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Auscultation methods enable non-invasive diagnosis of diseases, e.g. of the heart, based on heartbeat sounds. Regular, early examinations using machine learning techniques could help to detect diseases at an early stage to prevent serious health conditions and then provide optimal therapy through continuous monitoring. There is already a lot of work on human data using AI algorithms to detect patterns in signals or images. However, there is hardly no work on detecting heart murmurs with digital such as Myxomatous Mitral Valve Disease. In this paper, we present a canine auscultation project that aims to provide a tool to establish a baseline of classification parameters from audio signals that could be used to monitor canine health status by analyzing deviations from this baseline. In the future, data analysis could also lead to prediction and early detection of other diseases.

Smart Devices, IoT and Co. are changing healthcare. The possibilities for pervasive sensing and analysis are fast increasing and new therapy concepts as well as business models are arising, related to the term “Digital Health”. The paper will give a brief overview on the history and ask, whether Digital Health is more than Telemedicine 4.0. Furthermore, we will ask for the prospective currency to participate in new preventive offer. Data is the new oil – Digital Biomarkers enable new value chains on health data and allow for the personalization of healthcare. We will present ongoing work of Fraunhofer ISST on a Digital Biomarker called beHealthy Health Score.

The aim of this online-survey study is the development and evaluation of a mobile health application specifically designed to meet the needs of individuals who have previously undergone intensive-care treatment. User acceptance and perception play a crucial role in refining and optimizing the app's features and functionalities. By actively incorporating suggestions and insights from users, the goal is to enhance the overall usability and better cater to the diverse needs of individuals in post-intensive care recovery. This iterative approach ensures that the application remains responsive to the evolving requirements of its target audience. Overall, the emphasis is on creating a user-centric and adaptive tool for former intensive care patients, to develop a user-friendly mobile app. [ABSTRACT FROM AUTHOR]