{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T03:15:41Z","timestamp":1758078941930,"version":"3.44.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686196","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T00:00:00Z","timestamp":1757980800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9,16]]},"abstract":"<jats:p>Workplace stress, a widespread issue in modern professional environments, significantly increases the potential for errors and accidents. Timely and precise stress identification is vital for fostering a secure and efficient work environment. This research introduces an innovative, comparative-analysis framework designed for real-time stress detection, utilizing Heart Rate Variability (HRV) as a reliable physiological indicator. Unlike standard heart rate measurements, HRV offers a granular view of the autonomic nervous system (ANS) function, enabling accurate stress evaluation. We implement a comprehensive methodology incorporating a refined preprocessing stage\u2014including the removal of outliers, feature selection, and data normalization\u2014along with a comparative assessment of eight deep recurrent neural network (RNN) architectures. These include vanilla RNN, bidirectional RNN (BiRNN), Gated Recurrent Unit (GRU), bidirectional GRU (BiGRU), standard Long Short-Term Memory network (LSTM), bidirectional LSTM (BiLSTM), Peephole LSTM, and Attention-based LSTM, applied to binary stress classification. Utilizing a dataset of 410,322 HRV records from the SWELL Knowledge Work (SWELL-KW) Dataset, our framework demonstrates exceptional performance, with the BiGRU architecture achieving a test accuracy of 99.51%. This study highlights the effectiveness of advanced temporal modeling and comparative analysis in creating robust stress detection systems for various occupational contexts, thereby enhancing workplace safety.<\/jats:p>","DOI":"10.3233\/faia250558","type":"book-chapter","created":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T13:20:16Z","timestamp":1758028816000},"source":"Crossref","is-referenced-by-count":0,"title":["Stress Monitoring Using HRV and Deep Recurrent Neural Networks for Safety in Workplace: A Comparative Analysis"],"prefix":"10.3233","author":[{"given":"Ghofrane","family":"Mzoughi","sequence":"first","affiliation":[{"name":"Institut Sup\u00e9rieur d\u2019Informatique de Tunis \u2013 ISI, Tunis, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jaouhar","family":"Fattahi","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, Laval University, 2325, rue de l\u2019Universit\u00e9, Qu\u00e9bec (Qu\u00e9bec) G1V 0A6, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Mejri","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, Laval University, 2325, rue de l\u2019Universit\u00e9, Qu\u00e9bec (Qu\u00e9bec) G1V 0A6, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sahbi","family":"Bahroun","sequence":"additional","affiliation":[{"name":"Institut Sup\u00e9rieur d\u2019Informatique de Tunis \u2013 ISI, Tunis, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ridha","family":"Ghayoula","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Information Systems Department, University of Moncton, New Brunswick, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","New Trends in Intelligent Software Methodologies, Tools and Techniques"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA250558","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T13:20:17Z","timestamp":1758028817000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA250558"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,16]]},"ISBN":["9781643686196"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia250558","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,16]]}}}