Fall Detection, Wearable Sensors & Artificial Intelligence: A Short Review

Arslan Ishtiaq, Zubair Saeed, Misha Urooj Khan, Aqsa Samer, Mamoona Shabbir, Waqar Ahmad
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引用次数: 1

Abstract

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.
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跌倒检测、可穿戴传感器与人工智能:综述
跌倒是老年人的一个主要公共健康问题,近年来,用于检测跌倒的小工具的数量显著增加。本文件提供了关于跌倒检测系统的研究的详细总结,并对不同类型的研究进行了比较。它的目的是为计划或进行实地研究的医生和工程师提供资源。在检查之后,详细讨论了跌倒检测的数据集、局限性和未来的必要性。使用情境感知方法的研究数量不断增加,但将跌倒检测集成到智能手机以及在检测算法中使用人工智能是一种新趋势。还强调了对实际性能、可用性和可靠性的关注。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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审稿时长
24 weeks
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