Smart-phone based electrocardiogram wavelet decomposition and neural network classification

This paper discusses ECG classification after parametrizing the ECG waveforms in the wavelet domain. The aim of the work is to develop an accurate classification algorithm that can be used to diagnose cardiac beat abnormalities detected using a mobile platform such as smart-phones. Continuous time recurrent neural network classifiers are considered for this task. Records from the European ST-T Database are decomposed in the wavelet domain using discrete wavelet transform (DWT) filter banks and the resulting DWT coefficients are filtered and used as inputs for training the neural network classifier. Advantages of the proposed methodology are the reduced memory requirement for the signals which is of relevance to mobile applications as well as an improvement in the ability of the neural network in its generalization ability due to the more parsimonious representation of the signal to its inputs

Beyond Screens: Tangible Approaches to sleep-tracking excellence

Sleep quality profoundly influences physical and mental well-being, yet it is frequently neglected in health discussions despite its pivotal role in these domains. This thesis utilizes Autoethnography, incorporating Mixed Method - Quantified Self-Tracking and Journaling methods to collect data and critically understand my sleep, lifestyle, and sleep environment. Sleep-tracking apps provide valuable data on our sleep, but interpreting this data can often be challenging. A sleep application utilizes mobile phone sensors and advises us to keep our phone close to the body, which may increase screen interaction and impact our quality of sleep. Sleep is complex, and many factors of our physical and mental health are interlinked. This thesis suggests tangible approaches to visualize personal data from sleep apps and journaling. Through the exploration of my own data, I experimented with different tangible representations, turning abstract information into touchable objects, aiming to foster a serene user experience by reducing reliance on screens. This research contributes to the fields of data visualization, tangible interface, and health design showcasing the potential of tangible visualization in promoting the understanding of sleep patterns. Keywords: Tangible Representation, Sleep Environment, User Experience, Data Humanism, Data Visualization, Digital Fabrication, Quantified Self, Self-trackin

First inter-laboratory study of a Supercritical Fluid Chromatography method for the determination of pharmaceutical impurities

International audienceSupercritical Fluid Chromatography (SFC) has known a strong regain of interest for the last 10 years, especially in the field of pharmaceutical analysis. Besides the development and validation of the SFC method in one individual laboratory, it is also important to demonstrate its applicability and transferability to various laboratories around the world. Therefore, an inter-laboratory study was conducted and published for the first time in SFC, to assess method reproducibility, and evaluate whether this chromatographic technique could become a reference method for quality control (QC) laboratories. This study involved 19 participating laboratories from 4 continents and 9 different countries. It included 5 academic groups, 3 demonstration laboratories at analytical instrument companies, 10 pharmaceutical companies and 1 food company. In the initial analysis of the study results, consistencies within- and between-laboratories were deeply examined. In the subsequent analysis, the method reproducibility was estimated taking into account variances in replicates, between-days and between-laboratories. The results obtained were compared with the literature values for liquid chromatography (LC) in the context of impurities determination. Repeatability and reproducibility variances were found to be similar or better than those described for LC methods, and highlighted the adequacy of the SFC method for QC analyses. The results demonstrated the excellent and robust quantitative performance of SFC. Consequently, this complementary technique is recognized on equal merit to other chromatographic techniques