DeepPerfusion: A comprehensible two-branched deep learning architecture for high-precision blood volume pulse extraction based on imaging photoplethysmography.

Imaging photoplethysmography (iPPG) is a contactless approach for the extraction of the blood volume pulsation (BVP). Analyzing the small intensity changes resulting from fluctuations in light absorption in upper skin layers enables BVP extraction. Inhomogeneous illumination or head movements impede iPPG-based BVP extraction.

Needs- and user-oriented development of contactless camera-based telemonitoring in heart disease-Results of an acceptance survey from the Home-based Healthcare Project (feasibility project).

Home-based telemonitoring in heart failure patients can reduce all-cause mortality and the relative risk of heart failure-related hospitalization compared to standard care. However, technology use depends, among other things, on user acceptance, making it important to include potential users early in development. In a home-based healthcare project (a feasibility project) a participatory approach was chosen in preparation for future development of contactless camera-based telemonitoring in heart disease patients.

Camera-based assessment of cutaneous perfusion strength in a clinical setting.

. After skin flap transplants, perfusion strength monitoring is essential for the early detection of tissue perfusion disorders and thus to ensure the survival of skin flaps. Camera-based photoplethysmography (cbPPG) is a non-contact measurement method, using video cameras and ambient light, which provides spatially resolved information about tissue perfusion.

Topical negative pressure wound therapy enhances the local tissue perfusion - A pilot study.

Background: Topical negative pressure wound therapy (TNPWT) is a regularly used method in modern wound treatment with a growing and diverse potential for clinical use. So far positive effects on microcirculation have been observed and examined, although precise statements on the underlying mechanism appear unsatisfying.

Objective: The aim of our study was to extend the understanding of the effect of TNPWT on tissue perfusion and determine the time frame and the extent to which the tissue perfusion changes due to TNPWT.

Predicting sepsis with a recurrent neural network using the MIMIC III database.

Objective: Predicting sepsis onset with a recurrent neural network and performance comparison with InSight - a previously proposed algorithm for the prediction of sepsis onset.

Methodology: A retrospective analysis of adult patients admitted to the intensive care unit (from the MIMIC III database) who did not fall under the definition of sepsis at the time of admission. The area under the receiver operating characteristic (AUROC) measures the performance of the prediction task.