in orthopaedic surgery, and particularly in maxillo-facial interventions, but validation studies rarely occur in literature. The present study defines a methodology to validate SGs dimensionally and mechanically through geometrical analysis, tensile testing, contact simulations, and abrasion testing. Distortions between the 3D printed SGs and the CAD model are quantified and an average deviation error for each production process step is obtained. Mechanical analysis identifies a way of applying the load on the SG to measure their equivalent linear stiffness (N/mm), maximum displacement (mm) and corresponding tolerable load (N) by varying some dimensional parameters. The stress state was assessed by finite element method (FEM) analysis, then the numerical results were compared with experimental ones using tensile tests: stiffness, maximum displacement and the corresponding loads were evaluated. The distribution of contact pressure on soft tissues was obtained numerically by FEM analysis. Finally, an ad hoc machine has been specially built to engrave discoidal specimens with typical operating room conditions. The methodology has been validated using 11 SG fibular and mandibular specimens and reporting the obtained results of each procedure step.

Keywords: CAD | Cutting guides | FEM | Maxillo-facial surgery | Surgical guides

Abstract: In orthopedic surgery and maxillofacial there is a growing use of augmented reality (AR) as a technology to increase the visual perception of the surgeon in the operating room. The objective of this review is to analyze the state of the art in the use of AR for osteotomies, highlighting the advantages and the most-known open issues to be addressed in the future research. Scopus, Web of Science, Pubmed and IEEE Xplore databases have been explored with a keyword search, setting the time limits from January 2017 to January 2023, inclusive. Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines has been used in this review, focusing on anatomical districts, real-virtual environment interaction, advantaged and limitations of existing AR-based applications. 49 articles met the inclusion criteria and have been selected in the final analysis. For the sake of clarity, works have been grouped according to the anatomical district, but also the real-virtual environment interaction methodology was reported, as well as information regarding accuracy assessment. A Quality Function Deployment (QFD) has been used to assess the AR-based solutions with regards to the more traditional freehand (FH) and Patient Specific Template (PST) approaches. Finally, some suggestions to foster the AR-based solution adoption in osteotomies treatment have been drawn, considering the highlighted advantages and limitations of this technology. The AR resulted to meet the surgeons’ needs more than other traditional approaches. Among the emerged advantages, AR can lead to a better surgical field accessibility, more flexible solutions and lower the management effort. Nonetheless, future research should address some well-known issues, among which the calibration time, the robustness of the tracking, and the HMDs discomfort.

Keywords: Augmented reality | Cutting guides | Maxillofacial surgery | Mixed reality | Orthopedic surgery | Osteotomies | Patient specific templates | Surgical guides

Abstract: Developing great products is not simple; users want products that can constantly adjust to their needs. The product development process should consider not only the users’ requirements and wishes but also their perceptions and emotions during and after the human-product interaction. Traditional studies have used self-report methods to study the users’ emotions; however, technological advances are making other methods able to measure respondents’ behavior. Electroencephalography (EEG), a technique for recording and interpreting the brain’s electrical activity, is becoming a valid tool to assess users’ emotional states. This study aims to explore the EEG as a method to interpret emotions. To do this, we created three different VR scenarios characterized by different interior design and automatic chromatic variations as a stimulus; this research aims to analyze if the changes in colors and scenarios reflect on the participants’ emotional responses, specifically on Valence, Arousal, and Engagement. The findings show that EEG results are a valid aid to emotion interpretation; also that color variation might influence users’ emotions and that the emotional responses were more evident when changing between scenarios. We expect this study can provide more information regarding the potential of physiological methods to explore users’ emotions during the product design and development.

Keywords: EEG | Emotional design | Engagement | Product development

Abstract: The evaluation of hip implantation success remains one of the most relevant problems in orthopaedics. There are several factors that can cause its failure, e.g.: aseptic loosening and dislocations of the prosthetic joint due to implant impingement. Following a total hip arthroplasty, it is fundamental that the orthopaedist can evaluate which may be the possible risk factors that would lead to dislocation, or in the worst cases, to implant failure. A procedure has been carried out with the aim of evaluating the Range of Movement (ROM) of the implanted prosthesis, to predict whether the inserted implant is correctly positioned or will be prone to dislocation or material wear due to the malposition of its components. Leveraging on a previous patented methodology that consists in the 3D reconstruction and movement simulation of the hip joint, this work aims to provide a more effective visualization of the simulation results through Mixed Reality (MR). The use of MR for the representation of hip kinematics and implant position can provide the orthopaedic surgeon with a deeper understanding of the orientation and position of implanted components, as well as the consequences of such placements while looking directly at the patient. To this end, an anchoring system based on a body-tracking recognition library was developed, so that both completely automatic and human-assisted options are available without additional markers or sensors. An Augmented Reality (AR) prototype has been developed in Unity 3D and used on HoloLens 2, integrating the implemented human-assisted anchoring system option.

Keywords: Computer-aided surgery | HoloLens 2 | Mixed reality | THA assessment | Total hip arthroplasty

Abstract: In the context of human–computer interaction (HCI), understanding user engagement (UE) while interacting with a product or service can provide valuable information for enhancing the design process. UE has been a priority research theme within HCI, as it assesses the user experience by studying the individual’s behavioral response to some stimulus. Many studies looking to quantify the UE are available; however, most use self-report methods that rely only on participants’ answers. This study aims to explore a non-traditional method, specifically electroencephalography, to analyze users’ engagement while interacting with an advergame, an interactive form of advertising in video games. We aim to understand if a more interactive type of advertising will enhance the UE and whether, at the same time, it would influence the user’s purchase intention (UPI). To do this, we computed and compared the UE during the interaction with an advergame and a conventional TV commercial while measuring the participants’ brain activity. After the interaction with both types of advertising, the UPI was also evaluated. The findings demonstrate that a more interactive advertisement increased the participants’ UE and that, in most cases, a UE increment positively influenced the UPI. This study shows an example of the potential of physiological feedback applications to explore the users’ perceptions during and after the human–product interaction. The findings show how physiological methods can be used along with traditional ones for enhancing the UE analysis and provide helpful information about the advantages of engagement measurement in HCI applications.

Keywords: advergames | EEG | purchase intention | user engagement

Abstract: Objectives: The aim of this study was to analyse changes in facial soft tissue thickness (FSTT) after corrective surgeries for dental malocclusion. The correlation between body mass index (BMI) and sex of patients and their FSTT before undergoing surgery was analysed. Materials and methods: Cone beam computed tomography of seventeen patients that underwent Le Fort I osteotomy in combination with bilateral sagittal split osteotomy were collected. Hard and soft tissue landmarks were selected basing on the interventions. FSTT were computed, and measurements from pre- to post-operative were compared. The relationship between FSTT, sex, and BMI was investigated. Results: Considering the comparison between pre- and post-operative measurements, any significant difference emerged (p >.05). The Pearson’s correlation coefficient computed between BMI and the FSTT (pre-operative) showed a correlation in normal-weight patients; the region-specific analysis highlighted a stronger correlation for specific landmarks. Higher median values emerged for women than for men; the subset-based analysis showed that women presented higher values in the malar region, while men presented higher values in the nasal region. Conclusions: The considered surgeries did not affect the FSTT of the patients; differences related to BMI and sex were found. A collection of FSTT mean values was provided for twenty landmarks of pre- and post-operative of female and male subjects. Clinical relevance: This exploratory analysis gave insights on the behaviour of STT after maxillofacial surgeries that can be applied in the development of predictive methodologies for soft tissue displacements and to study modifications in the facial aspect of the patients.

Keywords: Bilateral sagittal split osteotomy (BSSO) | Body mass index (BMI) | Facial landmarks | Le Fort I osteotomy (LFI) | Soft tissue thickness (STT)

Abstract: Most cultural promotion and dissemination are nowadays performed through the digitization of heritage sites and museums, a necessary requirement to meet the new needs of the public. Augmented Reality (AR), Mixed Reality (MR), and Virtual Reality (VR) have the potential to improve the experience quality and educational effect of these sites by stimulating users’ senses in a more natural and vivid way. In this respect, head-mounted display (HMD) devices allow visitors to enhance the experience of cultural sites by digitizing information and integrating additional virtual cues about cultural artifacts, resulting in a more immersive experience that engages the visitor both physically and emotionally. This study contributes to the development and incorporation of AR, MR, and VR applications in the cultural heritage domain by providing an overview of relevant studies utilizing fully immersive systems, such as headsets and CAVE systems, emphasizing the advantages that they bring when compared to handheld devices. We propose a framework study to identify the key features of headset-based Extended Reality (XR) technologies used in the cultural heritage domain that boost immersion, sense of presence, and agency. Furthermore, we highlight core characteristics that favor the adoption of these systems over more traditional solutions (e.g., handheld devices), as well as unsolved issues that must be addressed to improve the guests’ experience and the appreciation of the cultural heritage. An extensive search of Google Scholar, Scopus, IEEE Xplore, ACM Digital Library, and Wiley Online Library databases was conducted, including papers published from January 2018 to September 2022. To improve review reporting, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used. Sixty-five papers met the inclusion criteria and were classified depending on the study's purpose: education, entertainment, edutainment, touristic guidance systems, accessibility, visitor profiling, and management. Immersive cultural heritage systems allow visitors to feel completely immersed and present in the virtual environment, providing a stimulating and educational cultural experience that can improve the quality and learning purposes of cultural visits. Nonetheless, the analyzed studies revealed some limitations that must be faced to give a further impulse to the adoption of these technologies in the cultural heritage domain.

Keywords: Augmented reality (AR) | Cultural heritage | Digital heritage | Head-mounted display (HMD) | Mixed reality (MR) | Virtual reality (VR)

Abstract: Background: Addressing intraoperative bleeding remains a significant challenge in the field of robotic surgery. This research endeavors to pioneer a groundbreaking solution utilizing convolutional neural networks (CNNs). The objective is to establish a system capable of forecasting instances of intraoperative bleeding during robot-assisted radical prostatectomy (RARP) and promptly notify the surgeon about bleeding risks. Methods: To achieve this, a multi-task learning (MTL) CNN was introduced, leveraging a modified version of the U-Net architecture. The aim was to categorize video input as either “absence of blood accumulation” (0) or “presence of blood accumulation” (1). To facilitate seamless interaction with the neural networks, the Bleeding Artificial Intelligence-based Detector (BLAIR) software was created using the Python Keras API and built upon the PyQT framework. A subsequent clinical assessment of BLAIR’s efficacy was performed, comparing its bleeding identification performance against that of a urologist. Various perioperative variables were also gathered. For optimal MTL-CNN training parameterization, a multi-task loss function was adopted to enhance the accuracy of event detection by taking advantage of surgical tools’ semantic segmentation. Additionally, the Multiple Correspondence Analysis (MCA) approach was employed to assess software performance. Results: The MTL-CNN demonstrated a remarkable event recognition accuracy of 90.63%. When evaluating BLAIR’s predictive ability and its capacity to pre-warn surgeons of potential bleeding incidents, the density plot highlighted a striking similarity between BLAIR and human assessments. In fact, BLAIR exhibited a faster response. Notably, the MCA analysis revealed no discernible distinction between the software and human performance in accurately identifying instances of bleeding. Conclusion: The BLAIR software proved its competence by achieving over 90% accuracy in predicting bleeding events during RARP. This accomplishment underscores the potential of AI to assist surgeons during interventions. This study exemplifies the positive impact AI applications can have on surgical procedures.

Keywords: artificial intelligence | complications | prostate cancer | robotics

Abstract: In the last decade, museums and exhibitions have benefited from the advances in Virtual Reality technologies to create complementary virtual elements to the traditional visit. The aim is to make the collections more engaging, interactive, comprehensible and accessible. Also, the studies regarding users’ and visitors’ engagement suggest that the real affective state cannot be fully assessed with self-assessment techniques and that other physiological techniques, such as EEG, should be adopted to gain a more unbiased and mature understanding of their feelings. With the aim of contributing to bridging this knowledge gap, this work proposes to adopt literature EEG-based indicators (valence, arousal, engagement) to analyze the affective state of 95 visitors interacting physically or virtually (in a VR environment) with five handicraft objects belonging to the permanent collection of the Museo dell’Artigianato Valdostano di Tradizione, which is a traditional craftsmanship museum in the Valle d’Aosta region. Extreme Gradient Boosting (XGBoost) was adopted to classify the obtained engagement measures, which were labeled according to questionnaire replies. EEG analysis played a fundamental role in understanding the cognitive and emotional processes underlying immersive experiences, highlighting the potential of VR technologies in enhancing participants’ cognitive engagement. The results indicate that EEG-based indicators have common trends with self-assessment, suggesting that their use as ‘the ground truth of emotion’ is a viable option.

Keywords: craftsmanship | cultural heritage | EEG | user engagement | Virtual Reality | XGBoost

Abstract: Introduction: The current study presents a deep learning framework to determine, in real-time, position and rotation of a target organ from an endoscopic video. These inferred data are used to overlay the 3D model of patient's organ over its real counterpart. The resulting augmented video flow is streamed back to the surgeon as a support during laparoscopic robot-assisted procedures. Methods: This framework exploits semantic segmentation and, thereafter, two techniques, based on Convolutional Neural Networks and motion analysis, were used to infer the rotation. Results: The segmentation shows optimal accuracies, with a mean IoU score greater than 80% in all tests. Different performance levels are obtained for rotation, depending on the surgical procedure. Discussion: Even if the presented methodology has various degrees of precision depending on the testing scenario, this work sets the first step for the adoption of deep learning and augmented reality to generalise the automatic registration process.

Keywords: abdominal | Kidney | prostate

Abstract: Background: Augmented Reality (AR) represents an innovative technology to improve data visualization and strengthen the human perception. Among Human–Machine Interaction (HMI), medicine can benefit most from the adoption of these digital technologies. In this perspective, the literature on orthopedic surgery techniques based on AR was evaluated, focusing on identifying the limitations and challenges of AR-based healthcare applications, to support the research and the development of further studies. Methods: Studies published from January 2018 to December 2021 were analyzed after a comprehensive search on PubMed, Google Scholar, Scopus, IEEE Xplore, Science Direct, and Wiley Online Library databases. In order to improve the review reporting, the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines were used. Results: Authors selected sixty-two articles meeting the inclusion criteria, which were categorized according to the purpose of the study (intraoperative, training, rehabilitation) and according to the surgical procedure used. Conclusions: AR has the potential to improve orthopedic training and practice by providing an increasingly human-centered clinical approach. Further research can be addressed by this review to cover problems related to hardware limitations, lack of accurate registration and tracking systems, and absence of security protocols.

Keywords: augmented reality | digital health | HoloLens | Human–Computer Interaction (HCI) | Human–Machine Interaction (HMI) | intraoperative | medical training | mixed reality | rehabilitation

Abstract: The current study aimed to propose a Deep Learning (DL) based framework to retrieve in real-time the position and the rotation of an object in need of maintenance from live video frames only. For testing the positioning performances, we focused on intervention on a generic Fused Deposition Modeling (FDM) 3D printer maintenance. Lastly, to demonstrate a possible Augmented Reality (AR) application that can be built on top of this, we discussed a specific case study using a Prusa i3 MKS FDM printer. This method was developed using a You Only Look Once (YOLOv3) network for object detection to locate the position of the FDM 3D printer and a subsequent Rotation Convolutional Neural Network (RotationCNN), trained on a dataset of artificial images, to predict the rotations’ parameters for attaching the 3D model. To train YOLOv3 we used an augmented dataset of 1653 real images, while to train the RotationCNN we utilized a dataset of 99.220 synthetic images, showing the FDM 3D Printer with different orientations, and fine-tuned it using 235 real images tagged manually. The YOLOv3 network obtained an AP (Average Precision) of 100% with Intersection Over Unit parameter of 0.5, while the RotationCNN showed a mean Geodesic Distance of 0.250 (σ = 0.210) and a mean accuracy to detect the correct rotation r of 0.619 (σ = 0.130), considering as acceptable the range [r − 10, r + 10]. We then evaluate the CAD system performances with 10 non-expert users: the average speed improved from 9.61 (σ = 1.53) to 5.30 (σ = 1.30) and the average number of actions to complete the task from 12.60 (σ = 2.15) to 11.00 (σ = 0.89). This work is a further step through the adoption of DL and AR in the assistance domain. In future works, we will overcome the limitations of this approach and develop a complete mobile CAD system that could be extended to any object that presents a 3D counterpart model.

Keywords: Augmented reality | CAD assistance | Deep learning | Neural network

Abstract: Building great products or services is not easy; users want products and services that exceed their expectations and evolve with their needs; it is not just about building the right features. Knowing the user engagement (UE) towards a physical, virtual product or service can give valuable information that could be used as feedback for the design, enhancing its chances of success. In the context of user-centered design, UE is the assessment of the user experience characterized by the study of the individual's cognitive, affective, and behavioral response to some stimulus, such as a product, a service, or a website. UE considers not only the users’ requirements and wishes but also their perceptions and reactions during and after an interaction with a product, system, or service. Many studies looking to quantify the UE are available. Still, a framework that provides a generic view of the most commonly used methods and metrics to measure UE does not yet exist in the literature. Aiming to understand the UE better, in this research, we developed a conceptual framework summarizing the available metrics and techniques used across different contexts, including good practices of self-report methods and physiological approaches. We expect this study will allow future researchers, developers, and designers to consider the UE as one of the most prominent product/service success indicators and use this guideline to find the more appropriate method, technique, and metric for its measurement.

Keywords: Consumer engagement | Physiological | UCD | User engagement measurement

Abstract: Driver inattention is the primary cause of vehicle accidents; hence, manufacturers have introduced systems to support the driver and improve safety; nonetheless, advanced driver assistance systems (ADAS) must be properly designed not to become a potential source of distraction for the driver due to the provided feedback. In the present study, an experiment involving auditory and haptic ADAS has been conducted involving 11 participants, whose attention has been monitored during their driving experience. An RGB-D camera has been used to acquire the drivers’ face data. Subsequently, these images have been analyzed using a deep learning-based approach, i.e., a convolutional neural network (CNN) specifically trained to perform facial expression recognition (FER). Analyses to assess possible relationships between these results and both ADAS activations and event occurrences, i.e., accidents, have been carried out. A correlation between attention and accidents emerged, whilst facial expressions and ADAS activations resulted to be not correlated, thus no evidence that the designed ADAS are a possible source of distraction has been found. In addition to the experimental results, the proposed approach has proved to be an effective tool to monitor the driver through the usage of non-invasive techniques.

Keywords: ADAS | CNN | DADA | Deep learning | Driver’s attention | RGB-D camera

Abstract: Today, surgical operations are less invasive than they were a few decades ago and, in medicine, there is a growing trend towards precision surgery. Among many technological advancements, augmented reality (AR) can be a powerful tool for improving the surgery practice through its ability to superimpose the 3D geometrical information of the pre-planned operation over the surgical field as well as medical and instrumental information gathered from operating room equipment. AR is fundamental to reach new standards in maxillofacial surgery. The surgeons will be able to not shift their focus from the patients while looking to the monitors. Osteotomies will not require physical tools to be fixed on patient bones as guides to make resections. Handling grafts and 3D models directly in the operating room will permit a fine tuning of the procedure before harvesting the implant. This article aims to study the application of AR head-mounted displays (HMD) in three operative scenarios (oncological and reconstructive surgery, orthognathic surgery, and maxillofacial trauma surgery) by the means of quantitative logic using the Quality Function Deployment (QFD) tool to determine their requirements. The article provides an evaluation of the readiness degree of HMD currently on market and highlights the lacking features.

Keywords: Computer-assisted surgery | Head mounted display | Maxillofacial surgery | Precision medicine | Quality function deployment

Abstract: The development of new methods for the correct disposal of waste is unavoidable for any city that aims to become eco-friendly. Waste management is no exception. In the modern era, the treatment and disposal of infectious waste should be seen as an opportunity to generate renewable energy, resource efficiency, and, above all, to improve the population's quality of life. Northern Italy currently produces 66,600 tons/year of infectious waste, mostly treated through incineration plants. This research aims to explore a more ecological and sustainable solution, thereby contributing one more step toward achieving better cities for all. Particularly, this paper presents a conceptual design of the main sterilization chamber for infectious waste. The methodology selected was Design Thinking (DT), since it has a user-centered approach which allows for co-design and the inclusion of the target population. This study demonstrates to the possibility of obtaining feasible results based on the user's needs through the application of DT as a framework for engineering design.

Keywords: Design thinking | Eco-friendly city | Infectious waste | Resource efficiency | Sustainability | Waste management

Abstract: Patients with severe facial deformities present serious dysfunctionalities along with an unsatisfactory aesthetic facial appearance. Several methods have been proposed to specifically plan the interventions on the patient’s needs, but none of these seem to achieve a sufficient level of accuracy in predicting the resulting facial appearance. In this context, a deep knowledge of what occurs in the face after bony movements in specific surgeries would give the possibility to develop more reliable systems. This study aims to propose a novel 3D approach for the evaluation of soft tissue zygomatic modifications after zygomatic osteotomy; geometrical descriptors usually involved in face analysis tasks, i.e., face recognition and facial expression recognition, are here applied to soft tissue malar region to detect changes in surface shape. As ground truth for zygomatic changes, a zygomatic openness angular measure is adopted. The results show a high sensibility of geometrical descriptors in detecting shape modification of the facial surface, outperforming the results obtained from the angular evaluation.

Keywords: 3D face analysis | Geometrical descriptors | Malar augmentation | Orthognathic surgery | Soft tissue prediction | Zygomatic osteotomy

Abstract: Additive Manufacturing (AM), allowing the layer-by-layer fabrication of products characterized by a shape complexity unobtainable with conventional manufacturing routes, has been widely recognized as a disruptive technology enabling the transition to the Industry 4.0. In this context, the design of a Portable Assisted Mobile Device (PAMD) prototype was considered as a case study. The best practices of the re-design for AM were applied to three of the main structural components, and the most sustainable manufacturing approach between AM processes and the conventional ones was identified with respect to cumulative energy demand, carbon dioxide emissions and costs. The paper aims to promote the debate concerning the correlation between design choices, process selection and sustainable product development.

Keywords: Cost assessment | Design for Additive Manufacturing | Energy efficiency | Portable Assisted Mobile Device (PAMD)

Abstract: Recently a wide variety of applications has been developed integrating 3D functionalities. Advantages given by the possibility of relying on depth information allows the developers to design new algorithms and to improve the existing ones. In particular, for what concerns face morphology, 3D has led to the possibility to obtain face depth maps highly close to reality and consequently an improvement of the starting point for further analysis such as Face Detection, Face Authentication, Face Identification and Face Expression Recognition. The development of the aforementioned applications would have been impossible without the progress of sensor technologies for obtaining 3D information. Several solutions have been adopted over time. In this paper, emphasis is put on passive stereoscopy, structured light, time-of-flight (ToF) and active stereoscopy, namely the most used technologies for the cameras design and fulfilment according to the literature. The aim of this article is to investigate facial applications and to examine 3D camera technologies to suggest some guidelines for addressing the correct choice of a 3D sensor according to the application that has to be developed.

Keywords: 3D cameras | 3D face analysis | Sensors | Stereoscopy | Structured light | ToF

Abstract: This paper presents a learning outcomes-based methodology to produce a summative assessment to use in any course at any educational level. It takes into consideration the European Qualifications Framework (EQF) to define the learning outcomes, Bloom’s taxonomy to define the assessment questions and the QR code to help managing large class size. The methodology has been applied in a case study regarding the technical drawing course of the BSc Engineering programme at the Faculty of Engineering in Italy. In general, the implementation of the new assessment, during the two academic years of analysis, has shown good results in terms of reduction of failures (7% in the first year and 3.9% in the second year), improvement of the weighted average mark (4.6%), reduction of the minimum mark obtained (8.1%), increase of the maximum mark obtained (3.1%) and time reduction of 48% to upload marks to the electronic register.

Keywords: assessment questions | Bloom’s taxonomy | engineering education | European Qualifications Framework (EQF) | technical drawing

Abstract: In recent years, bone fracture detection and classification has been a widely discussed topic and many researchers have proposed different methods to tackle this problem. Despite this, a universal approach able to classify all the fractures in the human body has not yet been defined. We aim to analyze and evaluate a selection of papers, chosen according to their representative approach, where the authors applied different deep learning techniques to classify bone fractures, in order to select the strengths of each of them and try to delineate a generalized strategy. Each study is summarized and evaluated using a radar graph with six values: area under the curve (AUC), test accuracy, sensitivity, specificity, dataset size and labelling reliability. Plus, we defined the key points which should be taken into account when trying to accomplish this purpose and we compared each study with our baseline. In recent years, deep learning and, in particular, the convolution neural network (CNN), has achieved results comparable to those of humans in bone fracture classification. Adopting a correct generalization, we are reasonably sure that a computer-aided diagnosis (CAD) system, correctly designed to assist doctors, would save a considerable amount of time and would limit the number of wrong diagnoses.

Keywords: Bone fracture | CAD system | Deep learning | Neural network | Orthopedics | X-ray

Abstract: Robot-assisted radical prostatectomy (RARP) has become a standardized practice in contemporary prostate cancer surgical procedures. Nowadays, the use of tailored surgical procedures in urologic surgery aims to maximize treatment efficacy while minimizing its impact on patient functions and health-related quality-of-life parameters. Augmented reality (AR) technology appears as a significant development in Image Guided Surgery (IGS) integrating surgical navigation with 3D virtual organ models registered on to the real patient’s anatomy. In particular, AR provides surgeons the ability to see through solid objects; as such, it has been exploited in different surgical specialties. In this paper, we present the development of a software system augmenting the spatial navigation of the surgical environment allowed by surgical robots. The application is able to visualize the 3D virtual model of the organ (prostate and kidneys) targeted by the surgical procedure, overlay it over its real counterpart, as captured by the endoscope camera, using of registration and tracking techniques in real time, and stream the augmentation to the surgeon.

Keywords: Augmented reality (AR) | Image Guided Surgery (IGS) | Minimally invasive surgery (MIS) | Robotic surgery

Abstract: This work proposes an innovative method for evaluating usersâ™ engagement, combining the User Engagement Scale (UES) questionnaire and a facial expression recognition (FER) system, active research topics of increasing interest in the humanâ"computer interaction domain (HCI). The subject of the study is a 3D simulator that reproduces a virtual FabLab in which users can approach and learn 3D modeling software and 3D printing. During the interaction with the virtual environment, a structured-light camera acquires the face of the participant in real-time, to catch its spontaneous reactions and compare them with the answers to the UES closed-ended questions. FER methods allow overcoming some intrinsic limits in the adoption of questioning methods, such as the non-sincerity of the interviewees and the lack of correspondence with facial expressions and body language. A convolutional neural network (CNN) has been trained on the Bosphorus database (DB) to perform expression recognition and the classification of the video frames in three classes of engagement (deactivation, average activation, and activation) according to the model of emotion developed by Russell. The results show that the two methodologies can be integrated to evaluate user engagement, to combine weighted answers and spontaneous reactions and to increase knowledge for the design of the new product or service.

Keywords: 3D simulator | CNN | Deep learning | Facial expression recognition | Human-computer interaction | User engagement scale | User-centered design

Abstract: Common sense usually considers the assessment of female human attractiveness to be subjective. Nevertheless, in the past decades, several studies and experiments showed that an objective component in beauty assessment exists and can be strictly related, even if it does not match, with proportions of features. Proportions can be studied through analysis of the face, which relies on landmarks, i.e., specific points on the facial surface, which are shared by everyone, and measurements between them. In this work, several measures have been gathered from studies in the literature considering datasets of beautiful women to build a set of measures that can be defined as suggestive of female attractiveness. The resulting set consists of 29 measures applied to a public dataset, the Bosphorus database, whose faces have been both analyzed by the developed methodology based on the expanded set of measures and judged by human observers. Results show that the set of chosen measures is significant in terms of attractiveness evaluation, confirming the key role of proportions in beauty assessment; furthermore, the sorting of identified measures has been performed to identify the most significant canons involved in the evaluation.

Keywords: 3D landmarks | Attractiveness | Face analysis | Face proportions | Features extraction

Abstract: As the potentials of technology grow, the embedding of IT advances in different fields and applications increases. A recent example is virtual reality and in particular the virtual product. The possibility of having a product in a virtual form allows creators and designers to efficiently manage the cycle of a product generation and evolution. The key advantage of the “virtual” is to have the product in advance, even in the conceptualization phase, with clear benefits in terms of consumptions of resources and, hence, sustainability. A potential customer could thus interact with a product-to-be and provide feedback about its look and feel, its usability, and, most of all, give an emotional response. In this context, the interaction between the virtual product and the future customer becomes a core point for the new approaches related to user-centred and user experience design, giving birth to a design methodology called “emotional design”. In particular, the study of facial expressions seems to be the more reliable and attractive aspect of it.

Keywords: 3D | Concept design | Emotional design | Facial expression recognition | PLM | Virtual reality

Abstract: Surgical interventions for jaw reconstruction require the design and the production of surgical guides that allow the surgeon to operate quickly and accurately. In some cases, the reconstruction is performed by inserting a prothesis, thus operating exclusively on the jaw, while in other cases the reconstruction is performed by withdrawing and inserting part of the fibula in place of the original jaw bone. This project aims to develop a procedure that allows 3D modeling of the surgical guides necessary for surgical intervention. The idea is to find a surgical guide archetype, a starting shape for the surgeon so that the cutting planes can be oriented without the surgical guide having to be redesigned from scratch for every single patient. The first step of the procedure is the segmentation, performed applying the thresholding operation on the images provided by magnetic resonance MR in order to identify the region of interest (ROI). The second step is the reconstruction of the 3D model, so that a mesh is obtained from 2D images. Subsequently the mesh is post-processed and the cutting plans along which the surgeon will intervene are defined.

Keywords: 3D modeling | 3D reconstruction | Maxillofacial surgery | Surgical guides

Abstract: This work proposes a method for recognizing the main 13 Facial Action Units and the 6 basic emotions. The methodologies rely on Differential Geometry to extract relevant discriminant features from the query faces, and on some linear quantities used as measures: Euclidean, geodesic, and angles between 17 automatically extracted soft-tissue landmarks. A thresholding system which evaluates local properties of connected regions, selected through tailored geometrical descriptors, supports the identification of the AUs. Then, a technique based on crisp logic allows the identification of the global expression. The three-dimensional context has been preferred due to its invariance to different lightening/make-up/camouflage conditions.

Keywords: Emotional design | Face expression recognition | Intelligent drive

Abstract: This work proposes a methodology to automatically diagnose and formalize prenatal cleft lip with representative key points and identify the type of defect (unilateral, bilateral, right, or left) in three-dimensional ultrasonography (3D US). Differential Geometry has been used as a framework for describing facial shapes and curvatures. Then, descriptors coming from this field are employed for identifying the typical key points of the defect and its dimensions. The descriptive accurateness of these descriptors has allowed us to automatically extract reference points, quantitative distances, labial profiles, and to provide information about facial asymmetry. Seventeen foetal faces, nine of healthy foetuses and eight with different types of cleft lips, have been obtained through a Voluson system and used for testing the algorithm. In case no defect is present, the algorithm detects thirteen standard facial soft-tissue landmarks. This would help ultrasonographists and future mothers in identifying the most salient points of the forthcoming baby. This algorithm has been designed to support practitioners in identifying and classifying cleft lips. The gained results have shown that differential geometry may be a valuable tool for describing faces and for diagnosis.

Keywords: 3D ultrasound | Cleft lip | Dysmorphisms | Landmarking | Syndrome diagnosis

Abstract: 3D face was recently investigated for various applications, including biometrics and diagnosis. Describing facial surface, i.e. how it bends and which kinds of patches is composed by, is the aim of studies in Face Analysis, whose ultimate goal is to identify which features could be extracted from three-dimensional faces depending on the application. In this study, we propose 54 novel geometrical descriptors for Face Analysis. They are generated by composing primary geometrical descriptors such as mean, Gaussian, principal curvatures, shape index, curvedness, and the coefficients of the fundamental forms. The new descriptors were mapped on 217 facial depth maps and analysed in terms of descriptiveness of facial shape and exploitability for localizing landmark points. Automatic landmark extraction stands as the final aim of this analysis. Results showed that the newly generated descriptors are suitable to 3D face description and to support landmark localization procedures.

Keywords: 3D Face | Face Analysis | Face Recognition | Geometry | Landmarks

Abstract: A 3D automatic facial expression recognition procedure is presented in this work. The method is based on point-by-point mapping of seventeen Differential Geometry descriptors onto the probe facial depth map, which is then partitioned into seventy-nine regions. Then, features such as mean, median, mode, volumes, histograms are computed for each region and for each descriptor, to reach a varied large set of parameters representing the query face. Each set of parameters, given by a geometrical descriptor, a region, and a feature, form a trio, whose featuring numerical values are compared with appropriate thresholds, set via experimentation in a previous phase by processing a limited portion of the public facial Bosphorus database. This allows the identification of the emotion-based expression of the query 3D face among the six basic ones (anger, disgust, fear, joy, sadness, surprise). The algorithm was tested on the Bosphorus database and is suitable for applications in security, marketing, medical. The three-dimensional context has been preferred due to its invariance to different lightening/make-up/camouflage conditions.

Keywords: 3D face | Differential geometry | Emotions | Face expression recognition (FER) | Facial expression recognition | Shape index

Abstract: Recent Face Analysis advances have focused the attention on studying and formalizing 3D facial shape. Landmarks, i.e. typical points of the face, are perfectly suited to the purpose, as their position on visage shape allows to build up a map of each human being’s appearance. This turns to be extremely useful for a large variety of fields and related applications. In particular, the forensic context is taken into consideration in this study. This work is intended as a survey of current research advances in forensic science involving 3D facial landmarks. In particular, by selecting recent scientific contributions in this field, a literature review is proposed for in-depth analyzing which landmarks are adopted, and how, in this discipline. The main outcome concerns the identification of a leading research branch, which is landmark-based facial reconstruction from skull. The choice of selecting 3D contributions is driven by the idea that the most innovative Face Analysis research trends work on three-dimensional data, such as depth maps and meshes, with three-dimensional software and tools. The third dimension improves the accurateness and is robust to colour and lightning variations.

Keywords: 3D face | Fiducial point | Forensic | Landmarks | Reconstruction

Abstract: Traditionally, the development of complex mechatronic products, such as products in aerospace or automotive domain, have employed a "document-based" Systems Engineering (SE) approach to perform the systems engineering activities. This approach is characterized by the generation of textual specifications and design documents that are used and exchanged between all project users. Today, innovative interdisciplinary product development requires a rethinking of current methods and IT solutions, employing an efficient Systems Engineering strategy. The goal is to move from a "documentbased" approach to a "model-based" approach that addresses all engineering disciplines. The "Model Based Systems Engineering (MBSE)" methodology is an approach that involves modeling for supporting system requirements definition and management, design, analysis, verification and validation activities. This approach provides a set of data and models that allows design teams to analyze the performances of the different product configurations in an early stage and to ensure product data traceability along the entire product lifecycle maintaining a structured relation between costumer requirements and all the product solution analyzed. At present a shared operative approached aimed at integrating MBSE in a Product Life Cycle Management scenario doesn't exist. For that reason, the paper outlines the key activities to deploy successfully a MBSE methodology, based on the Systems Modeling Language (SysML) within a PLM platform by the use of the Product Functional View.

Keywords: Model-Based Systems Engineering | Product Lifecycle Management | SysML | Systems engineering

Abstract: This work proposes a methodology that can be used to define a FEM simulation of the body welding process with the aim of evaluating compliant assembly deformations and spring-back, considering the effect of material plasticity, in order to improve the results of variational analysis methods, which so far have been based on a linear elastic material model. With reference to the automotive field, the simulation considers the effects of fixturing and resistance spot welding applied to sheet metal parts subjected to dimensional and geometrical tolerances.

Keywords: Compliant assembly | FEM | Plasticity | Resistance spot welding | Variational analysis

Abstract: The next generation of tyre sensors will be bonded directly onto the inner liner (IL) in order to measure important parameters such as strain, vehicle load, contact pressure, the tyre-road friction coefficient or wear. Sensor packages (SP) have a sensor node, which is bonded and kept in position by a specifically designed rubber housing (RH). Since the measurements they provide to the car control unit are used to improve the active or passive safety of vehicles, these packages can be considered critical safety components that should be dimensioned carefully. A tyre analysis, whether statical or dynamical, in which the complete structure is considered, under any load, inflating pressure or temperature working condition is mainly oriented towards defining the tyre product. The insertion of an SP inside such a complex tyre model, with the purpose of only analysing its behaviour, would be too time consuming considering the strong nonlinear behaviour of the tyre model. Therefore, this work presents a method that can be used to define a computationally lightweight finite element method (FEM) simulation, which is able to recreate the working conditions to which an SP is subjected. The basic idea behind this method is to separate the analysis of the SP from the structural tyre analyses; the latter is only run once, independently. The first task is to impose the deformed shape on a simplified model of the tyre with a bonded SP. All the deformation states that occur during rolling are computed in a static FEM simulation. The second task is to apply the inertial forces that act on the SP, whether computed or measured directly on the tyre, as external loads. These tasks are implemented in user-defined routines that are executed by the FEM solver. The method permits the stress concentration inside the RH material volume to be identified, at any angular position of the wheel. This information is then used, during the design process, to identify the most suitable geometry to level out the stress distribution. The resulting shape can be tested under different boundary conditions, by substituting the corresponding data arrays, but using the same FEM model. Since the deformed shapes and inertial forces are stored as simple text matrices (which are also used to form a test library), they can be easily interchanged in a flexible way. This more extended design process can reduce the costs of prototyping moulds. The proposed methodology has been developed and tested for the Pirelli Cyber TM Tyre project.

Keywords: FEM | Rubber house | Tyre sensor

Abstract: The variational analysis of a compliant assembly is influenced to a great extent by the plastic deformations of the parts, which are caused by the fixturing and the application of resistance spot welding to the flanges, which are mismatching because of tolerance effects. Spring-back of an assembly results to be very different when evaluated with an elastic material model and with a plastic model. The aim of this paper is to define the finite element analysis (FEA) methods that are necessary to transfer the complex interaction of the complete resistance spot welding process, which is best described by a coupled thermoelectrical-mechanical simulation with 3D solid elements, to a shell model. The entire welding process is simulated by considering the following steps: fixture closure on the parts, weldgun closure on the flanges, heating and cooling of the weld spots, release and measuring of the resulting assembly. The constraints corresponding to the datum point scheme are defined on the shell partitions, and a mesh offset is applied to the welding flange in order to simulate the geometry mismatch caused by the effects of the dimensional and geometrical tolerances. The methods developed to recreate the welding process conditions on a shell model are implemented in FEA runtime routines. The temperature distribution, previously exported from 3D thermal simulations, is loaded and imposed on the shell nodes of the welding partition during the heating and cooling phases, in order to make the material plastic and reduce the elastic energy available for spring-back. The weld caps that act against the part's flanges are defined with analytical rigid surfaces in order to avoid the necessity of explicitly modelling them in the FEA software. The contact between the welding flanges is redefined to lock the nodes that surpass the melting temperature. The methods were tested on the shell model of a butt joint. The thus obtained deformations were in good agreement with the results of the complete 3D thermoelectrical-mechanical simulation. This result makes it possible to calculate deformations with a plastic model in a reasonable time and use them as input data for an improved variational analysis. © 2013 Springer-Verlag London.

Keywords: Compliant assembly | FEM | Plasticity | Quality | Resistance spot welding | Shell model | Variational analysis

Abstract: Recently, 3D landmark extraction has been widely researched and experimented in medical field, for both corrective and aesthetic purposes. Automation of these procedures on three-dimensional face renderings is something desirable for the specialists who work in this field. In this work we propose a new method for accurate landmark localization on facial scans. The method relies on geometrical descriptors, such as curvatures and Shape Index, for computing candidate and initial points, and on a statistical model based on Procrustes Analysis and Principal Component Analysis, which is fitted to candidate points, for extracting the final landmarks. The elaborated method is independent on face pose. © 2012 Elsevier Ireland Ltd.

Keywords: 3D face | Differential Geometry | Landmark extraction | PCA | Procrustes Analysis

Abstract: The variational analysis of compliant assemblies is mainly based on linear elastic models. Some guidelines have been defined to integrate material plasticity into a tolerance analysis model in order to improve its results when considering the resistance spot welding (RSW) process. A finite element model that simulates the body-in-white and RSW processes has been applied to butt and slip joints, with parts subjected to dimensional and geometrical tolerances that cause gap mismatching condition and loading interference on fixtures. The dimensional quality of assemblies is affected by plasticization near the welding spot, at the base of welded flanges and near the locators. The springback evidenced relative rotation of parts. © Springer-Verlag London Limited 2011.

Keywords: Compliant assembly | FEM | Quality | Resistance spot welding | Tolerance analysis

Abstract: The present globalized market is forcing many companies to invest in new strategies and tools for supporting knowledge management. This aspect is becoming a key factor in the industrial competitiveness for the presence of extended enterprises that normally deal with huge data exchange and share processes. This scenario is due to the presence of partners geographically distributed over the entire globe, that participate in different steps of the product lifecycle (product development, maintenance and recycling). At present, Product Lifecycle Management (PLM) seems to be the appropriate solution to support enterprises in this complex scenario, even though a real standardized approach for the implementation of knowledge sharing and management tools does not exist today. For this reason, the aim of this paper is to develop a knowledge management operative methodology able to support the formalization and the reuse of the enterprise expertise acquired while working on previous products. By focusing on consumer packaged goods enterprises and on the concept development phase (which is one of the most knowledge intensive phases of the whole product lifecycle), this research work has developed a new systematic methodology to support knowledge codification and knowledge management operations. The new methodology integrates the Quality Function Deployment (QFD) and the Teoriya Resheniya Izobreatatelskikh Zadatch (TRIZ). Also, a case study on the problem of waste disposal has been conducted to validate the proposed methodology. © 2011 Elsevier Ltd. All rights reserved.

Keywords: Knowledge sharing | PLM | QFD | TRIZ | Waste disposal

Abstract: This paper presents a multi-physic modeling of an electromechanical energy scavenging device able to supply energy inside car tires for wireless sensors. A permanent magnet, connected to the inner liner of a tire, is accelerated along a guide by the tire deformation during car motion; by interacting with coils it generates a power which is conditioned by a proper electronic interfaced to an external load. The original approach implemented in this kind of device is the nonlinear dynamic properties designed and controlled: adaptive resonance in function of car velocity is optimized for increasing its global efficiency. The energy conversion process takes into account the simulation of different phenomena such as: non linear dynamic and adaptive resonant behavior of the seismic mass, electromagnetic and magneto-static coupling between moving mass and coils, transfer of the generated power to an external load by means of a nonlinear circuit interface. An integrated model of the cascaded energy steps is developed inside the Simulink/Stateflow environment. A good agreement is found in the comparison between theoretical model and experiments conducted on prototypes produced by means of drawings directly obtained from 3D CAD models. To compare these results to other energy harvesting devices found in Literature, the same device adapted with symmetric configuration is derived. Empirical formulas to measure efficiency are evaluated for this device and compared with Literature results. The accurate modeling of the energy conversion device is a breakthrough in the modeling of these kinds of devices and allows to reach interesting power/volume ratios: small dimensions (about one cubic centimeter) and relatively high power output (more than one milliwatt). © 2011 SAE International.

Abstract: This paper presents a multi-physic modeling of an electromechanical energy scavenging device able to supply energy inside car tires for wireless sensors. A permanent magnet, connected to the inner liner of a tire, is accelerated along a guide by the tire deformation during car motion; by interacting with coils it generates a power which is conditioned by a proper electronic interfaced to an external load. The original approach implemented in this kind of device is the nonlinear dynamic properties designed and controlled: adaptive resonance in function of car velocity is optimized for increasing its global efficiency. The energy conversion process takes into account the simulation of different phenomena such as: non linear dynamic and adaptive resonant behavior of the seismic mass, electromagnetic and magneto-static coupling between moving mass and coils, transfer of the generated power to an external load by means of a nonlinear circuit interface. An integrated model of the cascaded energy steps is developed inside the Simulink/Stateflow environment. A good agreement is found in the comparison between theoretical model and experiments conducted on prototypes produced by means of drawings directly obtained from 3D CAD models. To compare these results to other energy harvesting devices found in Literature, the same device adapted with symmetric configuration is derived. Empirical formulas to measure efficiency are evaluated for this device and compared with Literature results. The accurate modeling of the energy conversion device is a breakthrough in the modeling of these kinds of devices and allows to reach interesting power/volume ratios: small dimensions (about one cubic centimeter) and relatively high power output (more than one milliwatt). Copyright © 2011 SAE International.

Abstract: This paper presents a very compact electro-mechanical wideband energy harvester optimized for tire applications. The energy conversion process of the device takes into account the simulation of different phenomena like: non linear dynamic and adaptive resonant behavior of the seismic mass, electromagnetic and magneto-static coupling between floating magnetic mass and coils, transfer of the generated power to an external load by means of a nonlinear circuit interface. The paper is focused on the pneumatic effects of the floating magnet sliding into a calibrated guide. A convenient choice of clearance between moving and fixed parts can be used to create an effective air brake preventing or softening shocks with end stops and to modify system dynamic. A block-oriented Simulink®, experimentally validated, model has been realized to predict scavenger device performance and to optimize design parameters. Equivalent linearized stiffness and damping factors due to pneumatic effects have been modeled in the lumped parameters system to get a simplified model and to formalize relations with the geometrical characteristics. Analysis of the effect of several nonlinearities at different vehicle speed have been performed.

Keywords: Adaptive resonance | Electro-mechanical device | Energy scavenger

Abstract: This paper presents a multi-physic modeling of an electromechanical energy scavenging device. A permanent magnet, connected to the inner liner of a tyre, is accelerated along a guide by the tyre deformation during car motion; by interacting with coils it generates a power which is conditioned by a proper electronic interfaced to an external load. The energy conversion process takes into account the simulation of different phenomena like: dynamic behavior of the seismic mass, electromagnetic coupling between moving mass and coils, transfer of the generated power to an external load by means of a nonlinear circuit interface. An integrated model of the cascaded energy steps is developed inside the Simulink environment. A good agreement is found in the comparison between theoretical model and experiments. The accurate modeling of the energy conversion device is a breakthrough in the modeling of these kinds of devices and allows to reach interesting power/volume ratios: small dimensions (about one cubic centimeter) and relatively high power output (more than one milliwatt). © 2006 IEEE.

Keywords: Adaptive resonance | electro-mechanical device | energy scavenger

Abstract: This article compares most of the three-dimensional (3D) morphometric methods currently proposed by the technical literature to evaluate their morphological informative value, while applying them to a case study of five patients affected by the malocclusion pathology. The compared methods are: conventional cephalometric analysis (CCA), generalised Procrustes superimposition (GPS) with principal-components analysis (PCA), thin-plate spline analysis (TPS), multisectional spline (MS) and clearance vector mapping (CVM). The results show that MS provides more reliable and useful diagnostic information. © 2008 British Association of Plastic, Reconstructive and Aesthetic Surgeons.

Keywords: 3D Scanner | Facial Morphology | Shape analysis

Abstract: The paper discusses a gearbox design method based on an optimization algorithm coupled to a full integrated tool to draw 3D virtual models, in order to verify both functionality and design. The aim of this activity is to explain how the state of the art of the gear design may be implemented through an optimization software for the geometrical parameters selection of helical gears of a manual transmission, starting from torque and speed time-histories, the required set of gear ratios and the material properties. This approach can be useful in order to use either the experimental acquisitions or the simulation results to verify or design all of the single gear pairs that compose a gearbox. Genetic algorithm methods are applied to solve the optimization problems of gears design, due to their capabilities of managing objective functions discontinuous, non-differentiable, stochastic, or highly non-linear. The final design tool, implemented in Matlab® environment, is based on the calculation of load capacity of helical gears, including the computation of tooth bending strength, of surface durability (pitting) and the estimation of service life under variable load, as suggested by International Standards. An automated macro procedure for Solidworks® interacts with the Matlab® environment to get the dimensional parameters of each gear and produces the models of each gear and their assembly. Copyright © 2010 SAE International.

Abstract: To obtain the best surgical results in orthognathic surgery, treatment planning and the evaluation of results should be performed. In these operations it is necessary to provide to the physicians powerful tools able to underline the behaviour of soft tissue. For this reason, considering the improvements provided by the use of 3D scanners, as photogrammetry, in the medical diagnosis this paper proposes a methodology for analysing the facial morphology working with geometrical features. The methodology has been tested over patients affected by malocclusion, in order to analyse the reliability and efficiency of the provided diagnostic results.

Keywords: 3D scanner | Facial morphology | Shape analysis | Soft tissue shifts