This bachelor thesis investigates the implementation of fall detection systems in assisted living communities and explores the associated challenges from the perspective of live-in caregivers. The study is based on the demographic development in Austria, characterized by an aging population and a rising number of people in need of care. Among older adults, falls are a major health concern. Technical assistance systems, particularly digital fall detection technologies, offer the potential to improve safety and support caregiving staff. However, their practical integration in residential care settings requires a high level of acceptance, training, and organizational adaptation, along with careful consideration of data protection issues.
A qualitative case study was conducted in an assisted living community in Salzburg, where caregivers were interviewed about their experiences with the use of two fall detection systems: the Nobi lamp and the Cogvis system. Data was collected through semi-structured interviews and analyzed using qualitative content analysis. The findings indicate that while the systems are generally perceived as beneficial—especially for rapid emergency response—technical malfunctions, insufficient training, and concerns about data privacy pose significant challenges.
This thesis contributes to practice-oriented research on technology-supported care in non-institutional settings and provides concrete recommendations for the further development and implementation of Ambient Assisted Living technologies in everyday caregiving practice. Future research should focus on comparable fall detection systems in private home environments, where many care-dependent individuals live at high risk of falling, often without direct supervision. Such studies should specifically address practical usability, data privacy, and acceptance among users and their relatives.