{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T19:09:43Z","timestamp":1767035383926,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819981373"},{"type":"electronic","value":"9789819981380"}],"license":[{"start":{"date-parts":[[2023,11,26]],"date-time":"2023-11-26T00:00:00Z","timestamp":1700956800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,11,26]],"date-time":"2023-11-26T00:00:00Z","timestamp":1700956800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-99-8138-0_23","type":"book-chapter","created":{"date-parts":[[2023,11,25]],"date-time":"2023-11-25T10:02:23Z","timestamp":1700906543000},"page":"287-297","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Novel Framework for\u00a0Forecasting Mental Stress Levels Based on\u00a0Physiological Signals"],"prefix":"10.1007","author":[{"given":"Yifan","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Binghua","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinhong","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan","family":"Feng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zerui","family":"Han","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yehan","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Likun","family":"Xia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,11,26]]},"reference":[{"key":"23_CR1","doi-asserted-by":"publisher","first-page":"964","DOI":"10.3389\/fpsyt.2019.00964","volume":"10","author":"F Wang","year":"2019","unstructured":"Wang, F., Yang, J., Pan, F., Bourgeois, J.A., Huang, J.H.: Early life stress and depression. Front. Psych. 10, 964 (2019)","journal-title":"Front. Psych."},{"key":"23_CR2","doi-asserted-by":"publisher","first-page":"l1255","DOI":"10.1136\/bmj.l1255","volume":"365","author":"H Song","year":"2019","unstructured":"Song, H., Fang, F., Arnberg, F.K., et al.: Stress related disorders and risk of cardiovascular disease: population based, sibling controlled cohort study. BMJ. Br. Med. J. 365, l1255 (2019)","journal-title":"BMJ. Br. Med. J."},{"issue":"6","key":"23_CR3","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1007\/s00406-017-0794-x","volume":"267","author":"G Kronenberg","year":"2017","unstructured":"Kronenberg, G., Sch\u00f6ner, J., Nolte, C., Heinz, A., Endres, M., Gertz, K.: Charting the perfect storm: emerging biological interfaces between stress and stroke. Eur. Arch. Psychiatry Clin. Neurosci. 267(6), 487\u2013494 (2017)","journal-title":"Eur. Arch. Psychiatry Clin. Neurosci."},{"issue":"6","key":"23_CR4","doi-asserted-by":"publisher","first-page":"532","DOI":"10.1016\/j.aap.2012.03.028","volume":"49","author":"AJ Day","year":"2012","unstructured":"Day, A.J., Brasher, K., Bridger, R.S.: Accident proneness revisited: the role of psychological stress and cognitive failure. Accid. Anal. Prev. 49(6), 532\u2013535 (2012)","journal-title":"Accid. Anal. Prev."},{"key":"23_CR5","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1016\/j.trf.2015.12.008","volume":"37","author":"CS Lu","year":"2016","unstructured":"Lu, C.S., Kuo, S.Y.: The effect of job stress on self-reported safety behaviour in container terminal operations: the moderating role of emotional intelligence. Transport. Res. F: Traffic Psychol. Behav. 37, 10\u201326 (2016)","journal-title":"Transport. Res. F: Traffic Psychol. Behav."},{"issue":"1","key":"23_CR6","doi-asserted-by":"publisher","first-page":"04015019","DOI":"10.1061\/(ASCE)ME.1943-5479.0000373","volume":"32","author":"MY Leung","year":"2016","unstructured":"Leung, M.Y., Liang, Q., Olomolaiye, P.: Impact of job stressors and stress on the safety behavior and accidents of construction workers. J. Manag. Eng. 32(1), 04015019 (2016)","journal-title":"J. Manag. Eng."},{"issue":"3","key":"23_CR7","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1016\/0167-8760(84)90046-1","volume":"1","author":"D Lehmann","year":"1984","unstructured":"Lehmann, D.: EEG assessment of brain activity: spatial aspects, segmentation and imaging. Int. J. Psychophysiol. 1(3), 267\u2013276 (1984)","journal-title":"Int. J. Psychophysiol."},{"key":"23_CR8","doi-asserted-by":"crossref","unstructured":"Al-Shargie, F.M., Tang, T.B., Kiguchi, M.: Mental stress quantification using EEG signals. In 2015 International Conference for Innovation in Biomedical Engineering and Life Sciences (IFMBE), Singapore: Springer Singapore, 15-19 (2016)","DOI":"10.1007\/978-981-10-0266-3_4"},{"key":"23_CR9","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.bspc.2018.06.004","volume":"46","author":"L Xia","year":"2018","unstructured":"Xia, L., Malik, A.S., Subhani, A.R.: A physiological signal-based method for early mental-stress detection. Biomed. Signal Process. Control 46, 18\u201332 (2018)","journal-title":"Biomed. Signal Process. Control"},{"issue":"6","key":"23_CR10","doi-asserted-by":"publisher","first-page":"2257","DOI":"10.1109\/JBHI.2019.2926407","volume":"23","author":"A Arsalan","year":"2019","unstructured":"Arsalan, A., Majid, M., Butt, A.R., Anwar, S.M.: Classification of perceived mental stress using a commercially available EEG headband. IEEE J. Biomed. Health Inform. 23(6), 2257\u20132264 (2019)","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"23_CR11","doi-asserted-by":"crossref","unstructured":"Jun, G., Smitha K.G.: EEG based stress level identification. IEEE International Conference on Systems, Man, and Cybernetics (SMC), 003270-003274 (2016)","DOI":"10.1109\/SMC.2016.7844738"},{"key":"23_CR12","doi-asserted-by":"publisher","first-page":"13545","DOI":"10.1109\/ACCESS.2017.2723622","volume":"5","author":"AR Subhani","year":"2017","unstructured":"Subhani, A.R., Mumtaz, W., Saad, M., Kamel, N., Malik, A.S.: Machine learning framework for the detection of mental stress at multiple levels. IEEE Access 5, 13545\u201313556 (2017)","journal-title":"IEEE Access"},{"key":"23_CR13","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1016\/j.compbiomed.2019.02.015","volume":"107","author":"A Asif","year":"2019","unstructured":"Asif, A., Majid, M., Anwar, S.M.: Human stress classification using EEG signals in response to music tracks. Comput. Biol. Med. 107, 182\u2013196 (2019)","journal-title":"Comput. Biol. Med."},{"key":"23_CR14","doi-asserted-by":"crossref","unstructured":"Ahirwal, M.K.: Analysis and identification of EEG features for mental stress. In Evolution in Computational Intelligence, Singapore: Springer Singapore, 201\u2013209 (2021)","DOI":"10.1007\/978-981-15-5788-0_19"},{"key":"23_CR15","doi-asserted-by":"crossref","unstructured":"Norhazman, H., Zaini, N., Taib, M.N., Jailani, R., Latip, M.: Alpha and Beta Sub-waves Patterns when Evoked by External Stressor and Entrained by Binaural Beats Tone. 2019 IEEE 7th Conference on Systems, Process and Control (ICSPC), 112-117 (2019)","DOI":"10.1109\/ICSPC47137.2019.9068008"},{"issue":"8","key":"23_CR16","doi-asserted-by":"publisher","first-page":"1771","DOI":"10.1109\/TNSRE.2020.3005771","volume":"28","author":"HY Chang","year":"2020","unstructured":"Chang, H.Y., Stevenson, C.E., Jung, T.P., Ko, L.W.: Stress-induced effects in resting EEG spectra predict the performance of SSVEP-based BCI. IEEE Trans. Neural Syst. Rehabil. Eng. 28(8), 1771\u20131780 (2020)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"23_CR17","doi-asserted-by":"crossref","unstructured":"Taelman, J., Vandeput, S., Spaepen, A., Van Huffel, S.: Influence of mental stress on heart rate and heart rate variability. In 4th European conference of the international federation for medical and biological engineering, 1366-1369 (2009)","DOI":"10.1007\/978-3-540-89208-3_324"},{"key":"23_CR18","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1016\/j.cmpb.2017.06.018","volume":"148","author":"T Pereira","year":"2017","unstructured":"Pereira, T., Almeida, P.R., Cunha, J.P., Aguiar, A.: Heart rate variability metrics for fine-grained stress level assessment. Comput. Methods Programs Biomed. 148, 71\u201380 (2017)","journal-title":"Comput. Methods Programs Biomed."},{"key":"23_CR19","doi-asserted-by":"crossref","unstructured":"Suhara, Y., Xu, Y., Pentland, A.: DeepMood: Forecasting depressed mood based on self-reported histories via recurrent neural networks. the 26th International Conference on International World Wide Web Conferences Steering Committee, 17 (2017)","DOI":"10.1145\/3038912.3052676"},{"key":"23_CR20","doi-asserted-by":"crossref","unstructured":"Taylor, S.A., Jaques, N., Nosakhare, E., Sano, A., Picard, R.: Personalized multitask learning for predicting tomorrow\u2019s mood, stress, and health. IEEE Trans. Affect. Comput. 11(2), 200\u2013213 (2020)","DOI":"10.1109\/TAFFC.2017.2784832"},{"key":"23_CR21","doi-asserted-by":"crossref","unstructured":"Umematsu, T., Sano, A., Taylor, S., Picard, R.W.: Improving students\u2019 daily life stress forecasting using LSTM neural networks. In 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), 1-4 (2019)","DOI":"10.1109\/BHI.2019.8834624"},{"issue":"1","key":"23_CR22","doi-asserted-by":"publisher","first-page":"14","DOI":"10.3390\/data4010014","volume":"4","author":"I Zyma","year":"2019","unstructured":"Zyma, I., Tukaev, S., Seleznov, I., Kiyono, K., Popov, A., Chernykh, M., Shpenkov, O.: Electroencephalograms during mental arithmetic task performance. Data 4(1), 14 (2019)","journal-title":"Data"},{"issue":"11","key":"23_CR23","doi-asserted-by":"publisher","first-page":"2106","DOI":"10.1109\/TNSRE.2018.2872924","volume":"26","author":"WL Lim","year":"2018","unstructured":"Lim, W.L., Sourina, O., Wang, L.P.: STEW: simultaneous task EEG workload data set. IEEE Trans. Neural Syst. Rehabil. Eng. 26(11), 2106\u20132114 (2018)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"issue":"5","key":"23_CR24","first-page":"319","volume":"30","author":"K Dedovic","year":"2005","unstructured":"Dedovic, K., Renwick, R., Pruessner, J.C.: The Montreal Imaging Stress Task: using functional imaging to investigate the effects of perceiving and processing psychosocial stress in the human brain. J. Psychiatry Neurosci. 30(5), 319 (2005)","journal-title":"J. Psychiatry Neurosci."},{"issue":"4","key":"23_CR25","doi-asserted-by":"publisher","first-page":"795","DOI":"10.1109\/TNSRE.2020.2972812","volume":"28","author":"O Komarov","year":"2020","unstructured":"Komarov, O., Ko, L.W., Jung, T.P.: Associations among emotional state, sleep quality, and resting-state EEG spectra: a longitudinal study in graduate students. IEEE Trans. Neural Syst. Rehabil. Eng. 28(4), 795\u2013804 (2020)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."}],"container-title":["Communications in Computer and Information Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-8138-0_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T17:33:22Z","timestamp":1710351202000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-8138-0_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,26]]},"ISBN":["9789819981373","9789819981380"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-8138-0_23","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2023,11,26]]},"assertion":[{"value":"26 November 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Changsha","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/iconip2023.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1274","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"650","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"51% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4.14","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.46","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}