{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T19:16:35Z","timestamp":1757618195349,"version":"3.44.0"},"publisher-location":"Cham","reference-count":40,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031941528"},{"type":"electronic","value":"9783031941535"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-94153-5_12","type":"book-chapter","created":{"date-parts":[[2025,6,7]],"date-time":"2025-06-07T09:38:49Z","timestamp":1749289129000},"page":"123-133","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Identifying Human Out-of-the-Loop in Cruising Flights Using EEG Spectral Features with Deep Learning"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5097-8723","authenticated-orcid":false,"given":"Cho Yin","family":"Yiu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4959-0502","authenticated-orcid":false,"given":"Kam K. H.","family":"Ng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3858-0736","authenticated-orcid":false,"given":"Qinbiao","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3791-5533","authenticated-orcid":false,"given":"Xin","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,5,30]]},"reference":[{"key":"12_CR1","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1016\/j.tranpol.2022.09.020","volume":"128","author":"CY Yiu","year":"2022","unstructured":"Yiu, C.Y., et al.: Sustaining aviation workforce after the pandemic: evidence from Hong Kong aviation students toward skills, specialised training, and career prospects through a mixed-method approach. Transp. Policy 128, 179\u2013192 (2022)","journal-title":"Transp. Policy"},{"issue":"2","key":"12_CR2","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1177\/0018720816665201","volume":"59","author":"A Sebok","year":"2017","unstructured":"Sebok, A., Wickens, C.D.: Implementing Lumberjacks and black swans into model-based tools to support human-automation interaction. Hum. Factors 59(2), 189\u2013203 (2017)","journal-title":"Hum. Factors"},{"key":"12_CR3","doi-asserted-by":"crossref","unstructured":"Gouraud, J.,\u00a0 Delorme, A., Berberian, B.: Autopilot, mind wandering, and the out of the loop performance problem. Front. Neurosci. 11 (2017)","DOI":"10.3389\/fnins.2017.00541"},{"key":"12_CR4","unstructured":"Billings, C., et al.: NASA aviation safety reporting system (1976)"},{"issue":"5","key":"12_CR5","doi-asserted-by":"publisher","first-page":"904","DOI":"10.1177\/0018720820960865","volume":"64","author":"T O\u2019Neill","year":"2020","unstructured":"O\u2019Neill, T., et al.: Human-autonomy teaming: a review and analysis of the empirical literature. Hum. Factors 64(5), 904\u2013938 (2020)","journal-title":"Hum. Factors"},{"issue":"3","key":"12_CR6","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1177\/0018720813501549","volume":"56","author":"L Onnasch","year":"2014","unstructured":"Onnasch, L., et al.: Human performance consequences of stages and levels of automation: an integrated meta-analysis. Hum. Factors 56(3), 476\u2013488 (2014)","journal-title":"Hum. Factors"},{"key":"12_CR7","doi-asserted-by":"crossref","unstructured":"Yeung, T.C., et al.: Airside terminal traffic flow problem formulation under extreme weather: a case study in the Hong Kong International Airport. In:\u00a0 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS) (2022)","DOI":"10.1109\/SCISISIS55246.2022.10001871"},{"issue":"3","key":"12_CR8","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1518\/001872008X312152","volume":"50","author":"JS Warm","year":"2008","unstructured":"Warm, J.S., Parasuraman, R., Matthews, G.: Vigilance requires hard mental work and is stressful. Hum. Factors 50(3), 433\u2013441 (2008)","journal-title":"Hum. Factors"},{"key":"12_CR9","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.concog.2014.04.001","volume":"27","author":"DR Thomson","year":"2014","unstructured":"Thomson, D.R., et al.: On the link between mind wandering and task performance over time. Conscious. Cogn. 27, 14\u201326 (2014)","journal-title":"Conscious. Cogn."},{"key":"12_CR10","doi-asserted-by":"crossref","unstructured":"Ayas, S., Donmez, B., Tang,  X.: Drowsiness mitigation through driver state monitoring systems: a scoping review. Hum. Fact., 00187208231208523 (2023)","DOI":"10.1177\/00187208231208523"},{"key":"12_CR11","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1016\/j.arcontrol.2017.09.010","volume":"44","author":"B Berberian","year":"2017","unstructured":"Berberian, B., et al.: The out-of-the-loop Brain: a neuroergonomic approach of the human automation interaction. Annu. Rev. Control. 44, 303\u2013315 (2017)","journal-title":"Annu. Rev. Control."},{"key":"12_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.apergo.2023.104162","volume":"115","author":"E Balta","year":"2024","unstructured":"Balta, E., Psarrakis, A., Vatakis, A.: The effects of increased mental workload of air traffic controllers on time perception: behavioral and physiological evidence. Appl. Ergon. 115, 104162 (2024)","journal-title":"Appl. Ergon."},{"issue":"6","key":"12_CR13","doi-asserted-by":"publisher","first-page":"775","DOI":"10.1016\/0005-1098(83)90046-8","volume":"19","author":"L Bainbridge","year":"1983","unstructured":"Bainbridge, L.: Ironies of automation. Automatica 19(6), 775\u2013779 (1983)","journal-title":"Automatica"},{"issue":"4","key":"12_CR14","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1109\/THMS.2023.3274916","volume":"53","author":"S Rothfu\u00df","year":"2023","unstructured":"Rothfu\u00df, S., et al.: Human-machine cooperative decision making outperforms individualism and autonomy. IEEE Trans. Hum.-Mach. Syst. 53(4), 761\u2013770 (2023)","journal-title":"IEEE Trans. Hum.-Mach. Syst."},{"issue":"3","key":"12_CR15","doi-asserted-by":"publisher","first-page":"511","DOI":"10.1518\/001872008X312198","volume":"50","author":"R Parasuraman","year":"2008","unstructured":"Parasuraman, R., Wickens, C.D.: Humans: still vital after all these years of automation. Hum. Fact. 50(3), 511\u2013520 (2008)","journal-title":"Hum. Fact."},{"key":"12_CR16","unstructured":"Liu, P.: Reflections on automation complacency. Inter. J. Hum.\u2013Comput. Interact.,\u00a0 1\u201317 (2023)"},{"key":"12_CR17","doi-asserted-by":"publisher","DOI":"10.1016\/j.apergo.2022.103838","volume":"105","author":"E van Weelden","year":"2022","unstructured":"van Weelden, E., et al.: Aviation and neurophysiology: a systematic review. Appl. Ergon. 105, 103838 (2022)","journal-title":"Appl. Ergon."},{"key":"12_CR18","unstructured":"Yiu, C.Y., et al.: On the significance of using event-related potentials and gaze behaviours to evaluate inflight emergency training performance. In: The 26th ATRS World Conference, Kobe, Japan (2023)"},{"issue":"2","key":"12_CR19","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1109\/TCDS.2016.2628702","volume":"10","author":"JA Blanco","year":"2018","unstructured":"Blanco, J.A., et al.: Quantifying cognitive workload in simulated flight using passive, dry EEG measurements. IEEE Trans. Cognitive Developm. Syst. 10(2), 373\u2013383 (2018)","journal-title":"IEEE Trans. Cognitive Developm. Syst."},{"key":"12_CR20","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/j.apergo.2019.01.012","volume":"77","author":"C Diaz-Piedra","year":"2019","unstructured":"Diaz-Piedra, C., et al.: The effects of flight complexity on gaze entropy: an experimental study with fighter pilots. Appl. Ergon. 77, 92\u201399 (2019)","journal-title":"Appl. Ergon."},{"issue":"7","key":"12_CR21","doi-asserted-by":"publisher","first-page":"1271","DOI":"10.1177\/0018720820928626","volume":"63","author":"KA Feltman","year":"2020","unstructured":"Feltman, K.A., Bernhardt, K.A., Kelley, A.M.: Measuring the domain specificity of workload using EEG: auditory and visual domains in rotary-wing simulated flight. Hum. Factors 63(7), 1271\u20131283 (2020)","journal-title":"Hum. Factors"},{"key":"12_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2020.101989","volume":"60","author":"D Das Chakladar","year":"2020","unstructured":"Das Chakladar, D., et al.: EEG-based mental workload estimation using deep BLSTM-LSTM network and evolutionary algorithm. Biomed. Signal Process. Control 60, 101989 (2020)","journal-title":"Biomed. Signal Process. Control"},{"key":"12_CR23","doi-asserted-by":"crossref","unstructured":"Borghini, G., et al.: Avionic technology testing by using a cognitive neurometric index: a study with professional helicopter pilots. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (2015)","DOI":"10.1109\/EMBC.2015.7319804"},{"issue":"10","key":"12_CR24","doi-asserted-by":"publisher","first-page":"3907","DOI":"10.1109\/TIM.2018.2885608","volume":"68","author":"EQ Wu","year":"2019","unstructured":"Wu, E.Q., et al.: Pilots\u2019 fatigue status recognition using deep contractive autoencoder network. IEEE Trans. Instrum. Meas. 68(10), 3907\u20133919 (2019)","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"12_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2022.101698","volume":"53","author":"CY Yiu","year":"2022","unstructured":"Yiu, C.Y., et al.: Towards safe and collaborative aerodrome operations: assessing shared situational awareness for adverse weather detection with EEG-enabled Bayesian neural networks. Adv. Eng. Inform. 53, 101698 (2022)","journal-title":"Adv. Eng. Inform."},{"key":"12_CR26","doi-asserted-by":"crossref","unstructured":"Binias, B., et al.: Prediction of pilot's reaction time based on EEG signals. Front. Neuroinformatics 14 (2020)","DOI":"10.3389\/fninf.2020.00006"},{"issue":"5","key":"12_CR27","doi-asserted-by":"publisher","first-page":"2298","DOI":"10.3390\/app12052298","volume":"12","author":"A Hern\u00e1ndez-Sabat\u00e9","year":"2022","unstructured":"Hern\u00e1ndez-Sabat\u00e9, A., et al.: Recognition of the mental workloads of pilots in the cockpit using EEG signals. Appl. Sci. 12(5), 2298 (2022)","journal-title":"Appl. Sci."},{"issue":"1","key":"12_CR28","doi-asserted-by":"publisher","first-page":"2507","DOI":"10.1038\/s41598-023-29647-0","volume":"13","author":"H Taheri Gorji","year":"2023","unstructured":"Taheri Gorji, H., et al.: Using machine learning methods and EEG to discriminate aircraft pilot cognitive workload during flight. Sci. Rep. 13(1), 2507 (2023)","journal-title":"Sci. Rep."},{"key":"12_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.ress.2023.109449","volume":"238","author":"Q Li","year":"2023","unstructured":"Li, Q., et al.: Securing air transportation safety through identifying pilot\u2019s risky VFR flying behaviours: an EEG-based neurophysiological modelling using machine learning algorithms. Reliab. Eng. Syst. Saf. 238, 109449 (2023)","journal-title":"Reliab. Eng. Syst. Saf."},{"issue":"1","key":"12_CR30","doi-asserted-by":"publisher","first-page":"324","DOI":"10.1016\/j.bbe.2019.12.002","volume":"40","author":"S-Y Han","year":"2020","unstructured":"Han, S.-Y., et al.: Classification of pilots\u2019 mental states using a multimodal deep learning network. Biocybernet. Biomed. Eng. 40(1), 324\u2013336 (2020)","journal-title":"Biocybernet. Biomed. Eng."},{"issue":"3","key":"12_CR31","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1109\/TCDS.2019.2963476","volume":"13","author":"EQ Wu","year":"2021","unstructured":"Wu, E.Q., et al.: Detecting fatigue status of pilots based on deep learning network using EEG signals. IEEE Trans. Cognitive Developm. Syst. 13(3), 575\u2013585 (2021)","journal-title":"IEEE Trans. Cognitive Developm. Syst."},{"issue":"22","key":"12_CR32","doi-asserted-by":"publisher","first-page":"10923","DOI":"10.3390\/app112210923","volume":"11","author":"CY Yiu","year":"2021","unstructured":"Yiu, C.Y., et al.: A digital twin-based platform towards intelligent automation with virtual counterparts of Flight and Air Traffic Control Operations. Appl. Sci. 11(22), 10923 (2021)","journal-title":"Appl. Sci."},{"issue":"3","key":"12_CR33","doi-asserted-by":"publisher","first-page":"192","DOI":"10.4103\/2228-7477.161495","volume":"5","author":"M Hassani","year":"2015","unstructured":"Hassani, M., Karami, M.R.: Noise estimation in electroencephalogram signal by using volterra series coefficients. J Med Signals Sens 5(3), 192\u2013200 (2015)","journal-title":"J Med Signals Sens"},{"issue":"1","key":"12_CR34","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.jneumeth.2003.10.009","volume":"134","author":"A Delorme","year":"2004","unstructured":"Delorme, A., Makeig, S.: EEGLAB: an open-source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods 134(1), 9\u201321 (2004)","journal-title":"J. Neurosci. Methods"},{"issue":"2","key":"12_CR35","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1111\/j.1469-8986.2010.01061.x","volume":"48","author":"A Mognon","year":"2011","unstructured":"Mognon, A., et al.: ADJUST: An automatic EEG artifact detector based on the joint use of spatial and temporal features. Psychophysiology 48(2), 229\u2013240 (2011)","journal-title":"Psychophysiology"},{"key":"12_CR36","unstructured":"Sanei, S., Chambers, J.A.: EEG signal processing. John Wiley & Sons (2013)"},{"key":"12_CR37","doi-asserted-by":"publisher","first-page":"1936","DOI":"10.1109\/TNSRE.2021.3112167","volume":"29","author":"PJ Lin","year":"2021","unstructured":"Lin, P.J., et al.: CNN-Based prognosis of BCI rehabilitation using EEG from first session bci training. IEEE Trans. Neural Syst. Rehabil. Eng. 29, 1936\u20131943 (2021)","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"12_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.105242","volume":"143","author":"MT Sadiq","year":"2022","unstructured":"Sadiq, M.T., et al.: Exploiting pretrained CNN models for the development of an EEG-based robust BCI framework. Comput. Biol. Med. 143, 105242 (2022)","journal-title":"Comput. Biol. Med."},{"issue":"2","key":"12_CR39","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1016\/S0167-8760(00)00079-9","volume":"37","author":"MA Schier","year":"2000","unstructured":"Schier, M.A.: Changes in EEG alpha power during simulated driving: a demonstration. Int. J. Psychophysiol. 37(2), 155\u2013162 (2000)","journal-title":"Int. J. Psychophysiol."},{"key":"12_CR40","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/j.eswa.2018.07.054","volume":"115","author":"S Barua","year":"2019","unstructured":"Barua, S., et al.: Automatic driver sleepiness detection using EEG, EOG and contextual information. Expert Syst. Appl. 115, 121\u2013135 (2019)","journal-title":"Expert Syst. Appl."}],"container-title":["Communications in Computer and Information Science","HCI International 2025 Posters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-94153-5_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T18:24:06Z","timestamp":1757183046000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-94153-5_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031941528","9783031941535"],"references-count":40,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-94153-5_12","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"30 May 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HCII","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Human-Computer Interaction","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Gothenburg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sweden","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 June 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"hcii2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2025.hci.international\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}