Abstract
This chapter provides a detailed exploration of an innovative solution for enhancing in-home care for elderly, frail, and vulnerable adults—radar-based fall detection systems. These technologies are emerging as transformative tools to address the prevalent and impactful issue of falls within this population, improving their safety and quality of life. Highlighting the novelty of combining radar design, micro-Doppler signature analysis, machine learning, and advanced signal processing, the chapter delves into the practical application and benefits of these systems. Clinical evidence and successful real-world implementations are discussed, demonstrating the robustness and feasibility of this technology. Importantly, the chapter also navigates the ethical, legal, and social terrain associated with these technologies, addressing vital concerns about privacy, data security, and user acceptance. The chapter stresses the importance of further research, ongoing development, and the integration of radar-based fall detection systems with other emerging technologies. It culminates with a balanced perspective on the practical considerations and challenges in implementation, aiming to guide future innovations in the field. This chapter serves as a foundation for understanding and advancing the deployment of radar-based fall detection systems in in-home care.
| Original language | English |
|---|---|
| Title of host publication | Artificial Intelligence, Big Data, Blockchain and 5G for the Digital Transformation of the Healthcare Industry |
| Subtitle of host publication | a Movement Toward more Resilient and Inclusive Societies |
| Publisher | Elsevier |
| Pages | 21-40 |
| Number of pages | 20 |
| ISBN (Electronic) | 9780443215988 |
| ISBN (Print) | 9780443215995 |
| DOIs | |
| State | Published - 1 Jan 2023 |
| Externally published | Yes |
Keywords
- Elderly and vulnerable adults
- Emerging technologies
- In-home care
- Radar-based fall detection
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