The Relationship of Somatosensory Perception and Fine-Force Control in the Adult Human Orofacial System

The orofacial area stands apart from other body systems in that it possesses a unique performance anatomy whereby oral musculature inserts directly into the underlying cutaneous skin, allowing for the generation of complex three-dimensional deformations of the orofacial system. This anatomical substrate provides for the tight temporal synchrony between self-generated cutaneous somatosensation and oromotor control during functional behaviors in this region and provides the necessary feedback needed to learn and maintain skilled orofacial behaviors. The Directions into Velocity of Articulators (DIVA) model highlights the importance of the bidirectional relationship between sensation and production in the orofacial region in children learning speech. This relationship has not been as well-established in the adult orofacial system. The purpose of this observational study was to begin assessing the perception-action relationship in healthy adults and to describe how this relationship may be altered as a function of healthy aging. This study was designed to determine the correspondence between orofacial cutaneous perception using vibrotactile detection thresholds (VDT) and low-level static and dynamic force control tasks in three representative age cohorts. Correlational relationships among measures of somatosensory capacity and low-level skilled orofacial force control were determined for 60 adults (19-84 years). Significant correlational relationships were identified using non-parametric Spearman’s correlations with an alpha at 0.1 between the 5 Hz test probe and several 0.5 N low-level force control assessments in the static and slow ramp-and-hold condition. These findings indicate that as vibrotactile detection thresholds increase (labial sensation decreases), ability to maintain a low-level force endpoint decreases. Group data was analyzed using non-parametric Kruskal-Wallis tests and identified significant differences between the 5 Hz test frequency probe and various 0.5 N skilled force assessments for group variables such as age, pure tone hearing assessments, sex, speech usage and smoking history. Future studies will begin the processing of modeling this complex multivariate relationship in healthy individuals before moving to a disordered population

The establishment of soft tissue thicknesses and profiles for reconstruction of the adult male Zulu face

A thesis submitted to the Faculty of Dentistry, University of the Witwatersrand, Johannesburg, for the Degree of Doctor of Philosophy. 1993Three-dimensional forensic facial reconstruction involves the building up in clay of the soft tissues of the human face onto an unidentified skull to suggest the identity of its owner. Early researchers physically punctured the facial tissues of cadavers at known anthropological to measure their depth. Later workers used radiography, ultrasonography and magnetic resonance imaging for collecting both depth and surface data on the head and face.GR 201

Models and Analysis of Vocal Emissions for Biomedical Applications

The Models and Analysis of Vocal Emissions with Biomedical Applications (MAVEBA) workshop came into being in 1999 from the particularly felt need of sharing know-how, objectives and results between areas that until then seemed quite distinct such as bioengineering, medicine and singing. MAVEBA deals with all aspects concerning the study of the human voice with applications ranging from the neonate to the adult and elderly. Over the years the initial issues have grown and spread also in other aspects of research such as occupational voice disorders, neurology, rehabilitation, image and video analysis. MAVEBA takes place every two years always in Firenze, Italy

CT Scanning

Since its introduction in 1972, X-ray computed tomography (CT) has evolved into an essential diagnostic imaging tool for a continually increasing variety of clinical applications. The goal of this book was not simply to summarize currently available CT imaging techniques but also to provide clinical perspectives, advances in hybrid technologies, new applications other than medicine and an outlook on future developments. Major experts in this growing field contributed to this book, which is geared to radiologists, orthopedic surgeons, engineers, and clinical and basic researchers. We believe that CT scanning is an effective and essential tools in treatment planning, basic understanding of physiology, and and tackling the ever-increasing challenge of diagnosis in our society

Progress Report No. 14

Progress report of the Biomedical Computer Laboratory, covering period 1 July 1977 to 30 June 1978

Computer aided stress analysis of the femur with prosthetic hip stem utilizing computed tomography

A computer aided design and analysis method, utilizing computed tomography (CT) is developed, which together with a finite element program determines the stress and deformation patterns in the femur with hip prosthesis. The CT scan data file provides the geometry and the material parameters for the generated finite element model. The three-dimensional finite element model of the femur with hip prosthesis is automatically generated from the CT data file by a preprocessing procedure. The preprocessor includes a CT image display, edge detector, nodes generation, prosthesis simulator, mesh generator and model display. The loading conditions applied on the finite element model are determined from existing gait analysis including joint force and muscle force. Formatted input data for ANSYS (Swanson Analysis Systems Inc.) finite element program is generated by the preprocessor. In this research, the influence on the stress pattern of different prosthetic materials and fixation, such as cobalt-chromium alloy or titanium alloy prosthesis, also cemented or porous-coated prosthesis are studied. A comparison of the stress patterns for the three different femora is made and a radiographic follow-up study in two cases is carried out at 14 months and 12 months postoperation for analyzing the bone remodeling process. As a result of the calculated stress patterns in the femur with prosthesis, it is found that the cobalt-chromium alloy prosthesis unloads the calcar cortical bone and the titanium alloy prosthesis decreases the stress within the prosthetic stem except for the proximal side. The highest calculated stress is approximately 12% of the fatigue limit for cobalt-chromium alloy prosthesis, and approximately 4% for the titanium alloy prosthesis. Comparing the porous coating model with the cemented model, the porous coating model leads to decreased bone stresses, reduced stress concentrations in bone surrounding the prosthesis and more uniformly distributed stress to the surrounding bone tissue. For the effect of stiffness and Poisson\u27s ratio of the porous coating layer, lower elastic modulus and Poisson\u27s ratio will reduce the interface stress between cancellous bone and the porous coating layer. The average stress of the fractured femur with prosthesis is approximately twice the amount of the femur with prosthesis in the proximal and distal side of the prosthetic stem. Furthermore the average stress of the male femur with prosthesis is about 4% lower than the female femur with prosthesis. In regards to stress changes in the postoperative femur, the bone remodeling results indicate that bone resorption of the cortex around the proximal prosthesis would increase the stress in the proximal prosthetic stem and femoral surface slightly while decreasing the stress of the midregion. Bone hypertrophy around the distal prosthesis would decrease the stress up to 35% in the distal prosthetic stem and femoral surface

Spinal modelling to investigate postural loading and stability

Numerous mathematical models have been developed to investigate the high incidence of low back pain associated with lifting activities. These mainly consider the muscle forces required to support the spine, and few have considered the additional role of curvature. One previous model which represented the spine as an arch (Aspden 1987) indicated the curvature to have a significant effect on both loading and stability of the spine. However this model included collective loading patterns for body weight and muscle forces, and only partial representation of the spine. On the basis that the level of anatomic detail of a model affects the accuracy of its predictions (McGill and Norman, 1987), this thesis describes the development of a model which provides greater detail for investigating spinal stability in the sagittal plane. The curvature of the whole spine, a distributed loading pattern for body weight, and the activity of individual spinal muscle groups have been considered. Comparison with the previous arch model has shown these to be necessary features for determining the loading and stability associated with a given posture. In particular, application of individual muscle forces provide greater control of stability at each vertebral level. By considering the force requirements of the individual muscle groups and the consequent loads at each intervertebral joint, possible areas of tissue over load can be identified

Data-Driven Representation Learning in Multimodal Feature Fusion

abstract: Modern machine learning systems leverage data and features from multiple modalities to gain more predictive power. In most scenarios, the modalities are vastly different and the acquired data are heterogeneous in nature. Consequently, building highly effective fusion algorithms is at the core to achieve improved model robustness and inferencing performance. This dissertation focuses on the representation learning approaches as the fusion strategy. Specifically, the objective is to learn the shared latent representation which jointly exploit the structural information encoded in all modalities, such that a straightforward learning model can be adopted to obtain the prediction. We first consider sensor fusion, a typical multimodal fusion problem critical to building a pervasive computing platform. A systematic fusion technique is described to support both multiple sensors and descriptors for activity recognition. Targeted to learn the optimal combination of kernels, Multiple Kernel Learning (MKL) algorithms have been successfully applied to numerous fusion problems in computer vision etc. Utilizing the MKL formulation, next we describe an auto-context algorithm for learning image context via the fusion with low-level descriptors. Furthermore, a principled fusion algorithm using deep learning to optimize kernel machines is developed. By bridging deep architectures with kernel optimization, this approach leverages the benefits of both paradigms and is applied to a wide variety of fusion problems. In many real-world applications, the modalities exhibit highly specific data structures, such as time sequences and graphs, and consequently, special design of the learning architecture is needed. In order to improve the temporal modeling for multivariate sequences, we developed two architectures centered around attention models. A novel clinical time series analysis model is proposed for several critical problems in healthcare. Another model coupled with triplet ranking loss as metric learning framework is described to better solve speaker diarization. Compared to state-of-the-art recurrent networks, these attention-based multivariate analysis tools achieve improved performance while having a lower computational complexity. Finally, in order to perform community detection on multilayer graphs, a fusion algorithm is described to derive node embedding from word embedding techniques and also exploit the complementary relational information contained in each layer of the graph.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201