{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T04:17:07Z","timestamp":1774066627987,"version":"3.50.1"},"reference-count":186,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"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":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1007\/s11517-025-03435-6","type":"journal-article","created":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T06:44:39Z","timestamp":1759214679000},"page":"27-48","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Emerging trends and clinical challenges in AI-enhanced emotion diagnosis using physiological data"],"prefix":"10.1007","volume":"64","author":[{"given":"Ying-Ying","family":"Tsai","sequence":"first","affiliation":[]},{"given":"Guan-Lin","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Yu-Jie","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Yen-Feng","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Ju-Yu","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Ching-Han","family":"Hsu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2601-3673","authenticated-orcid":false,"given":"Lun-De","family":"Liao","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,9,30]]},"reference":[{"issue":"1","key":"3435_CR1","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1037\/0003-066X.55.1.110","volume":"55","author":"P Salovey","year":"2000","unstructured":"Salovey P, Rothman AJ, Detweiler JB, Steward WT (2000) Emotional states and physical health. Am Psychol 55(1):110","journal-title":"Am Psychol"},{"key":"3435_CR2","doi-asserted-by":"crossref","unstructured":"Elder Jr GH, Conger RD, Foster EM, Ardelt M\u00a0(1992) Families under economic pressure.\u00a0J Fam Issues\u00a013(1):5\u201337","DOI":"10.1177\/019251392013001002"},{"issue":"3","key":"3435_CR3","doi-asserted-by":"publisher","first-page":"360","DOI":"10.1080\/09585190601165577","volume":"18","author":"S Lewis","year":"2007","unstructured":"Lewis S, Gambles R, Rapoport R (2007) The constraints of a \u2018work\u2013life balance\u2019approach: an international perspective. Int J Hum Resour Manage 18(3):360\u2013373","journal-title":"Int J Hum Resour Manage"},{"key":"3435_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.psychres.2020.113230","volume":"291","author":"NK Fofana","year":"2020","unstructured":"Fofana NK, Latif F, Sarfraz S, Bashir MF, Komal B (2020) Fear and agony of the pandemic leading to stress and mental illness: an emerging crisis in the novel coronavirus (COVID-19) outbreak. Psychiatr Res 291:113230","journal-title":"Psychiatr Res"},{"key":"3435_CR5","doi-asserted-by":"publisher","DOI":"10.3390\/bios12121097","volume":"12","author":"J-Y Wu","year":"2022","unstructured":"Wu J-Y, Ching CT-S, Wang H-MD, Liao L-D (2022) Emerging wearable biosensor technologies for stress monitoring and their real-world applications. Biosensors 12:1097","journal-title":"Biosensors"},{"key":"3435_CR6","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1016\/j.neubiorev.2021.04.017","volume":"127","author":"L Saccaro","year":"2021","unstructured":"Saccaro L, Schilliger Z, Dayer A, Perroud N, Piguet C (2021) Inflammation, anxiety, and stress in bipolar disorder and borderline personality disorder: a narrative review. Neurosci Biobehav Rev 127:184\u2013192","journal-title":"Neurosci Biobehav Rev"},{"key":"3435_CR7","doi-asserted-by":"crossref","unstructured":"Wu J-Y, Tsai Y-Y, Chen Y-J, Hsiao F-C, Hsu C-H, Lin Y-F, Liao L-D (2025) Digital transformation of mental health therapy by integrating digitalized cognitive behavioral therapy and eye movement desensitization and reprocessing. Med Biol Eng Comput\u00a063(2):339\u2013354","DOI":"10.1007\/s11517-024-03209-6"},{"key":"3435_CR8","unstructured":"Beck AT, Alford BA (2009) Depression: causes and treatment. University of Pennsylvania Press"},{"key":"3435_CR9","doi-asserted-by":"crossref","unstructured":"Rowa K, Waechter S, Hood HK, Antony MM (2017) Generalized anxiety disorder. Psychopathology: History, diagnosis, and empirical foundations, 3rd edn. pp 149\u2013186","DOI":"10.1002\/9781394258949.ch4"},{"key":"3435_CR10","doi-asserted-by":"publisher","unstructured":"Johnson SL, Gruber J, Eisner LR (2007) Emotion and bipolar disorder. In: Rottenberg J, Johnson SL\u00a0(eds) Emotion and psychopathology: bridging affective and clinical science. American Psychological Association, pp 123\u2013150. https:\/\/doi.org\/10.1037\/11562-006","DOI":"10.1037\/11562-006"},{"issue":"10310","key":"3435_CR11","doi-asserted-by":"publisher","first-page":"1528","DOI":"10.1016\/S0140-6736(21)00476-1","volume":"398","author":"M Bohus","year":"2021","unstructured":"Bohus M, Stoffers-Winterling J, Sharp C, Krause-Utz A, Schmahl C, Lieb K (2021) Borderline personality disorder. Lancet 398(10310):1528\u20131540","journal-title":"Lancet"},{"issue":"3","key":"3435_CR12","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1176\/appi.neuropsych.12110268","volume":"26","author":"R C\u00e1ceda","year":"2014","unstructured":"C\u00e1ceda R, Nemeroff CB, Harvey PD (2014) Toward an understanding of decision making in severe mental illness. J Neuropsychiatry Clin Neurosci 26(3):196\u2013213","journal-title":"J Neuropsychiatry Clin Neurosci"},{"issue":"1","key":"3435_CR13","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1038\/s41597-022-01361-y","volume":"9","author":"S Hosseini","year":"2022","unstructured":"Hosseini S et al (2022) A multimodal sensor dataset for continuous stress detection of nurses in a hospital. Sci Data 9(1):255","journal-title":"Sci Data"},{"key":"3435_CR14","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2021.614539","volume":"12","author":"H Kim","year":"2021","unstructured":"Kim H et al (2021) Effect of virtual reality on stress reduction and change of physiological parameters including heart rate variability in people with high stress: an open randomized crossover trial. Front Psychiatry 12:614539","journal-title":"Front Psychiatry"},{"key":"3435_CR15","unstructured":"Kumar KS, Srivastava S, Paswan S, Dutta AS (2012) Depression-symptoms, causes, medications and therapies. Pharma Innov 1(3 Part A):37"},{"key":"3435_CR16","unstructured":"Guthrie S, Podvigin S, Dzhumaeva L, AA M, Musheer M (n.d.) Anxiety and anxiety disorders: an overview. Turk J Physiother Rehabil 32:3"},{"issue":"5","key":"3435_CR17","first-page":"483","volume":"85","author":"AL Price","year":"2012","unstructured":"Price AL, Marzani-Nissen GR (2012) Bipolar disorders: a review. Am Fam Physician 85(5):483\u2013493","journal-title":"Am Fam Physician"},{"key":"3435_CR18","doi-asserted-by":"publisher","DOI":"10.2147\/NDT.S198804","author":"N Thomas","year":"2019","unstructured":"Thomas N, Gurvich C, Kulkarni J (2019) Borderline personality disorder, trauma, and the hypothalamus\u2013pituitary\u2013adrenal axis. Neuropsychiatr Dis Treat. https:\/\/doi.org\/10.2147\/NDT.S198804","journal-title":"Neuropsychiatr Dis Treat"},{"key":"3435_CR19","doi-asserted-by":"publisher","first-page":"71146","DOI":"10.1109\/ACCESS.2020.2987058","volume":"8","author":"K Zhang","year":"2020","unstructured":"Zhang K, Ling W (2020) Health monitoring of human multiple physiological parameters based on wireless remote medical system. IEEE Access 8:71146\u201371159","journal-title":"IEEE Access"},{"issue":"9","key":"3435_CR20","doi-asserted-by":"publisher","first-page":"2164","DOI":"10.3390\/s19092164","volume":"19","author":"S Majumder","year":"2019","unstructured":"Majumder S, Deen MJ (2019) Smartphone sensors for health monitoring and diagnosis. Sensors 19(9):2164","journal-title":"Sensors"},{"key":"3435_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2020.103678","volume":"92","author":"O Fink","year":"2020","unstructured":"Fink O, Wang Q, Svensen M, Dersin P, Lee W-J, Ducoffe M (2020) Potential, challenges and future directions for deep learning in prognostics and health management applications. Eng Appl Artif Intell 92:103678","journal-title":"Eng Appl Artif Intell"},{"key":"3435_CR22","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/8875426","author":"NS Suhaimi","year":"2020","unstructured":"Suhaimi NS, Mountstephens J, Teo J (2020) EEG-based emotion recognition: a state-of-the-art review of current trends and opportunities. Comput Intell Neurosci. https:\/\/doi.org\/10.1155\/2020\/8875426","journal-title":"Comput Intell Neurosci"},{"issue":"7","key":"3435_CR23","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6579\/ab998c","volume":"41","author":"E Mej\u00eda-Mej\u00eda","year":"2020","unstructured":"Mej\u00eda-Mej\u00eda E, May JM, Torres R, Kyriacou PA (2020) Pulse rate variability in cardiovascular health: a review on its applications and relationship with heart rate variability. Physiol Meas 41(7):07TR01","journal-title":"Physiol Meas"},{"key":"3435_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2023.113150","volume":"218","author":"F Scardulla","year":"2023","unstructured":"Scardulla F et al (2023) Photoplethysmograhic sensors, potential and limitations: is it time for regulation? A comprehensive review. Measurement 218:113150","journal-title":"Measurement"},{"key":"3435_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.enbuild.2020.110261","volume":"224","author":"B Yang","year":"2020","unstructured":"Yang B et al (2020) Non-invasive (non-contact) measurements of human thermal physiology signals and thermal comfort\/discomfort poses-a review. Energy Build 224:110261","journal-title":"Energy Build"},{"key":"3435_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2024.e35484","author":"W-C Kao","year":"2024","unstructured":"Kao W-C, Fan Y-L, Hsu F-R, Shen C-Y, Liao L-D (2024) Next-generation swimming pool drowning prevention strategy integrating AI and IoT technologies. Heliyon. https:\/\/doi.org\/10.1016\/j.heliyon.2024.e35484","journal-title":"Heliyon"},{"issue":"1","key":"3435_CR27","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1177\/1557234X11410385","volume":"7","author":"D Lottridge","year":"2011","unstructured":"Lottridge D, Chignell M, Jovicic A (2011) Affective interaction: understanding, evaluating, and designing for human emotion. Rev Hum Factors Ergon 7(1):197\u2013217","journal-title":"Rev Hum Factors Ergon"},{"key":"3435_CR28","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1007\/s10459-014-9516-6","volume":"20","author":"VR LeBlanc","year":"2015","unstructured":"LeBlanc VR, McConnell MM, Monteiro SD (2015) Predictable chaos: a review of the effects of emotions on attention, memory and decision making. Adv Health Sci Educ Theory Pract 20:265\u2013282","journal-title":"Adv Health Sci Educ Theory Pract"},{"key":"3435_CR29","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.inffus.2022.03.009","volume":"83","author":"Y Wang","year":"2022","unstructured":"Wang Y et al (2022) A systematic review on affective computing: emotion models, databases, and recent advances. Information Fusion 83:19\u201352","journal-title":"Information Fusion"},{"key":"3435_CR30","unstructured":"Friedewald M, Da Costa O (2003) Science and technology roadmapping: ambient intelligence in everyday life (AmI@ Life).\u00a0Working Paper.\u00a0Institute for Prospective Technology Studies IPTS, Seville, pp 1\u2013197"},{"key":"3435_CR31","first-page":"190","volume":"12","author":"N Depraz","year":"2017","unstructured":"Depraz N, Gyemant M, Desmidt T (2017) A first-person analysis using third-person data as a generative method. Construc Found 12:190\u2013203","journal-title":"Construc Found"},{"key":"3435_CR32","unstructured":"Kramsch C (1993) Context and culture in language teaching. Oxford university press"},{"issue":"2","key":"3435_CR33","doi-asserted-by":"publisher","first-page":"434","DOI":"10.1037\/0022-3514.83.2.434","volume":"83","author":"MM Herrald","year":"2002","unstructured":"Herrald MM, Tomaka J (2002) Patterns of emotion-specific appraisal, coping, and cardiovascular reactivity during an ongoing emotional episode. J Pers Soc Psychol 83(2):434","journal-title":"J Pers Soc Psychol"},{"key":"3435_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijhcs.2022.102872","volume":"166","author":"B Tag","year":"2022","unstructured":"Tag B, Sarsenbayeva Z, Cox AL, Wadley G, Goncalves J, Kostakos V (2022) Emotion trajectories in smartphone use: towards recognizing emotion regulation in-the-wild. Int J Hum Comput Stud 166:102872","journal-title":"Int J Hum Comput Stud"},{"key":"3435_CR35","unstructured":"Schwarz N, Sudman S (2012) Autobiographical memory and the validity of retrospective reports. Springer Science & Business Media"},{"issue":"2","key":"3435_CR36","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1177\/1088868316628405","volume":"21","author":"RV Palumbo","year":"2017","unstructured":"Palumbo RV et al (2017) Interpersonal autonomic physiology: a systematic review of the literature. Pers Soc Psychol Rev 21(2):99\u2013141","journal-title":"Pers Soc Psychol Rev"},{"key":"3435_CR37","unstructured":"Klarkowski MW (2017) The psychophysiological evaluation of the player experience.\u00a0Ph.D. thesis, Queensland University of Technology"},{"issue":"4","key":"3435_CR38","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3009906","volume":"49","author":"P Wiriyathammabhum","year":"2016","unstructured":"Wiriyathammabhum P, Summers-Stay D, Ferm\u00fcller C, Aloimonos Y (2016) Computer vision and natural language processing: recent approaches in multimedia and robotics. ACM Comput Surv 49(4):1\u201344","journal-title":"ACM Comput Surv"},{"key":"3435_CR39","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1109\/RBME.2021.3066072","volume":"16","author":"V Skaramagkas","year":"2021","unstructured":"Skaramagkas V et al (2021) Review of eye tracking metrics involved in emotional and cognitive processes. IEEE Rev Biomed Eng 16:260\u2013277","journal-title":"IEEE Rev Biomed Eng"},{"issue":"3","key":"3435_CR40","doi-asserted-by":"publisher","first-page":"217","DOI":"10.3390\/jsan1030217","volume":"1","author":"M Swan","year":"2012","unstructured":"Swan M (2012) Sensor mania! the internet of things, wearable computing, objective metrics, and the quantified self 2.0. J Sens Actuator Netw 1(3):217\u2013253","journal-title":"J Sens Actuator Netw"},{"issue":"17","key":"3435_CR41","doi-asserted-by":"publisher","DOI":"10.3390\/s19173805","volume":"19","author":"K Kyriakou","year":"2019","unstructured":"Kyriakou K et al (2019) Detecting moments of stress from measurements of wearable physiological sensors. Sensors 19(17):3805","journal-title":"Sensors"},{"key":"3435_CR42","unstructured":"Clark DA, Beck AT (2011) Cognitive therapy of anxiety disorders: science and practice. Guilford Press"},{"key":"3435_CR43","unstructured":"Hilton CL, Kramer J (2019) Assessment and intervention of social participation and social skills.\u00a0Case-Smith\u2019s occupational therapy for children and adolescents. pp 338\u2013340"},{"key":"3435_CR44","doi-asserted-by":"publisher","unstructured":"Janelle CM, Fawver BJ, Beatty GF (2020) Emotion and sport performance. In: Tenenbaum G,\u00a0Eklund RC,\u00a0Boiangin N (eds)\u00a0Handbook of sport psychology: Social perspectives, cognition, and applications, 4th edn. John Wiley & Sons, Inc., pp 254\u2013298.\u00a0https:\/\/doi.org\/10.1002\/9781119568124.ch13","DOI":"10.1002\/9781119568124.ch13"},{"key":"3435_CR45","unstructured":"Wen M, Yang D, Rose C (2014) Sentiment analysis in MOOC discussion forums: what does it tell us?. In: Educational data mining 2014, Citeseer"},{"key":"3435_CR46","unstructured":"Panksepp J (2004) Affective neuroscience: the foundations of human and animal emotions. Oxford University Press"},{"issue":"2\u20133","key":"3435_CR47","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/S0165-0173(97)00064-7","volume":"26","author":"AR Damasio","year":"1998","unstructured":"Damasio AR (1998) Emotion in the perspective of an integrated nervous system. Brain Res Rev 26(2\u20133):83\u201386","journal-title":"Brain Res Rev"},{"key":"3435_CR48","unstructured":"Ekman PE, Davidson RJ (1994) The nature of emotion: fundamental questions. Oxford University Press"},{"issue":"2","key":"3435_CR49","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/S0376-6357(02)00078-5","volume":"60","author":"M Cabanac","year":"2002","unstructured":"Cabanac M (2002) What is emotion? Behav Processes 60(2):69\u201383","journal-title":"Behav Processes"},{"issue":"2","key":"3435_CR50","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1111\/1467-6494.00058","volume":"67","author":"JR Averill","year":"1999","unstructured":"Averill JR (1999) Individual differences in emotional creativity: structure and correlates. J Personality 67(2):331\u2013371","journal-title":"J Personality"},{"key":"3435_CR51","unstructured":"Cuza AI (2022)\u00a0Privacy and mutual authentication under temporary state disclosure in RFID systems"},{"key":"3435_CR52","doi-asserted-by":"crossref","unstructured":"Picard RW (2000) Affective computing. MIT press","DOI":"10.1007\/978-3-540-45012-2_2"},{"key":"3435_CR53","unstructured":"Fleckenstein KS (1997) Defining affect in relation to cognition: a response to Susan McLeod. J Adv Compos pp 447\u2013453"},{"issue":"3","key":"3435_CR54","doi-asserted-by":"publisher","first-page":"1590","DOI":"10.1109\/TCE.2009.5278031","volume":"55","author":"J-S Park","year":"2009","unstructured":"Park J-S, Kim J-H, Oh Y-H (2009) Feature vector classification based speech emotion recognition for service robots. IEEE Trans Consum Electron 55(3):1590\u20131596","journal-title":"IEEE Trans Consum Electron"},{"issue":"4","key":"3435_CR55","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1109\/T-AFFC.2012.29","volume":"3","author":"M Scheutz","year":"2012","unstructured":"Scheutz M (2012) The affect dilemma for artificial agents: should we develop affective artificial agents? IEEE Trans Affect Comput 3(4):424\u2013433","journal-title":"IEEE Trans Affect Comput"},{"key":"3435_CR56","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1007\/s10846-015-0259-2","volume":"82","author":"D McColl","year":"2016","unstructured":"McColl D, Hong A, Hatakeyama N, Nejat G, Benhabib B (2016) A survey of autonomous human affect detection methods for social robots engaged in natural HRI. J Intell Robot Syst 82:101\u2013133","journal-title":"J Intell Robot Syst"},{"issue":"2","key":"3435_CR57","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1109\/TAFFC.2014.2317187","volume":"5","author":"M Munezero","year":"2014","unstructured":"Munezero M, Montero CS, Sutinen E, Pajunen J (2014) Are they different? Affect, feeling, emotion, sentiment, and opinion detection in text. IEEE Trans Affect Comput 5(2):101\u2013111","journal-title":"IEEE Trans Affect Comput"},{"key":"3435_CR58","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.inffus.2017.02.003","volume":"37","author":"S Poria","year":"2017","unstructured":"Poria S, Cambria E, Bajpai R, Hussain A (2017) A review of affective computing: from unimodal analysis to multimodal fusion. Inf Fusion 37:98\u2013125","journal-title":"Inf Fusion"},{"issue":"2","key":"3435_CR59","doi-asserted-by":"publisher","first-page":"524","DOI":"10.1109\/TAFFC.2018.2890471","volume":"12","author":"PV Rouast","year":"2019","unstructured":"Rouast PV, Adam MT, Chiong R (2019) Deep learning for human affect recognition: insights and new developments. IEEE Trans Affect Comput 12(2):524\u2013543","journal-title":"IEEE Trans Affect Comput"},{"key":"3435_CR60","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2019.102447","volume":"149","author":"NJ Shoumy","year":"2020","unstructured":"Shoumy NJ, Ang L-M, Seng KP, Rahaman DM, Zia T (2020) Multimodal big data affective analytics: a comprehensive survey using text, audio, visual and physiological signals. J Netw Comput Appl 149:102447","journal-title":"J Netw Comput Appl"},{"issue":"3","key":"3435_CR61","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1177\/1754073912439763","volume":"4","author":"WA Mason","year":"2012","unstructured":"Mason WA, Capitanio JP (2012) Basic emotions: a reconstruction. Emot Rev 4(3):238\u2013244","journal-title":"Emot Rev"},{"key":"3435_CR62","unstructured":"Mehrabian A (1980) Basic dimensions for a general psychological theory: implications for personality, social, environmental, and developmental studies"},{"issue":"4","key":"3435_CR63","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1111\/j.1460-2466.1972.tb00163.x","volume":"22","author":"P Ekman","year":"1972","unstructured":"Ekman P, Friesen WV (1972) Hand movements. J Commun 22(4):353\u2013374","journal-title":"J Commun"},{"issue":"3\u20134","key":"3435_CR64","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1080\/02699939208411068","volume":"6","author":"P Ekman","year":"1992","unstructured":"Ekman P (1992) An argument for basic emotions. Cogn Emot 6(3\u20134):169\u2013200","journal-title":"Cogn Emot"},{"key":"3435_CR65","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.patcog.2018.01.035","volume":"79","author":"A Mohanty","year":"2018","unstructured":"Mohanty A, Sahay RR (2018) Rasabodha: understanding Indian classical dance by recognizing emotions using deep learning. Pattern Recogn 79:97\u2013113","journal-title":"Pattern Recogn"},{"issue":"10","key":"3435_CR66","doi-asserted-by":"publisher","first-page":"1193","DOI":"10.1002\/(SICI)1097-4679(199910)55:10<1193::AID-JCLP3>3.0.CO;2-I","volume":"55","author":"HJ Hermans","year":"1999","unstructured":"Hermans HJ (1999) Self-narrative as meaning construction: the dynamics of self-investigation. J Clin Psychol 55(10):1193\u20131211","journal-title":"J Clin Psychol"},{"key":"3435_CR67","doi-asserted-by":"publisher","DOI":"10.2307\/351556","author":"CI Notarius","year":"1982","unstructured":"Notarius CI, Johnson JS (1982) Emotional expression in husbands and wives. J Marriage Fam. https:\/\/doi.org\/10.2307\/351556","journal-title":"J Marriage Fam"},{"key":"3435_CR68","doi-asserted-by":"crossref","unstructured":"Shaffer David R (1994) Social and personality development. Cole Publishing Company, Pacific Grove, CA: Brooks.\u00a0Van Acker R, Wehby HJ (2000) Exploring the social contexts influencing student success or failure: Introduction. Preventing School Failure 44(3):93\u201397","DOI":"10.1080\/10459880009599789"},{"issue":"2","key":"3435_CR69","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1037\/0882-7974.2.2.193","volume":"2","author":"CZ Malatesta","year":"1987","unstructured":"Malatesta CZ, Izard CE, Culver C, Nicolich M (1987) Emotion communication skills in young, middle-aged, and older women. Psychol Aging 2(2):193","journal-title":"Psychol Aging"},{"key":"3435_CR70","doi-asserted-by":"publisher","DOI":"10.2307\/1166153","author":"CZ Malatesta","year":"1989","unstructured":"Malatesta CZ et al (1989) The development of emotion expression during the first two years of life. Monogr Soc Res Child Dev. https:\/\/doi.org\/10.2307\/1166153","journal-title":"Monogr Soc Res Child Dev"},{"issue":"4","key":"3435_CR71","doi-asserted-by":"publisher","first-page":"397","DOI":"10.1177\/1754073911410747","volume":"3","author":"JL Tracy","year":"2011","unstructured":"Tracy JL, Randles D (2011) Four models of basic emotions: a review of Ekman and Cordaro, Izard, Levenson, and Panksepp and Watt. Emot Rev 3(4):397\u2013405","journal-title":"Emot Rev"},{"key":"3435_CR72","first-page":"161","volume":"158","author":"S D\u2019mello","year":"2007","unstructured":"D\u2019mello S, Graesser A (2007) Mind and body: dialogue and posture for affect detection in learning environments. Front Artif Intell Appl 158:161","journal-title":"Front Artif Intell Appl"},{"issue":"11","key":"3435_CR73","doi-asserted-by":"publisher","first-page":"2797","DOI":"10.1007\/s11517-023-02903-1","volume":"61","author":"Y-L Fan","year":"2023","unstructured":"Fan Y-L, Hsu F-R, Wang Y, Liao L-D (2023) Unlocking the potential of zebrafish research with artificial intelligence: advancements in tracking, processing, and visualization. Med Biol Eng Comput 61(11):2797\u20132814","journal-title":"Med Biol Eng Comput"},{"issue":"8","key":"3435_CR74","first-page":"651","volume":"10","author":"S Ps","year":"2017","unstructured":"Ps S, Mahalakshmi G (2017) Emotion models: a review. Int J Control Theory Appl 10(8):651\u2013657","journal-title":"Int J Control Theory Appl"},{"key":"3435_CR75","unstructured":"Plutchik R (2003) Emotions and life: perspectives from psychology, biology, and evolution. American Psychological Association"},{"key":"3435_CR76","doi-asserted-by":"crossref","unstructured":"Thayer RE (1990) The biopsychology of mood and arousal. Oxford University Press","DOI":"10.1093\/oso\/9780195068276.001.0001"},{"key":"3435_CR77","doi-asserted-by":"crossref","unstructured":"Yeh C-H, Lin H-H, Chang H-T (2009) An efficient emotion detection scheme for popular music. In: 2009 IEEE International Symposium on Circuits and Systems, IEEE, pp 1799\u20131802","DOI":"10.1109\/ISCAS.2009.5118126"},{"key":"3435_CR78","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1007\/BF02229025","volume":"19","author":"A Mehrabian","year":"1997","unstructured":"Mehrabian A (1997) Comparison of the PAD and PANAS as models for describing emotions and for differentiating anxiety from depression. J Psychopathol Behav Assess 19:331\u2013357","journal-title":"J Psychopathol Behav Assess"},{"issue":"6","key":"3435_CR79","doi-asserted-by":"publisher","first-page":"1161","DOI":"10.1037\/h0077714","volume":"39","author":"JA Russell","year":"1980","unstructured":"Russell JA (1980) A circumplex model of affect. J Pers Soc Psychol 39(6):1161","journal-title":"J Pers Soc Psychol"},{"key":"3435_CR80","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/B978-0-12-558704-4.50011-6","volume-title":"The measurement of emotions","author":"CM Whissell","year":"1989","unstructured":"Whissell CM (1989) The dictionary of affect in language. The measurement of emotions. Elsevier, pp 113\u2013131"},{"key":"3435_CR81","doi-asserted-by":"crossref","unstructured":"Hupont I, Cerezo E, Baldassarri S (2010) Sensing facial emotions in a continuous 2D affective space. In: 2010 IEEE International Conference on Systems, Man and Cybernetics. IEEE, pp 2045\u20132051","DOI":"10.1109\/ICSMC.2010.5641717"},{"key":"3435_CR82","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.neucom.2012.01.030","volume":"92","author":"J Ortigosa-Hern\u00e1ndez","year":"2012","unstructured":"Ortigosa-Hern\u00e1ndez J, Rodr\u00edguez JD, Alzate L, Lucania M, Inza I, Lozano JA (2012) Approaching sentiment analysis by using semi-supervised learning of multi-dimensional classifiers. Neurocomputing 92:98\u2013115","journal-title":"Neurocomputing"},{"issue":"11","key":"3435_CR83","doi-asserted-by":"publisher","first-page":"1392","DOI":"10.1111\/j.1540-8159.2010.02838.x","volume":"33","author":"O Monfredi","year":"2010","unstructured":"Monfredi O, Dobrzynski H, Mondal T, Boyett MR, Morris GM (2010) The anatomy and physiology of the sinoatrial node\u2014a contemporary review. Pacing Clin Electrophysiol 33(11):1392\u20131406","journal-title":"Pacing Clin Electrophysiol"},{"key":"3435_CR84","doi-asserted-by":"publisher","first-page":"308","DOI":"10.1007\/s40806-016-0065-5","volume":"2","author":"M Richardson","year":"2016","unstructured":"Richardson M, McEwan K, Maratos F, Sheffield D (2016) Joy and calm: how an evolutionary functional model of affect regulation informs positive emotions in nature. Evol Psychol Sci 2:308\u2013320","journal-title":"Evol Psychol Sci"},{"issue":"3","key":"3435_CR85","doi-asserted-by":"publisher","first-page":"H469","DOI":"10.1152\/ajpheart.00507.2016","volume":"312","author":"LEV Silva","year":"2017","unstructured":"Silva LEV, Silva CAA, Salgado HC, Fazan R Jr (2017) The role of sympathetic and vagal cardiac control on complexity of heart rate dynamics. American Journal of Physiology-Heart and Circulatory Physiology 312(3):H469\u2013H477","journal-title":"American Journal of Physiology-Heart and Circulatory Physiology"},{"issue":"15","key":"3435_CR86","doi-asserted-by":"publisher","DOI":"10.1161\/JAHA.118.009351","volume":"7","author":"AG Bonomi","year":"2018","unstructured":"Bonomi AG et al (2018) Atrial fibrillation detection using a novel cardiac ambulatory monitor based on photo-plethysmography at the wrist. J Am Heart Assoc 7(15):e009351","journal-title":"J Am Heart Assoc"},{"issue":"4","key":"3435_CR87","doi-asserted-by":"publisher","first-page":"1511","DOI":"10.1002\/j.2040-4603.2014.tb00589.x","volume":"4","author":"PG Guyenet","year":"2014","unstructured":"Guyenet PG (2014) Regulation of breathing and autonomic outflows by chemoreceptors. Compr Physiol 4(4):1511","journal-title":"Compr Physiol"},{"issue":"2","key":"3435_CR88","doi-asserted-by":"publisher","DOI":"10.3390\/bios14020090","volume":"14","author":"D Vitazkova","year":"2024","unstructured":"Vitazkova D et al (2024) Advances in respiratory monitoring: a comprehensive review of wearable and remote technologies. Biosensors 14(2):90","journal-title":"Biosensors"},{"key":"3435_CR89","doi-asserted-by":"crossref","unstructured":"Porges SW (1986) Respiratory sinus arrhythmia: physiological basis, quantitative methods, and clinical implications. In: Cardiorespiratory and cardiosomatic psychophysiology. Springer, pp 101\u2013115","DOI":"10.1007\/978-1-4757-0360-3_7"},{"issue":"2","key":"3435_CR90","doi-asserted-by":"publisher","first-page":"683","DOI":"10.1378\/chest.125.2.683","volume":"125","author":"F Yasuma","year":"2004","unstructured":"Yasuma F, Hayano J-I (2004) Respiratory sinus arrhythmia: why does the heartbeat synchronize with respiratory rhythm? Chest 125(2):683\u2013690","journal-title":"Chest"},{"key":"3435_CR91","doi-asserted-by":"publisher","DOI":"10.3389\/fphys.2016.00460","volume":"7","author":"T Penzel","year":"2016","unstructured":"Penzel T et al (2016) Modulations of heart rate, ECG, and cardio-respiratory coupling observed in polysomnography. Front Physiol 7:460","journal-title":"Front Physiol"},{"issue":"15","key":"3435_CR92","doi-asserted-by":"publisher","first-page":"2272","DOI":"10.2174\/092986711795656081","volume":"18","author":"VM Costa","year":"2011","unstructured":"Costa VM, Carvalho F, Bastos ML, Carvalho RA, Carvalho M, Remiao F (2011) Contribution of catecholamine reactive intermediates and oxidative stress to the pathologic features of heart diseases. Curr Med Chem 18(15):2272\u20132314","journal-title":"Curr Med Chem"},{"issue":"12","key":"3435_CR93","doi-asserted-by":"publisher","first-page":"1378","DOI":"10.1037\/bul0000119","volume":"143","author":"LY Busch","year":"2017","unstructured":"Busch LY, P\u00f6ssel P, Valentine JC (2017) Meta-analyses of cardiovascular reactivity to rumination: a possible mechanism linking depression and hostility to cardiovascular disease. Psychol Bull 143(12):1378","journal-title":"Psychol Bull"},{"issue":"1","key":"3435_CR94","doi-asserted-by":"publisher","DOI":"10.1080\/08037051.2024.2304190","volume":"33","author":"B Henry","year":"2024","unstructured":"Henry B, Merz M, Hoang H, Abdulkarim G, Wosik J, Schoettker P (2024) Cuffless blood pressure in clinical practice: challenges, opportunities and current limits. Blood Press 33(1):2304190","journal-title":"Blood Press"},{"issue":"9","key":"3435_CR95","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1111\/exd.12773","volume":"24","author":"CY Cui","year":"2015","unstructured":"Cui CY, Schlessinger D (2015) Eccrine sweat gland development and sweat secretion. Exp Dermatol 24(9):644\u2013650","journal-title":"Exp Dermatol"},{"issue":"4","key":"3435_CR96","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1111\/jcpp.13734","volume":"64","author":"KL Burkhouse","year":"2023","unstructured":"Burkhouse KL, Kujawa A (2023) Annual research review: emotion processing in offspring of mothers with depression diagnoses\u2013a systematic review of neural and physiological research. J Child Psychol Psychiatry 64(4):583\u2013607","journal-title":"J Child Psychol Psychiatry"},{"key":"3435_CR97","doi-asserted-by":"crossref","unstructured":"Lang PJ (2019) The cognitive psychophysiology of emotion: fear and anxiety. In: Anxiety and the anxiety disorders. Routledge, pp 131\u2013170","DOI":"10.4324\/9780203728215-10"},{"key":"3435_CR98","doi-asserted-by":"publisher","unstructured":"Jachs B (2021) The neurophenomenology of meditative states: introducing temporal experience tracing to capture subjective experience states and their neural correlates.\u00a0Apollo, University of Cambridge Repository.\u00a0https:\/\/doi.org\/10.17863\/CAM.80153","DOI":"10.17863\/CAM.80153"},{"issue":"9","key":"3435_CR99","doi-asserted-by":"publisher","first-page":"1295","DOI":"10.1111\/psyp.12878","volume":"54","author":"D Adolph","year":"2017","unstructured":"Adolph D, von Glischinski M, Wannem\u00fcller A, Margraf J (2017) The influence of frontal alpha-asymmetry on the processing of approach-and withdrawal-related stimuli\u2014a multichannel psychophysiology study. Psychophysiology 54(9):1295\u20131310","journal-title":"Psychophysiology"},{"key":"3435_CR100","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/S0079-6123(06)56002-9","volume":"156","author":"HT Schupp","year":"2006","unstructured":"Schupp HT, Flaisch T, Stockburger J, Jungh\u00f6fer M (2006) Emotion and attention: event-related brain potential studies. Prog Brain Res 156:31\u201351","journal-title":"Prog Brain Res"},{"issue":"3","key":"3435_CR101","doi-asserted-by":"publisher","DOI":"10.3390\/brainsci15030220","volume":"15","author":"E Gkintoni","year":"2025","unstructured":"Gkintoni E, Aroutzidis A, Antonopoulou H, Halkiopoulos C (2025) From neural networks to emotional networks: a systematic review of EEG-based emotion recognition in cognitive neuroscience and real-world applications. Brain Sci 15(3):220","journal-title":"Brain Sci"},{"issue":"5","key":"3435_CR102","doi-asserted-by":"publisher","first-page":"1196","DOI":"10.1213\/01.ane.0000247964.47706.5d","volume":"103","author":"G Takla","year":"2006","unstructured":"Takla G, Petre JH, Doyle DJ, Horibe M, Gopakumaran B (2006) The problem of artifacts in patient monitor data during surgery: a clinical and methodological review. Anesth Analg 103(5):1196\u20131204","journal-title":"Anesth Analg"},{"issue":"3","key":"3435_CR103","doi-asserted-by":"publisher","DOI":"10.1002\/ett.3710","volume":"33","author":"M Hartmann","year":"2022","unstructured":"Hartmann M, Hashmi US, Imran A (2022) Edge computing in smart health care systems: review, challenges, and research directions. Trans Emerging Telecommun Technol 33(3):e3710","journal-title":"Trans Emerging Telecommun Technol"},{"key":"3435_CR104","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1016\/j.inffus.2023.02.028","volume":"95","author":"L Zhu","year":"2023","unstructured":"Zhu L, Zhu Z, Zhang C, Xu Y, Kong X (2023) Multimodal sentiment analysis based on fusion methods: a survey. Inf Fusion 95:306\u2013325","journal-title":"Inf Fusion"},{"key":"3435_CR105","doi-asserted-by":"publisher","DOI":"10.1063\/5.0256590","author":"Y-Y Tsai","year":"2025","unstructured":"Tsai Y-Y, Chen Y-J, Lin Y-F, Hsiao F-C, Hsu C-H, Liao L-D (2025) Photoplethysmography-based HRV analysis and machine learning for real-time stress quantification in mental health applications. APL Bioeng. https:\/\/doi.org\/10.1063\/5.0256590","journal-title":"APL Bioeng"},{"issue":"10","key":"3435_CR106","doi-asserted-by":"publisher","first-page":"1849","DOI":"10.1185\/03007995.2015.1074065","volume":"31","author":"AdO Pinheiro","year":"2015","unstructured":"Pinheiro AdO, Pereira VL Jr, Baltatu OC, Campos LA (2015) Cardiac autonomic dysfunction in elderly women with myocardial infarction. Curr Med Res Opin 31(10):1849\u20131854","journal-title":"Curr Med Res Opin"},{"key":"3435_CR107","doi-asserted-by":"publisher","first-page":"258","DOI":"10.3389\/fpubh.2017.00258","volume":"5","author":"F Shaffer","year":"2017","unstructured":"Shaffer F, Ginsberg JP (2017) An overview of heart rate variability metrics and norms. Front Public Health 5:258","journal-title":"Front Public Health"},{"issue":"5","key":"3435_CR108","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1089\/tmj.2014.0104","volume":"21","author":"HJ Baek","year":"2015","unstructured":"Baek HJ, Cho C-H, Cho J, Woo J-M (2015) Reliability of ultra-short-term analysis as a surrogate of standard 5-min analysis of heart rate variability. Telemed e-Health 21(5):404\u2013414","journal-title":"Telemed e-Health"},{"issue":"2","key":"3435_CR109","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1111\/j.1542-474X.2011.00426.x","volume":"16","author":"AM Hekkala","year":"2011","unstructured":"Hekkala AM, Swan H, Viitasalo M, V\u00e4\u00e4n\u00e4nen H, Toivonen L (2011) Epinephrine bolus test in detecting long QT syndrome mutation carriers with indeterminable electrocardiographic phenotype. Ann Noninvasive Electrocardiol 16(2):172\u2013179","journal-title":"Ann Noninvasive Electrocardiol"},{"key":"3435_CR110","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1007\/s00421-016-3401-3","volume":"116","author":"SW Weinschenk","year":"2016","unstructured":"Weinschenk SW, Beise RD, Lorenz J (2016) Heart rate variability (HRV) in deep breathing tests and 5-min short-term recordings: agreement of ear photoplethysmography with ECG measurements, in 343 subjects. Eur J Appl Physiol 116:1527\u20131535","journal-title":"Eur J Appl Physiol"},{"key":"3435_CR111","unstructured":"Tully J (2021) Investigating the effect of oxytocin and the neurochemistry of antisocial personality disorder and psychopathy using neuroimaging. King\u2019s College London"},{"issue":"1","key":"3435_CR112","doi-asserted-by":"publisher","first-page":"4825","DOI":"10.1038\/s41598-020-61576-0","volume":"10","author":"M Kumar","year":"2020","unstructured":"Kumar M, Suliburk JW, Veeraraghavan A, Sabharwal A (2020) Pulsecam: a camera-based, motion-robust and highly sensitive blood perfusion imaging modality. Sci Rep 10(1):4825","journal-title":"Sci Rep"},{"issue":"1","key":"3435_CR113","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1186\/s12938-023-01100-3","volume":"22","author":"B Deka","year":"2023","unstructured":"Deka B, Deka D (2023) Nonlinear analysis of heart rate variability signals in meditative state: a review and perspective. BioMed Eng Online 22(1):35","journal-title":"BioMed Eng Online"},{"key":"3435_CR114","unstructured":"Asgari Mehrabadi M (2022) Holistic health monitoring and personalized intervention for well-being promotion. UC Irvine"},{"issue":"8","key":"3435_CR115","doi-asserted-by":"publisher","DOI":"10.2196\/12832","volume":"21","author":"BM Booth","year":"2019","unstructured":"Booth BM et al (2019) Multimodal human and environmental sensing for longitudinal behavioral studies in naturalistic settings: framework for sensor selection, deployment, and management. J Med Internet Res 21(8):e12832","journal-title":"J Med Internet Res"},{"key":"3435_CR116","doi-asserted-by":"publisher","first-page":"366","DOI":"10.1109\/TBME.1973.324231","volume":"5","author":"DP Golden","year":"1973","unstructured":"Golden DP, Wolthuis RA, Hoffler G (1973) A spectral analysis of the normal resting electrocardiogram. IEEE Trans Biomed Eng 5:366\u2013372","journal-title":"IEEE Trans Biomed Eng"},{"key":"3435_CR117","unstructured":"Cakmak AS (2021) Disease state prediction using multiscale dynamics"},{"issue":"5","key":"3435_CR118","doi-asserted-by":"publisher","first-page":"492","DOI":"10.1111\/j.1469-8986.1995.tb02101.x","volume":"32","author":"DA Litvack","year":"1995","unstructured":"Litvack DA, Oberlander TF, Carney LH, Saul JP (1995) Time and frequency domain methods for heart rate variability analysis: a methodological comparison. Psychophysiology 32(5):492\u2013504","journal-title":"Psychophysiology"},{"key":"3435_CR119","volume-title":"Signal processing methods for heart rate variability","author":"G Clifford","year":"2002","unstructured":"Clifford G (2002) Signal processing methods for heart rate variability. Oxford University, UK"},{"issue":"30","key":"3435_CR120","doi-asserted-by":"publisher","first-page":"1974","DOI":"10.1093\/eurheartj\/ehv087","volume":"36","author":"JS Floras","year":"2015","unstructured":"Floras JS, Ponikowski P (2015) The sympathetic\/parasympathetic imbalance in heart failure with reduced ejection fraction. Eur Heart J 36(30):1974\u20131982","journal-title":"Eur Heart J"},{"issue":"11","key":"3435_CR121","doi-asserted-by":"publisher","DOI":"10.1111\/eci.13174","volume":"49","author":"AA Khan","year":"2019","unstructured":"Khan AA, Lip GY, Shantsila A (2019) Heart rate variability in atrial fibrillation: the balance between sympathetic and parasympathetic nervous system. Eur J Clin Invest 49(11):e13174","journal-title":"Eur J Clin Invest"},{"issue":"6","key":"3435_CR122","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1002\/clc.23190","volume":"42","author":"M Qin","year":"2019","unstructured":"Qin M, Zeng C, Liu X (2019) The cardiac autonomic nervous system: a target for modulation of atrial fibrillation. Clin Cardiol 42(6):644\u2013652","journal-title":"Clin Cardiol"},{"key":"3435_CR123","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 PR, Cunha JP, Aguiar A (2017) Heart rate variability metrics for fine-grained stress level assessment. Comput Methods Programs Biomed 148:71\u201380","journal-title":"Comput Methods Programs Biomed"},{"issue":"2","key":"3435_CR124","first-page":"63","volume":"22","author":"E Tharion","year":"2009","unstructured":"Tharion E, Parthasarathy S, Neelakantan N (2009) Short-term heart rate variability measures in students during examinations. Natl Med J India 22(2):63\u201366","journal-title":"Natl Med J India"},{"key":"3435_CR125","doi-asserted-by":"crossref","unstructured":"Arza A, Garz\u00f3n J, Hemando A, Aguil\u00f3 J, Bail\u00f3n R (2015) Towards an objective measurement of emotional stress: preliminary analysis based on heart rate variability. In: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, pp 3331\u20133334","DOI":"10.1109\/EMBC.2015.7319105"},{"issue":"1","key":"3435_CR126","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1161\/hy0102.100784","volume":"39","author":"D Lucini","year":"2002","unstructured":"Lucini D, Norbiato G, Clerici M, Pagani M (2002) Hemodynamic and autonomic adjustments to real life conditions involving stress in humans. Hypertension 39(1):184\u2013188","journal-title":"Hypertension"},{"key":"3435_CR127","doi-asserted-by":"publisher","first-page":"1035","DOI":"10.1007\/s00421-009-1310-4","volume":"108","author":"E Filaire","year":"2010","unstructured":"Filaire E, Portier H, Massart A, Ramat L, Teixeira A (2010) Effect of lecturing to 200 students on heart rate variability and alpha-amylase activity. Eur J Appl Physiol 108:1035\u20131043","journal-title":"Eur J Appl Physiol"},{"key":"3435_CR128","first-page":"286","volume":"5","author":"CK Endukuru","year":"2016","unstructured":"Endukuru CK, Tripathi S (2016) Evaluation of cardiac responses to stress in healthy individuals-a non invasive evaluation by heart rate variability and stroop test. Int J Sci Res 5:286\u2013289","journal-title":"Int J Sci Res"},{"issue":"5","key":"3435_CR129","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1097\/PSY.0000000000000306","volume":"78","author":"NL Sin","year":"2016","unstructured":"Sin NL, Sloan RP, McKinley PS, Almeida DM (2016) Linking daily stress processes and laboratory-based heart rate variability in a national sample of midlife and older adults. Psychosom Med 78(5):573\u2013582","journal-title":"Psychosom Med"},{"key":"3435_CR130","doi-asserted-by":"publisher","first-page":"12134","DOI":"10.1109\/ACCESS.2021.3051281","volume":"9","author":"M Khateeb","year":"2021","unstructured":"Khateeb M, Anwar SM, Alnowami M (2021) Multi-domain feature fusion for emotion classification using DEAP dataset. IEEE Access 9:12134\u201312142","journal-title":"IEEE Access"},{"key":"3435_CR131","doi-asserted-by":"crossref","unstructured":"Wiem MBH, Lachiri Z (2017) Emotion classification in arousal valence model using MAHNOB-HCI database. Int J Adv Comput Sci Appl 8(3)","DOI":"10.14569\/IJACSA.2017.080344"},{"issue":"2","key":"3435_CR132","doi-asserted-by":"publisher","first-page":"479","DOI":"10.1109\/TAFFC.2018.2884461","volume":"12","author":"JA Miranda-Correa","year":"2018","unstructured":"Miranda-Correa JA, Abadi MK, Sebe N, Patras I (2018) Amigos: a dataset for affect, personality and mood research on individuals and groups. IEEE Trans Affect Comput 12(2):479\u2013493","journal-title":"IEEE Trans Affect Comput"},{"issue":"1","key":"3435_CR133","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1109\/JBHI.2017.2688239","volume":"22","author":"S Katsigiannis","year":"2017","unstructured":"Katsigiannis S, Ramzan N (2017) DREAMER: a database for emotion recognition through EEG and ECG signals from wireless low-cost off-the-shelf devices. IEEE J Biomed Health Inform 22(1):98\u2013107","journal-title":"IEEE J Biomed Health Inform"},{"key":"3435_CR134","doi-asserted-by":"crossref","unstructured":"Schmidt P, Reiss A, Duerichen R, Marberger C, Van Laerhoven K (2018) Introducing wesad, a multimodal dataset for wearable stress and affect detection. In: Proceedings of the 20th ACM international conference on multimodal interaction, pp 400\u2013408","DOI":"10.1145\/3242969.3242985"},{"key":"3435_CR135","doi-asserted-by":"crossref","unstructured":"Koldijk S, Sappelli M, Verberne S, Neerincx MA, Kraaij W (2014) The swell knowledge work dataset for stress and user modeling research. In: Proceedings of the 16th international conference on multimodal interaction, pp 291\u2013298","DOI":"10.1145\/2663204.2663257"},{"issue":"2","key":"3435_CR136","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1109\/TAFFC.2016.2625250","volume":"9","author":"R Subramanian","year":"2016","unstructured":"Subramanian R, Wache J, Abadi MK, Vieriu RL, Winkler S, Sebe N (2016) Ascertain: emotion and personality recognition using commercial sensors. IEEE Trans Affect Comput 9(2):147\u2013160","journal-title":"IEEE Trans Affect Comput"},{"key":"3435_CR137","unstructured":"V\u00e4yrynen E (2014) Emotion recognition from speech using prosodic features"},{"issue":"22","key":"3435_CR138","doi-asserted-by":"publisher","DOI":"10.3390\/s21227665","volume":"21","author":"C Luna-Jim\u00e9nez","year":"2021","unstructured":"Luna-Jim\u00e9nez C, Griol D, Callejas Z, Kleinlein R, Montero JM, Fern\u00e1ndez-Mart\u00ednez F (2021) Multimodal emotion recognition on RAVDESS dataset using transfer learning. Sensors 21(22):7665","journal-title":"Sensors"},{"key":"3435_CR139","doi-asserted-by":"crossref","unstructured":"Sun C, Shrivastava A, Singh S, Gupta A (2017) Revisiting unreasonable effectiveness of data in deep learning era. in Proceedings of the IEEE international conference on computer vision, pp 843\u2013852","DOI":"10.1109\/ICCV.2017.97"},{"key":"3435_CR140","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1109\/ACCESS.2018.2883213","volume":"7","author":"L Santamaria-Granados","year":"2018","unstructured":"Santamaria-Granados L, Munoz-Organero M, Ramirez-Gonzalez G, Abdulhay E, Arunkumar N (2018) Using deep convolutional neural network for emotion detection on a physiological signals dataset (AMIGOS). IEEE Access 7:57\u201367","journal-title":"IEEE Access"},{"key":"3435_CR141","doi-asserted-by":"crossref","unstructured":"Kumar S, SP S (2024) Parallel-way: multi-modality-based brain tumor segmentation using parallel capsule network. Electromagn Biol Med 43(4):267\u2013291","DOI":"10.1080\/15368378.2024.2390058"},{"key":"3435_CR142","doi-asserted-by":"publisher","first-page":"106620","DOI":"10.1109\/ACCESS.2023.3318015","volume":"11","author":"K Zaman","year":"2023","unstructured":"Zaman K, Sah M, Direkoglu C, Unoki M (2023) A survey of audio classification using deep learning. IEEE Access 11:106620\u2013106649","journal-title":"IEEE Access"},{"issue":"11","key":"3435_CR143","doi-asserted-by":"publisher","first-page":"5585","DOI":"10.1109\/TIP.2018.2852503","volume":"27","author":"Y Peng","year":"2018","unstructured":"Peng Y, Qi J, Yuan Y (2018) Modality-specific cross-modal similarity measurement with recurrent attention network. IEEE Trans Image Process 27(11):5585\u20135599","journal-title":"IEEE Trans Image Process"},{"issue":"1","key":"3435_CR144","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1152\/jn.00253.2015","volume":"114","author":"J Decety","year":"2015","unstructured":"Decety J, Lewis KL, Cowell JM (2015) Specific electrophysiological components disentangle affective sharing and empathic concern in psychopathy. J Neurophysiol 114(1):493\u2013504","journal-title":"J Neurophysiol"},{"issue":"1","key":"3435_CR145","doi-asserted-by":"publisher","first-page":"1393","DOI":"10.1038\/s41467-019-09406-4","volume":"10","author":"S Mangul","year":"2019","unstructured":"Mangul S et al (2019) Systematic benchmarking of omics computational tools. Nat Commun 10(1):1393","journal-title":"Nat Commun"},{"key":"3435_CR146","doi-asserted-by":"publisher","DOI":"10.3389\/frobt.2015.00028","volume":"2","author":"M Vrigkas","year":"2015","unstructured":"Vrigkas M, Nikou C, Kakadiaris IA (2015) A review of human activity recognition methods. Front Robot AI 2:28","journal-title":"Front Robot AI"},{"key":"3435_CR147","unstructured":"Mora Melanchthon D (2021) Unimodal feature-level improvement on multimodal CMU-MOSEI dataset: uncorrelated and convolved feature sets"},{"issue":"9","key":"3435_CR148","doi-asserted-by":"publisher","DOI":"10.3390\/s23094221","volume":"23","author":"Z Liu","year":"2023","unstructured":"Liu Z, Alavi A, Li M, Zhang X (2023) Self-supervised contrastive learning for medical time series: a systematic review. Sensors 23(9):4221","journal-title":"Sensors"},{"issue":"11","key":"3435_CR149","doi-asserted-by":"publisher","first-page":"8135","DOI":"10.1109\/TNNLS.2022.3152527","volume":"34","author":"H Song","year":"2022","unstructured":"Song H, Kim M, Park D, Shin Y, Lee J-G (2022) Learning from noisy labels with deep neural networks: a survey. IEEE Trans Neural Netw Learn Syst 34(11):8135\u20138153","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"3435_CR150","first-page":"72842","volume":"36","author":"S Chen","year":"2023","unstructured":"Chen S et al (2023) Vast: a vision-audio-subtitle-text omni-modality foundation model and dataset. Adv Neural Inf Process Syst 36:72842\u201372866","journal-title":"Adv Neural Inf Process Syst"},{"key":"3435_CR151","doi-asserted-by":"publisher","first-page":"7834","DOI":"10.1109\/TIP.2020.3006377","volume":"29","author":"Y Zhang","year":"2020","unstructured":"Zhang Y et al (2020) Collaborative unsupervised domain adaptation for medical image diagnosis. IEEE Trans Image Process 29:7834\u20137844","journal-title":"IEEE Trans Image Process"},{"key":"3435_CR152","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1016587515822","volume":"7","author":"HW Gellersen","year":"2002","unstructured":"Gellersen HW, Schmidt A, Beigl M (2002) Multi-sensor context-awareness in mobile devices and smart artifacts. Mob Netw Appl 7:341\u2013351","journal-title":"Mob Netw Appl"},{"issue":"1","key":"3435_CR153","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1109\/TCAD.2018.2878168","volume":"39","author":"S Pagani","year":"2018","unstructured":"Pagani S, Manoj PS, Jantsch A, Henkel J (2018) Machine learning for power, energy, and thermal management on multicore processors: a survey. IEEE Trans Comput Aided Des Integr Circuits Syst 39(1):101\u2013116","journal-title":"IEEE Trans Comput Aided Des Integr Circuits Syst"},{"key":"3435_CR154","unstructured":"Dao T, Sohoni NS, Gu A, Eichhorn M, Blonder A, Leszczynski M, Rudra A, R\u00e9 C (2020) Kaleidoscope: an efficient, learnable representation for all structured linear maps. arXiv preprint arXiv:2012.14966"},{"key":"3435_CR155","first-page":"22941","volume":"35","author":"J Lin","year":"2022","unstructured":"Lin J, Zhu L, Chen W-M, Wang W-C, Gan C, Han S (2022) On-device training under 256kb memory. Adv Neural Inf Process Syst 35:22941\u201322954","journal-title":"Adv Neural Inf Process Syst"},{"key":"3435_CR156","unstructured":"Cruz SL (2025) Equityware: designing responsible AI driven wearables for safety, health, and well-being.\u00a0(Doctoral dissertation, Northwestern University)"},{"issue":"10","key":"3435_CR157","doi-asserted-by":"publisher","DOI":"10.3390\/nano15100724","volume":"15","author":"T Huang","year":"2025","unstructured":"Huang T et al (2025) A review of nanowire devices applied in simulating neuromorphic computing. Nanomaterials 15(10):724","journal-title":"Nanomaterials"},{"key":"3435_CR158","unstructured":"Wang Y, Zhang T, Guo X, Shen Z (2024) Gradient based feature attribution in explainable AI: a technical review. arXiv preprint arXiv:2403.10415"},{"issue":"1","key":"3435_CR159","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1016\/j.ijpsycho.2015.07.003","volume":"98","author":"SL Mann","year":"2015","unstructured":"Mann SL, Selby EA, Bates ME, Contrada RJ (2015) Integrating affective and cognitive correlates of heart rate variability: a structural equation modeling approach. Int J Psychophysiol 98(1):76\u201386","journal-title":"Int J Psychophysiol"},{"issue":"3","key":"3435_CR160","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3550299","volume":"6","author":"H Haresamudram","year":"2022","unstructured":"Haresamudram H, Essa I, Pl\u00f6tz T (2022) Assessing the state of self-supervised human activity recognition using wearables. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 6(3):1\u201347","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"3435_CR161","unstructured":"Ramponi G, Protopapas P, Brambilla M, Janssen R (2018) T-cgan: conditional generative adversarial network for data augmentation in noisy time series with irregular sampling. arXiv preprint arXiv:1811.08295"},{"issue":"1","key":"3435_CR162","volume":"2022","author":"F Sabry","year":"2022","unstructured":"Sabry F, Eltaras T, Labda W, Alzoubi K, Malluhi Q (2022) Machine learning for healthcare wearable devices: the big picture. J Healthc Eng 2022(1):4653923","journal-title":"J Healthc Eng"},{"key":"3435_CR163","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2023.103180","volume":"129","author":"A Mu\u00f1oz","year":"2023","unstructured":"Mu\u00f1oz A, R\u00edos R, Rom\u00e1n R, L\u00f3pez J (2023) A survey on the (in) security of trusted execution environments. Comput Secur 129:103180","journal-title":"Comput Secur"},{"key":"3435_CR164","doi-asserted-by":"crossref","unstructured":"Barrett SF, Pack DJ (2012) Atmel avr microcontroller primer: programming and interfacing. Morgan & Claypool Publishers","DOI":"10.1007\/978-3-031-79849-8"},{"issue":"4","key":"3435_CR165","doi-asserted-by":"publisher","first-page":"760","DOI":"10.1093\/cercor\/bhn125","volume":"19","author":"A Akrami","year":"2009","unstructured":"Akrami A, Liu Y, Treves A, Jagadeesh B (2009) Converging neuronal activity in inferior temporal cortex during the classification of morphed stimuli. Cereb Cortex 19(4):760\u2013776","journal-title":"Cereb Cortex"},{"issue":"7","key":"3435_CR166","doi-asserted-by":"publisher","first-page":"292","DOI":"10.1111\/pcn.13356","volume":"76","author":"YC Cheng","year":"2022","unstructured":"Cheng YC, Su MI, Liu CW, Huang YC, Huang WL (2022) Heart rate variability in patients with anxiety disorders: a systematic review and meta-analysis. Psychiatry Clin Neurosci 76(7):292\u2013302","journal-title":"Psychiatry Clin Neurosci"},{"issue":"4","key":"3435_CR167","doi-asserted-by":"publisher","first-page":"247","DOI":"10.15420\/aer.2018.30.2","volume":"7","author":"N Singh","year":"2018","unstructured":"Singh N, Moneghetti KJ, Christle JW, Hadley D, Froelicher V, Plews D (2018) Heart rate variability: an old metric with new meaning in the era of using mhealth technologies for health and exercise training guidance. part Two: prognosis and training. Arrhythm Electrophysiol Rev 7(4):247","journal-title":"Arrhythm Electrophysiol Rev"},{"issue":"8","key":"3435_CR168","doi-asserted-by":"publisher","DOI":"10.2196\/38943","volume":"10","author":"S Choudhary","year":"2022","unstructured":"Choudhary S et al (2022) A machine learning approach for continuous mining of nonidentifiable smartphone data to create a novel digital biomarker detecting generalized anxiety disorder: prospective cohort study. JMIR Med Inform 10(8):e38943","journal-title":"JMIR Med Inform"},{"issue":"8","key":"3435_CR169","doi-asserted-by":"publisher","first-page":"852","DOI":"10.1097\/PSY.0b013e3181b8bb7a","volume":"71","author":"M Koschke","year":"2009","unstructured":"Koschke M et al (2009) Autonomy of autonomic dysfunction in major depression. Psychosom Med 71(8):852\u2013860","journal-title":"Psychosom Med"},{"issue":"6","key":"3435_CR170","doi-asserted-by":"publisher","DOI":"10.3390\/s17061385","volume":"17","author":"S-C Liao","year":"2017","unstructured":"Liao S-C, Wu C-T, Huang H-C, Cheng W-T, Liu Y-H (2017) Major depression detection from EEG signals using kernel eigen-filter-bank common spatial patterns. Sensors 17(6):1385","journal-title":"Sensors"},{"key":"3435_CR171","doi-asserted-by":"crossref","unstructured":"Peng D, Liu W, Luo Y, Mao Z, Zheng W-L, Lu B-L (2023) Deep depression detection with resting-state and cognitive-task EEG. In: 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), IEEE, pp 1\u20134","DOI":"10.1109\/EMBC40787.2023.10340667"},{"issue":"1","key":"3435_CR172","doi-asserted-by":"publisher","first-page":"11379","DOI":"10.1038\/s41598-025-96052-0","volume":"15","author":"K Rawat","year":"2025","unstructured":"Rawat K, Sharma T (2025) An enhanced CNN-bi-transformer based framework for detection of neurological illnesses through neurocardiac data fusion. Sci Rep 15(1):11379","journal-title":"Sci Rep"},{"issue":"3","key":"3435_CR173","doi-asserted-by":"publisher","first-page":"416","DOI":"10.9758\/cpn.24.1165","volume":"22","author":"YW Song","year":"2024","unstructured":"Song YW, Lee HS, Kim S, Kim K, Kim B-N, Kim JS (2024) How to solve clinical challenges in mood disorders; machine learning approaches using electrophysiological markers. Clin Psychopharmacol Neurosci 22(3):416","journal-title":"Clin Psychopharmacol Neurosci"},{"key":"3435_CR174","doi-asserted-by":"crossref","unstructured":"Nguyen H, Rahimi A, Whitford V, Fournier H, Kondratova I, Richard R, Cao H (2025) Heart2Mind: human-centered contestable psychiatric disorder diagnosis system using wearable ECG monitors. arXiv preprint arXiv:2505.11612","DOI":"10.1145\/3788686"},{"issue":"3","key":"3435_CR175","doi-asserted-by":"publisher","first-page":"594","DOI":"10.1016\/j.ijpsycho.2014.11.006","volume":"98","author":"S Lissek","year":"2015","unstructured":"Lissek S, van Meurs B (2015) Learning models of PTSD: theoretical accounts and psychobiological evidence. Int J Psychophysiol 98(3):594\u2013605","journal-title":"Int J Psychophysiol"},{"key":"3435_CR176","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1007\/s10286-003-0107-5","volume":"13","author":"R Vetrugno","year":"2003","unstructured":"Vetrugno R, Liguori R, Cortelli P, Montagna P (2003) Sympathetic skin response: basic mechanisms and clinical applications. Clin Auton Res 13:256\u2013270","journal-title":"Clin Auton Res"},{"key":"3435_CR177","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/2045-5380-2-8","volume":"2","author":"SP Orr","year":"2012","unstructured":"Orr SP, Lasko NB, Macklin ML, Pineles SL, Chang Y, Pitman RK (2012) Predicting post-trauma stress symptoms from pre-trauma psychophysiologic reactivity, personality traits and measures of psychopathology. Biology of mood & anxiety disorders 2:1\u201312","journal-title":"Biology of mood & anxiety disorders"},{"key":"3435_CR178","doi-asserted-by":"publisher","DOI":"10.1177\/2470547019844441","volume":"3","author":"R Hinrichs","year":"2019","unstructured":"Hinrichs R et al (2019) Increased skin conductance response in the immediate aftermath of trauma predicts PTSD risk. Chronic Stress 3:2470547019844441","journal-title":"Chronic Stress"},{"issue":"6","key":"3435_CR179","doi-asserted-by":"publisher","first-page":"502","DOI":"10.1002\/da.22610","volume":"34","author":"R Hinrichs","year":"2017","unstructured":"Hinrichs R et al (2017) Mobile assessment of heightened skin conductance in posttraumatic stress disorder. Depress Anxiety 34(6):502\u2013507","journal-title":"Depress Anxiety"},{"issue":"9","key":"3435_CR180","doi-asserted-by":"publisher","first-page":"1296","DOI":"10.1038\/s41380-018-0267-2","volume":"24","author":"A Perry","year":"2019","unstructured":"Perry A, Roberts G, Mitchell PB, Breakspear M (2019) Connectomics of bipolar disorder: a critical review, and evidence for dynamic instabilities within interoceptive networks. Mol Psychiatry 24(9):1296\u20131318","journal-title":"Mol Psychiatry"},{"issue":"14","key":"3435_CR181","doi-asserted-by":"publisher","DOI":"10.3390\/s24144721","volume":"24","author":"D Kami\u0144ska","year":"2024","unstructured":"Kami\u0144ska D, Kami\u0144ska O, Sochacka M, Sok\u00f3\u0142-Szaw\u0142owska M (2024) The role of selected speech signal characteristics in discriminating unipolar and bipolar disorders. Sensors 24(14):4721","journal-title":"Sensors"},{"key":"3435_CR182","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40345-021-00243-3","volume":"9","author":"M Faurholt-Jepsen","year":"2021","unstructured":"Faurholt-Jepsen M, Rohani DA, Busk J, Vinberg M, Bardram JE, Kessing LV (2021) Voice analyses using smartphone-based data in patients with bipolar disorder, unaffected relatives and healthy control individuals, and during different affective states. Int J Bipolar Disord 9:1\u201313","journal-title":"Int J Bipolar Disord"},{"key":"3435_CR183","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2024.1394210","volume":"15","author":"J Ji","year":"2024","unstructured":"Ji J et al (2024) Depressive and mania mood state detection through voice as a biomarker using machine learning. Front Neurol 15:1394210","journal-title":"Front Neurol"},{"key":"3435_CR184","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1016\/j.jad.2020.07.011","volume":"276","author":"K Koller-Schlaud","year":"2020","unstructured":"Koller-Schlaud K, Str\u00f6hle A, B\u00e4rwolf E, Behr J, Rentzsch J (2020) EEG frontal asymmetry and theta power in unipolar and bipolar depression. J Affect Disord 276:501\u2013510","journal-title":"J Affect Disord"},{"key":"3435_CR185","doi-asserted-by":"publisher","first-page":"677","DOI":"10.3758\/s13415-019-00719-x","volume":"19","author":"EL Maresh","year":"2019","unstructured":"Maresh EL et al (2019) Neurophysiological correlates of cognitive control and approach motivation abnormalities in adolescent bipolar disorders. Cogn Affect Behav Neurosci 19:677\u2013691","journal-title":"Cogn Affect Behav Neurosci"},{"issue":"1","key":"3435_CR186","doi-asserted-by":"publisher","DOI":"10.1038\/s44184-024-00090-x","volume":"3","author":"F Corponi","year":"2024","unstructured":"Corponi F et al (2024) A bayesian analysis of heart rate variability changes over acute episodes of bipolar disorder. NPJ Ment Health Res 3(1):44","journal-title":"NPJ Ment Health Res"}],"container-title":["Medical &amp; Biological Engineering &amp; Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-025-03435-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11517-025-03435-6","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-025-03435-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,3]],"date-time":"2026-02-03T07:03:01Z","timestamp":1770102181000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11517-025-03435-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,30]]},"references-count":186,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["3435"],"URL":"https:\/\/doi.org\/10.1007\/s11517-025-03435-6","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,30]]},"assertion":[{"value":"16 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 September 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}