整合可穿戴传感器和机器学习来检测工业工人的关键事件
George Mantellos1, Themis P Exarchos2, Georgios N Dimitrakopoulos1
1Bioinformatics and Human Electrophysiology Laboratory, Department of Informatics, Ionian University, Corfu, Greece.
Advances in experimental medicine and biology
|July 24, 2023
概括
使用人工智能和可穿戴传感器的工业工人实时健康监测可以显著减少现场关键健康事件. 该系统提醒职业医生和工人潜在的问题,提高工作场所的安全.
科学领域:
- 职业健康 职业健康 职业健康
- 生物医学工程 生物医学工程
- 人工智能的人工智能
背景情况:
- 在工业环境中发生的与直接工作任务无关的严重健康事件,引发了严重的安全问题.
- 现有的监测方法往往不足以防止不可预见的健康事件.
- 积极的健康监测对于减轻工业环境中的风险至关重要.
研究的目的:
- 开发和介绍一个新的框架,用于实时监测工业工人的健康状况.
- 将人工智能与可穿戴传感器集成在一起,以早期检测健康事件.
- 尽量减少工业工地关键健康事件的发生和影响.
主要方法:
- 实施一个涉及可穿戴传感器的框架 (智能手表,基于耳朵的血压装置).
- 传感器数据直接传输到云存储系统,用于自主数据分析.
- 为职业医生开发一个界面,以便审查实时健康数据.
主要成果:
- 拟议的系统允许无和自主实时监测工人健康状况.
- 该框架有助于早期发现潜在的健康问题.
- 在检测到健康事件时,及时通知职业医生和工人.
结论:
- 可穿戴传感器和人工智能的集成系统为主动职业健康管理提供了强大的解决方案.
- 实时监控和人工智能驱动的分析可以通过预测和预防关键健康事件,显著提高工人安全.
- 这种方法使工人和职业医生能够获得及时的健康见解,改善工作场所的整体幸福感.
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