A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals.

Pulse decomposition analysis (PDA) has been proposed to extract reliable information from photoplethysmography (PPG) morphology by decomposing the signal in its physiological sub-waves. The Gaussian model has been widely used in the literature, even though it often underperforms because it is limited to symmetric morphologies. More advanced asymmetric models, such as the Gamma model, have been proposed to achieve improved accuracy.

Ethics of Wearable-Based Out-of-Hospital Cardiac Arrest Detection.

Out-of-hospital cardiac arrest is a major health problem, and immediate treatment is essential for improving the chances of survival. The development of technological solutions to detect out-of-hospital cardiac arrest and alert emergency responders is gaining momentum; multiple research consortia are currently developing wearable technology for this purpose. For the responsible design and implementation of this technology, it is necessary to attend to the ethical implications.

"Psychiatric emergency consultations of minors: a qualitative study of professionals' experiences".

Background: Psychiatric emergency assessment of minors can be a complex process, especially for professional staff who are not specifically trained in handling child and adolescent emergency patients. As minors cannot usually express their feelings and experiences as well as adults, it is difficult to form an accurate picture of their condition and to determine what kind of emergency care is needed, for instance whether or not a psychiatric emergency admission is necessary. We lack insight in what professionals at emergency departments need to adequately assess these minors and their families.

Unsupervised denoising of the non-invasive fetal electrocardiogram with sparse domain Kalman filtering and vectorcardiographic loop alignment.

Even though the electrocardiogram (ECG) has potential to be used as a monitoring or diagnostic tool for fetuses, the use of non-invasive fetal ECG is complicated by relatively high amounts of noise and fetal movement during the measurement. Moreover, machine learning-based solutions to this problem struggle with the lack of clean reference data, which is difficult to obtain. To solve these problems, this work aims to incorporate fetal rotation correction with ECG denoising into a single unsupervised end-to-end trainable method.

Quantitative validation of the suprasternal pressure signal to assess respiratory effort during sleep.

Intra-esophageal pressure (Pes) measurement is the recommended gold standard to quantify respiratory effort during sleep, but used to limited extent in clinical practice due to multiple practical drawbacks. Respiratory inductance plethysmography belts (RIP) in conjunction with oronasal airflow are the accepted substitute in polysomnographic systems (PSG) thanks to a better usability, although they are partial views on tidal volume and flow rather than true respiratory effort and are often used without calibration. In their place, the pressure variations measured non-invasively at the suprasternal notch (SSP) may provide a better measure of effort.