Artimate: an articulatory animation framework for audiovisual speech synthesis

We present a modular framework for articulatory animation synthesis using speech motion capture data obtained with electromagnetic articulography (EMA). Adapting a skeletal animation approach, the articulatory motion data is applied to a three-dimensional (3D) model of the vocal tract, creating a portable resource that can be integrated in an audiovisual (AV) speech synthesis platform to provide realistic animation of the tongue and teeth for a virtual character. The framework also provides an interface to articulatory animation synthesis, as well as an example application to illustrate its use with a 3D game engine. We rely on cross-platform, open-source software and open standards to provide a lightweight, accessible, and portable workflow.Comment: Workshop on Innovation and Applications in Speech Technology (2012

An IoT-Based Framework of Webvr Visualization for Medical Big Data in Connected Health

Recently, telemedicine has been widely applied in remote diagnosis, treatment and counseling, where the Internet of Things (IoT) technology plays an important role. In the process of telemedicine, data are collected from remote medical equipment, such as CT machine and MRI machine, and then transmitted and reconstructed locally in three-dimensions. Due to the large amount of data to be transmitted in the reconstructed model and the small storage capacity, data need to be compressed progressively before transmission. On this basis, we proposed a lightweight progressive transmission algorithm based on large data visualization in telemedicine to improve transmission efficiency and achieve lossless transmission of original data. Moreover, a novel four-layer system architecture based on IoT has been introduced, including the sensing layer, analysis layer, network layer and application layer. In this way, the three-dimensional reconstructed data at the local end is compressed and transmitted to the remote end, and then visualized at the remote end to show reconstructed 3D models. Thus, it is conducive to doctors in remote real-time diagnosis and treatment, and then realize the data processing and transmission between doctors, patients and medical equipment

Biomechanical importance of proximal human femur morphology and mechanics in orthopaedic purposes

Bone morphology is essential in orthopedic surgery to perform precise preoperative planning and surgery as well as to appropriately design optimal medical implants. In this study we provided a database of surgically important morphological parameters of proximal human femur for orthopedic and biomedical research purposes (study 1), indicated accuracy of the 3D reconstructed images in comparison with the optical 3D scan of real human femur (study 2), and reported the accuracy and reliability of the developed image-based finite element model in comparison with the experimental results (study 3)

Intelligent visual media processing: when graphics meets vision

The computer graphics and computer vision communities have been working closely together in recent years, and a variety of algorithms and applications have been developed to analyze and manipulate the visual media around us. There are three major driving forces behind this phenomenon: i) the availability of big data from the Internet has created a demand for dealing with the ever increasing, vast amount of resources; ii) powerful processing tools, such as deep neural networks, provide e�ective ways for learning how to deal with heterogeneous visual data; iii) new data capture devices, such as the Kinect, bridge between algorithms for 2D image understanding and 3D model analysis. These driving forces have emerged only recently, and we believe that the computer graphics and computer vision communities are still in the beginning of their honeymoon phase. In this work we survey recent research on how computer vision techniques bene�t computer graphics techniques and vice versa, and cover research on analysis, manipulation, synthesis, and interaction. We also discuss existing problems and suggest possible further research directions

Robotic Ultrasound Imaging: State-of-the-Art and Future Perspectives

Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques.Comment: Accepted by Medical Image Analysi

Quasi-Articulation of a Continuous Robotic Manipulator Enabled by Stiffness-Switching Origami Joints

Soft robots possess a nearly infinite number of kinematic degrees of freedom due to the compliance of their underlying materials which enables them to accomplish incredible feats of movement and adaptation. However, their severely underactuated structures limit their controllability and the degree of precision that can be achieved. As demonstrated by the octopus when fetching prey, it is possible to achieve precise movement in an otherwise “soft” arm by stiffening select sections of the arm while keeping other sections flexible, in effect generating a quasi-articulated structure and reducing the degrees of freedom from practically infinite to a finite number of angles. In this study, we use the bistable generalized Kresling origami to emulate this strategy. Both experimental and computational modeling procedures are conducted to evaluate the bending mechanics of the structure at each of its two stable states (extended and contracted). As the model accurately predicts the major trends observed in experiments, it is used to perform a parametric study on the bending stiffness ratio, defined as the ratio of bending stiffness at the extended state to the bending stiffness at the contracted state. Using the results of the parametric study, we discover that the Kresling design which maximizes the bending stiffness ratio is that possessing the greatest angle ratio λ, the lowest contracted height Lc, and the largest number of sides of the base polygon n, enabling the transformation of the structure from rigid to flexible. To complete the study, we use the optimal Kresling design in the fabrication of a tendon-driven reconfigurable manipulator composed of three Kresling modules. We find that by reconfiguring the Kresling module states (rigid or flexible), the manipulator can effectively transform into 2m different configurations where m corresponds to the number of modules. Through this reconfiguration, the manipulator can generate a quasi-articulated structure which reduces its effective degrees of freedom and enables linkage-like motion. Unlike other methods of stiffness modulation, this solution reduces system complexity by using a bistable structure as both the body of the robot and as a mechanism of stiffness-switching. The structure’s primary reliance on geometry for its properties makes it a scalable solution, which is appealing for minimally invasive surgical applications where both precision and adaptability are vital. The manipulator may also be used as an inspection or exploration robot to access areas that may be inaccessible to humans or rigid robots

Task-based Augmented Contour Trees with Fibonacci Heaps

This paper presents a new algorithm for the fast, shared memory, multi-core computation of augmented contour trees on triangulations. In contrast to most existing parallel algorithms our technique computes augmented trees, enabling the full extent of contour tree based applications including data segmentation. Our approach completely revisits the traditional, sequential contour tree algorithm to re-formulate all the steps of the computation as a set of independent local tasks. This includes a new computation procedure based on Fibonacci heaps for the join and split trees, two intermediate data structures used to compute the contour tree, whose constructions are efficiently carried out concurrently thanks to the dynamic scheduling of task parallelism. We also introduce a new parallel algorithm for the combination of these two trees into the output global contour tree. Overall, this results in superior time performance in practice, both in sequential and in parallel thanks to the OpenMP task runtime. We report performance numbers that compare our approach to reference sequential and multi-threaded implementations for the computation of augmented merge and contour trees. These experiments demonstrate the run-time efficiency of our approach and its scalability on common workstations. We demonstrate the utility of our approach in data segmentation applications

Regional diversity in the murine cortical vascular network is revealed by synchrotron X-ray tomography and is amplified with age

Cortical bone is permeated by a system of pores, occupied by the blood supply and osteocytes. With ageing, bone mass reduction and disruption of the microstructure are associated with reduced vascular supply. Insight into the regulation of the blood supply to the bone could enhance the understanding of bone strength determinants and fracture healing. Using synchrotron radiation-based computed tomography, the distribution of vascular canals and osteocyte lacunae was assessed in murine cortical bone and the influence of age on these parameters was investigated. The tibiofibular junction from 15-week- and 10-month-old female C57BL/6J mice were imaged post-mortem. Vascular canals and three-dimensional spatial relationships between osteocyte lacunae and bone surfaces were computed for both age groups. At 15 weeks, the posterior region of the tibiofibular junction had a higher vascular canal volume density than the anterior, lateral and medial regions. Intracortical vascular networks in anterior and posterior regions were also different, with connectedness in the posterior higher than the anterior at 15 weeks. By 10 months, cortices were thinner, with cortical area fraction and vascular density reduced, but only in the posterior cortex. This provided the first evidence of age-related effects on murine bone porosity due to the location of the intracortical vasculature. Targeting the vasculature to modulate bone porosity could provide an effective way to treat degenerative bone diseases, such as osteoporosis

Low-Cost Sensors and Biological Signals

Many sensors are currently available at prices lower than USD 100 and cover a wide range of biological signals: motion, muscle activity, heart rate, etc. Such low-cost sensors have metrological features allowing them to be used in everyday life and clinical applications, where gold-standard material is both too expensive and time-consuming to be used. The selected papers present current applications of low-cost sensors in domains such as physiotherapy, rehabilitation, and affective technologies. The results cover various aspects of low-cost sensor technology from hardware design to software optimization