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This paper describes the protocol of the microgravity experiment BEAT (Ballistocardiography for Extraterrestrial Applications and Long-Term Missions). The current study makes use of signal acquisition of cardiac parameters with a high-precision Ballistocardiography (BCG)/Seismocardiography (SCG) measurement system, which is integrated in a smart shirt (SmartTex). The goal is to evaluate the feasibility of this concept for continuous wearable monitoring and wireless data transfer. BEAT is part of the “Wireless Compose-2” (WICO2) project deployed on the International Space Station (ISS) that will provide wireless network infrastructure for scientific, localization and medical experiments.

For a decade, seismocardiography (SCG) on smartphones has been an interesting topic within the technical community, but mobile applications for this topic are rare on the market. The transition from laboratory to bedside application seems to have not yet been completed. To possibly increase the chances of a successful implementation, the added value of the method needs to be addressed clearly and backed up by research. The authors address the following aspects. 1. To improve comparability, standardization is required, 2. adequate validation processes in clinical settings will build trust, but foremost, 3. the field of application should be critically evaluated to identify the most meaningful and reasonable benefit of this method.

For cardiological datasets acquired via different methodologies, ECG signals that are recorded in parallel allow for relatively accurate matching. Some research issues, e.g., the identification of timings of the cardiac cycle in seismocardiography, require higher temporal resolutions. Therefore, we introduce a method derived from a feasibility study to determine deviations and factors influencing the merging of signals simultaneously recorded with different modalities.

Mobile devices and the apps running on them have become an integral part of daily life and this also includes the areas of medicine and health. Target audiences include those interested in their health, patients, and professional users. Nevertheless, the sheer number of available apps makes it hard for users to decide whether an app they are interested in is trustable or not. Nevertheless, such a decision should be based on a careful analysis of the available information. If left to their own devices, especially casual users may tend to forget certain aspects when performing such an evaluation. In order to provide them with a guideline on how to perform their evaluations, we propose a checklist covering the most important aspects for deciding whether an app can be entrusted with information that - especially when it comes to personal, health related information - is usually of a highly sensitive nature.

The patient as an active participant in decision-making has become an important resource in health care. Shared decision-making (SDM) relies on the patient's easy access to reliable and evidence-based health care information as well as the availability of patient-generated data, such as values and preferences for the health care professional (HCP). The aim of the present pilot study was to evaluate what type of information people with multiple sclerosis (pwMS) use in the SDM process, and what are the sources of that information. A semi-structured web-based survey of SDM was conducted through the MS-society in Finland. The results are presented against the Ottawa Decision Support Framework. A total of 27 pwMS participated. We found that all the participants wished to be involved in the decision-making process, but that they seldom found the information provided by HCP to be helpful. Instead, they searched the internet and visited various conversation platforms in social media, such as Facebook groups, for additional information. publishedVersion

In pursuit of equitable access to emergency-related knowledge, the World Health Organization (WHO) translates COVID-19 and other infectious disease courses into multiple languages on its open-access online learning platform OpenWHO.org. Languages spoken by vulnerable or underserved populations in low- and middle-income countries and in outbreak-prone and affected areas are prioritized. Accessing learning in preferred languages enhances uptake and comprehension. In this study, we assess and compare the initial enrollment levels and global reach of these multilingual courses. On average, OpenWHO's 38 COVID-19 courses have each been translated into 4.8 languages. The platform hosts courses in 55 different languages with 10.4 million words translated. The findings identify which available languages were most utilized for COVID-19 learning to inform course production and outreach strategies. Languages were used differently across geographic regions, calling for localized learning offerings. A streamlined multilingual publishing scheme, ensuring quick and effective delivery of diverse languages, is critical to achieving greater equity of access to knowledge. publishedVersion