57 research outputs found
Waste Material Recycling in the Circular Economy
This book highlights current challenges and developments in waste material recycling in the framework of a circular economy. The increase in the standard of living has resulted in the large consumption of several materials, mainly polymers. Therefore the problem of waste recycling, specifically polymer recycling, in an environmentally friendly way is more urgent than ever. Nowadays, more specialized recycling methods are required to manage a wide variety of wastes. Over fourteen chapters in three sections, this book addresses such topics as chemical recycling techniques, recycling of polyethylene, denim production and recycling, valorization of waste materials, urban mining, the circular economy, and much more
Advances in Structural Mechanics Modeled with FEM
It is well known that many structural and physical problems cannot be solved by analytical approaches. These problems require the development of numerical methods to get approximate but accurate solutions. The minite element method (FEM) represents one of the most typical methodologies that can be used to achieve this aim, due to its simple implementation, easy adaptability, and very good accuracy. For these reasons, the FEM is a widespread technique which is employed in many engineering fields, such as civil, mechanical, and aerospace engineering. The large-scale deployment of powerful computers and the consequent recent improvement of the computational resources have provided the tools to develop numerical approaches that are able to solve more complex structural systems characterized by peculiar mechanical configurations. Laminated or multi-phase composites, structures made of innovative materials, and nanostructures are just some examples of applications that are commonly and accurately solved by the FEM. Analogously, the same numerical approaches can be employed to validate the results of experimental tests. The main aim of this Special Issue is to collect numerical investigations focused on the use of the finite element metho
Towards markerless orthopaedic navigation with intuitive Optical See-through Head-mounted displays
The potential of image-guided orthopaedic navigation to improve surgical outcomes has been well-recognised during the last two decades. According to the tracked pose of target bone, the anatomical information and preoperative plans are updated and displayed to surgeons, so that they can follow the guidance to reach the goal with higher accuracy, efficiency and reproducibility. Despite their success, current orthopaedic navigation systems have two main limitations: for target tracking, artificial markers have to be drilled into the bone and calibrated manually to the bone, which introduces the risk of additional harm to patients and increases operating complexity; for guidance visualisation, surgeons have to shift their attention from the patient to an external 2D monitor, which is disruptive and can be mentally stressful.
Motivated by these limitations, this thesis explores the development of an intuitive, compact and reliable navigation system for orthopaedic surgery. To this end, conventional marker-based tracking is replaced by a novel markerless tracking algorithm, and the 2D display is replaced by a 3D holographic Optical see-through (OST) Head-mounted display (HMD) precisely calibrated to a user's perspective.
Our markerless tracking, facilitated by a commercial RGBD camera, is achieved through deep learning-based bone segmentation followed by real-time pose registration. For robust segmentation, a new network is designed and efficiently augmented by a synthetic dataset. Our segmentation network outperforms the state-of-the-art regarding occlusion-robustness, device-agnostic behaviour, and target generalisability. For reliable pose registration, a novel Bounded Iterative Closest Point (BICP) workflow is proposed. The improved markerless tracking can achieve a clinically acceptable error of 0.95 deg and 2.17 mm according to a phantom test.
OST displays allow ubiquitous enrichment of perceived real world with contextually blended virtual aids through semi-transparent glasses. They have been recognised as a suitable visual tool for surgical assistance, since they do not hinder the surgeon's natural eyesight and require no attention shift or perspective conversion. The OST calibration is crucial to ensure locational-coherent surgical guidance.
Current calibration methods are either human error-prone or hardly applicable to commercial devices. To this end, we propose an offline camera-based calibration method that is highly accurate yet easy to implement in commercial products, and an online alignment-based refinement that is user-centric and robust against user error. The proposed methods are proven to be superior to other similar State-of-
the-art (SOTA)s regarding calibration convenience and display accuracy.
Motivated by the ambition to develop the world's first markerless OST navigation system, we integrated the developed markerless tracking and calibration scheme into a complete navigation workflow designed for femur drilling tasks during knee replacement surgery. We verify the usability of our designed OST system with an experienced orthopaedic surgeon by a cadaver study. Our test validates the potential of the proposed markerless navigation system for surgical assistance, although further improvement is required for clinical acceptance.Open Acces
ROBOTIC TECHNOLOGIES FOR MINIMIZING CREW MAINTENANCE REQUIREMENTS IN SPACE HABITATS
Gemstone Team ASTROThe International Space Station (ISS) is crewed continuously by astronauts conducting
scientifc research in microgravity. However, their work is not limited to scientifc research
alone; in fact, logistics, maintenance, and repair tasks on the ISS require more than 80% of
available crew time, severely limiting opportunities for performing scientifc experiments
and technological development. NASA is planning a new project known as Gateway (also
referred to as the Lunar Orbital Platform-Gateway). This station will orbit the Moon and be
uncrewed for 11 months per year. Astronauts will only be present in the outpost for a limited
period of time and will not always be available for continuous repairs and maintenance, as
is required for Gateway to operate. Therefore, robotic system(s) are necessary to regularly
accomplish these tasks both in the absence and presence of astronauts. Throughout this
project, Team ASTRO (Assessment of Space Technologies for Robotic Operations) explored
the feasibility of integrating dexterous robotic systems in space habitat architectures to
perform routine and contingency operational and maintenance tasks. Ultimately, this allows
for astronauts, when present, to focus on exploration and scientifc discoveries. The team
conducted this research through three approaches: Gateway component analog taskboard development and end e˙ector assessment, Cargo Transfer Bag (CTB) manipulation and logistics, and AprilTag situational awareness simulation development. Based on analyses and experimental results gained from this research, the team found that robotic systems are feasible alternatives for space habitat operation. Team ASTRO also determined that AprilTags can be used for optimization of the Gateway design to facilitate uncrewed operations and robotic servicing to improve crew productivity when present
Design and Development of ReMoVES Platform for Motion and Cognitive Rehabilitation
Exergames have recently gained popularity and scientific reliability in the field of assistive computing technology for human well-being. The ReMoVES platform, developed by the author, provides motor and cognitive exergames to be performed by elderly or disabled people, in conjunction with traditional rehabilitation.
Data acquisition during the exercise takes place through Microsoft Kinect, Leap Motion and touchscreen monitor. The therapist is provided with feedback on patients' activity over time in order to assess their weakness and correct inaccurate movement attitudes.
This work describes the technical characteristics of the ReMoVES platform, designed to be used by multiple locations such as rehabilitation centers or the patient's home, while providing a centralized data collection server. The system includes 15 exergames, developed from scratch by the author, with the aim of promoting motor and cognitive activity through patient entertainment.
The ReMoVES platform differs from similar solutions for the automatic data processing features in support of the therapist. Three methods are presented: based on classic data analysis, on Support Vector Machine classification, and finally on Recurrent Neural Networks. The results describe how it is possible to discern patient gaming sessions with adequate performance from those with incorrect movements with an accuracy of up to 92%.
The system has been used with real patients and a data database is made available to the scientific community. The aim is to encourage the dissemination of such data to lay the foundations for a comparison between similar studies
ME-EM 2019-20 Annual Report
Table of Contents Element 1 Element 2 Element 3 Element 4 Enrollment & Degrees Graduates Department Alumni Donorshttps://digitalcommons.mtu.edu/mechanical-annualreports/1015/thumbnail.jp
- …