Fall Detection, Wearable Sensors & Artificial Intelligence: A Short Review
| Autor: | Arslan Ishtiaq, Zubair Saeed, Misha Urooj Khan, Aqsa Samer, Mamoona Shabbir, Waqar Ahmad |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | JAREE (Journal on Advanced Research in Electrical Engineering). 6 |
| ISSN: | 2579-6216 2580-0361 |
| DOI: | 10.12962/jaree.v6i2.323 |
| Popis: | Falls are a major public health concern among the elderly and the number of gadgets designed to detect them has increased significantly in recent years. This document provides a detailed summary of research done on fall detection systems, with comparisons across different types of studies. Its purpose is to be a resource for doctors and engineers who are planning or conducting field research. Following the examination, datasets, limitations, and future imperatives in fall detection were discussed in detail. The quantity of research using context-aware approaches continues to rise, but there is a new trend toward integrating fall detection into smartphones, as well as the use of artificial intelligence in the detection algorithm. Concerns with real-world performance, usability, and reliability are also highlighted. |
| Databáze: | OpenAIRE |
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