The exam of fetal well-being during routine prenatal care plays a crucial role in preventing pregnancy complications and reducing the risks of miscarriages, birth defects and other health problems. However, the conventional prenatal screening and diagnosis is conducted by medical professionals in a clinical environment, which is subject to certain limitations such as manpower, medical devices and location, time and cost of services, etc. This paper presents a new approach to detect and monitor fetal movement safely and reliably without any constrains of time, environment and cost. Unlike the conventional method, our contribution includes a novel soft sensor pad which can automatically detect fetal movement and uterine contraction nonintrusively and the robust data analysis software to monitor pregnancy health and screen abnormalities with quantitative assessment. The monitoring belt embedded with the soft sensor pad is wearable, non-intrusive, radiation free and washable. The new algorithms are robust for noise removal, feature extraction, time sequence data analysis and decision support to achieve personalized care. Both the design of soft sensor pad and functions of the belt are original and unique. The results of preliminary clinical trials demonstrate the feasibility and advantages of our prototype.
In the process of digitization of cultural heritage objects with differentiated shininess it is difficult to reproduce faithfully the aesthetic of the original. The aim of the presented research is to address simultaneous capturing of shape, color and reflection features in order to digitally reproduce the appearance of the real object. We focus our work on a study of a ceramic furnace tile which exhibits complex shape, color and varying reflection properties. To achieve the goal we use a specially designed automated acquisition setup and provide a dedicated data processing pipeline. The collected geometry conforms to metrological uncertainty validation and the diffuse component is colorimetrically calibrated. The reflection properties are measurement-based, modeled with Blinn-Phong and visualized with an OpenGL shader. Close integration of capturing devices and a single data processing pipeline allows to fully utilize multidimensional raw data in order to get faithful final appearance model.