Evaluation of the digital image correlation method for the measurement of vibration mode shapes

Digital Image Correlation (DIC) is a modern non-contact, full-field optical technique that is being used for the measurement of static and dynamic displacement problems, material testing and fracture mechanics. In particular, three dimensional DIC is able to measure the out-of-plane vibration mode shapes and deformation of a vibrating structure. Thus, this technique can potentially provide an important validation tool between measured and predicted results. This paper presents some preliminary evaluation results from using the DIC measurement approach. The DIC method was implemented using two low-speed charge-couple device cameras and a phase-locked measurement technique synchronised to the excitation. A 1.2mm thick steel plate with clamped boundary conditions was chosen as the test sample. Resonant frequencies and mode shapes were compared to predictions made using a Finite Element analysis and the experimental Chladni method of visualizing vibrating mode patterns. This comparison reveals some of the advantages and limitations of the DIC method for vibration mode shape analysi

Health Figures: An Open Source JavaScript Library for Health Data Visualization

The way we look at data has a great impact on how we can understand it, particularly when the data is related to health and wellness. Due to the increased use of self-tracking devices and the ongoing shift towards preventive medicine, better understanding of our health data is an important part of improving the general welfare of the citizens. Electronic Health Records, self-tracking devices and mobile applications provide a rich variety of data but it often becomes difficult to understand. We implemented the hFigures library inspired on the hGraph visualization with additional improvements. The purpose of the library is to provide a visual representation of the evolution of health measurements in a complete and useful manner. We researched the usefulness and usability of the library by building an application for health data visualization in a health coaching program. We performed a user evaluation with Heuristic Evaluation, Controlled User Testing and Usability Questionnaires. In the Heuristics Evaluation the average response was 6.3 out of 7 points and the Cognitive Walkthrough done by usability experts indicated no design or mismatch errors. In the CSUQ usability test the system obtained an average score of 6.13 out of 7, and in the ASQ usability test the overall satisfaction score was 6.64 out of 7. We developed hFigures, an open source library for visualizing a complete, accurate and normalized graphical representation of health data. The idea is based on the concept of the hGraph but it provides additional key features, including a comparison of multiple health measurements over time. We conducted a usability evaluation of the library as a key component of an application for health and wellness monitoring. The results indicate that the data visualization library was helpful in assisting users in understanding health data and its evolution over time.Comment: BMC Medical Informatics and Decision Making 16.1 (2016