公共行政工作人员职业风险因素一周多模式数据采集

Eduarda Oliosi, Phillip Probst, João Rodrigues, Luís Silva, Daniel Zagalo, Cátia Cepeda, Hugo Gamboa
{"title":"公共行政工作人员职业风险因素一周多模式数据采集","authors":"Eduarda Oliosi, Phillip Probst, João Rodrigues, Luís Silva, Daniel Zagalo, Cátia Cepeda, Hugo Gamboa","doi":"10.1109/IE57519.2023.10179099","DOIUrl":null,"url":null,"abstract":"Work-related disorders are a growing issue for office workers and represent a significant burden to public health. Work aspects such as sitting for prolonged periods and occupational stress are modifiable risk factors highly associated with occupational disorders in office workers. The PrevOccu-pAI Project (Prevention of Occupational Disorders in Public Administrations based on Artificial Intelligence) objectively investigates relationships between a variety of occupational risk factors and physiological outcomes. For this purpose, a data acquisition protocol was carried out at the Portuguese Tax and Customs Authority. Physiological, movement, and environmental signals from office workers were acquired during five consecutive workdays using a smartphone, a smartwatch, and two electromyography sensors. Additionally, demographic, occupational, and pain information were collected through questionnaires. The present manuscript provides a detailed description of the PrevOccupAI acquisition protocol. The collected data is used to gather knowledge regarding modifiable factors at the individual and organisational levels.","PeriodicalId":439212,"journal":{"name":"2023 19th International Conference on Intelligent Environments (IE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Week-long Multimodal Data Acquisition of Occupational Risk Factors in Public Administration Workers\",\"authors\":\"Eduarda Oliosi, Phillip Probst, João Rodrigues, Luís Silva, Daniel Zagalo, Cátia Cepeda, Hugo Gamboa\",\"doi\":\"10.1109/IE57519.2023.10179099\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Work-related disorders are a growing issue for office workers and represent a significant burden to public health. Work aspects such as sitting for prolonged periods and occupational stress are modifiable risk factors highly associated with occupational disorders in office workers. The PrevOccu-pAI Project (Prevention of Occupational Disorders in Public Administrations based on Artificial Intelligence) objectively investigates relationships between a variety of occupational risk factors and physiological outcomes. For this purpose, a data acquisition protocol was carried out at the Portuguese Tax and Customs Authority. Physiological, movement, and environmental signals from office workers were acquired during five consecutive workdays using a smartphone, a smartwatch, and two electromyography sensors. Additionally, demographic, occupational, and pain information were collected through questionnaires. The present manuscript provides a detailed description of the PrevOccupAI acquisition protocol. The collected data is used to gather knowledge regarding modifiable factors at the individual and organisational levels.\",\"PeriodicalId\":439212,\"journal\":{\"name\":\"2023 19th International Conference on Intelligent Environments (IE)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 19th International Conference on Intelligent Environments (IE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IE57519.2023.10179099\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 19th International Conference on Intelligent Environments (IE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IE57519.2023.10179099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

与工作有关的疾病是办公室工作人员日益严重的问题,对公共卫生构成了重大负担。工作方面,如长时间坐着和职业压力是可改变的风险因素,与办公室工作人员的职业障碍高度相关。prevoccupation - pai项目(基于人工智能的公共管理职业障碍预防)客观调查了各种职业风险因素与生理结果之间的关系。为此目的,在葡萄牙税务和海关管理局执行了一项数据获取议定书。研究人员使用智能手机、智能手表和两个肌电传感器,在连续五个工作日内获取办公室工作人员的生理、运动和环境信号。此外,通过问卷调查收集人口统计、职业和疼痛信息。目前的手稿提供了PrevOccupAI获取协议的详细描述。收集到的数据用于收集关于个人和组织层面的可修改因素的知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Week-long Multimodal Data Acquisition of Occupational Risk Factors in Public Administration Workers
Work-related disorders are a growing issue for office workers and represent a significant burden to public health. Work aspects such as sitting for prolonged periods and occupational stress are modifiable risk factors highly associated with occupational disorders in office workers. The PrevOccu-pAI Project (Prevention of Occupational Disorders in Public Administrations based on Artificial Intelligence) objectively investigates relationships between a variety of occupational risk factors and physiological outcomes. For this purpose, a data acquisition protocol was carried out at the Portuguese Tax and Customs Authority. Physiological, movement, and environmental signals from office workers were acquired during five consecutive workdays using a smartphone, a smartwatch, and two electromyography sensors. Additionally, demographic, occupational, and pain information were collected through questionnaires. The present manuscript provides a detailed description of the PrevOccupAI acquisition protocol. The collected data is used to gather knowledge regarding modifiable factors at the individual and organisational levels.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信