Fall Detection

Abstract

As the global population ages, the incidence of falls among the older adults increases, necessitating advancements in fall detection and prevention technologies. This chapter provides a comprehensive overview of the current state of these technologies in the context of Active Assisted Living (AAL). It begins by discussing the importance of fall statistics and the critical need for early detection to mitigate severe health consequences and reduce healthcare costs. Various fall detection methods are explored, distinguishing between image-based and non-image-based approaches. The chapter also examines the technological principles behind these methods, such as the use of accelerometers, pressure sensors, depth cameras, and thermal imaging. Privacy concerns are addressed, highlighting the balance between effective monitoring and maintaining user confidentiality. The usability challenges associated with false positives and false negatives are analyzed, emphasizing the importance of user-friendly systems that encourage consistent use by both older adults and caregivers. Finally, the chapter considers the ethical implications and the need for ongoing research to refine these technologies for better accuracy and user acceptance.