{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T21:47:34Z","timestamp":1757627254763,"version":"3.44.0"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T00:00:00Z","timestamp":1755475200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T00:00:00Z","timestamp":1755475200000},"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":["SN COMPUT. SCI."],"DOI":"10.1007\/s42979-025-04282-w","type":"journal-article","created":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T11:38:02Z","timestamp":1755517082000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AI-Techniques for Re-Identification Attacks on De-Identified Smartwatch Health Data"],"prefix":"10.1007","volume":"6","author":[{"given":"K. V.","family":"Sudheesh","sequence":"first","affiliation":[]},{"given":"Jyoti","family":"Metan","sequence":"additional","affiliation":[]},{"given":"K. P.","family":"Suhaas","sequence":"additional","affiliation":[]},{"given":"Mahantesh","family":"Mathapati","sequence":"additional","affiliation":[]},{"given":"H. S.","family":"Ranjan Kumar","sequence":"additional","affiliation":[]},{"given":"S.","family":"Nandini","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,18]]},"reference":[{"key":"4282_CR1","unstructured":"Lange L, Schreieder T, Christen V, Rahm E. Slice it up: unmasking user identities in smartwatch health data. arXiv:2308.08310 [preprint] 2023."},{"key":"4282_CR2","doi-asserted-by":"crossref","unstructured":"Datta P, Namin AS, Chatterjee M. A survey of privacy concerns in wearable devices. In 2018 IEEE international conference on big data (big data). IEEE; 2018. p. 4549\u201353.","DOI":"10.1109\/BigData.2018.8622110"},{"key":"4282_CR3","unstructured":"Tenzer F. Prognose zum Absatz von Smartwatches weltweit in den Jahren 2022 bis 2027. Statista; 2004. https:\/\/de.statista.com\/statistik\/daten\/studie\/500483\/umfrage\/prognose-zum-weltweiten-absatz-von-smartwatches\/."},{"issue":"2","key":"4282_CR4","doi-asserted-by":"publisher","first-page":"1125","DOI":"10.1109\/COMST.2021.3064507","volume":"23","author":"AK Sikder","year":"2021","unstructured":"Sikder AK, Petracca G, Aksu H, Jaeger T, Uluagac AS. A survey on sensor-based threats and attacks to smart devices and applications. IEEE Commun Surv Tutor. 2021;23(2):1125\u201359.","journal-title":"IEEE Commun Surv Tutor"},{"issue":"5","key":"4282_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s42979-025-03961-y","volume":"6","author":"VV Leelavathi","year":"2025","unstructured":"Leelavathi VV, Bajanemane Krishnamurthy RP, Puttegowda K. Securing telehealth electronic health records with adaptive chaotic encryption and dynamic key generation. SN Comput Sci. 2025;6(5):1\u201319.","journal-title":"SN Comput Sci"},{"key":"4282_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.isci.2025.112109","author":"JK Adeniyi","year":"2025","unstructured":"Adeniyi JK, Ajagbe SA, Adeniyi AE, Adeyanju KI, Afolorunso AA, Adigun MO, Ogene I. A blockchain-based smart healthcare system for data protection. iScience. 2025. https:\/\/doi.org\/10.1016\/j.isci.2025.112109.","journal-title":"iScience"},{"key":"4282_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.atech.2025.100774","volume":"10","author":"G Taiwo","year":"2025","unstructured":"Taiwo G, Vadera S, Alameer A. Vision transformers for automated detection of pig interactions in groups. Smart Agric Technol. 2025;10: 100774.","journal-title":"Smart Agric Technol"},{"key":"4282_CR8","doi-asserted-by":"crossref","unstructured":"Akinlade O, Vakaj E, Dridi A, Tiwari S, Ortiz-Rodriguez F. Semantic segmentation of the lung to examine the effect of COVID-19 using UNET model. In: International conference on applied machine learning and data analytics. Cham: Springer Nature Switzerland; 2022. p. 52\u201363.","DOI":"10.1007\/978-3-031-34222-6_5"},{"key":"4282_CR9","doi-asserted-by":"crossref","unstructured":"Naveenkumar SK, Panduranga HT. Chaos and hill cipher based image encryption for mammography images. In: 2015 International conference on innovations in information, embedded and communication systems (ICIIECS). IEEE; 2015. p. 1\u20135.","DOI":"10.1109\/ICIIECS.2015.7193175"},{"key":"4282_CR10","doi-asserted-by":"crossref","unstructured":"Schmidt P, Reiss A, Duerichen R, Marberger C, Van Laerhoven K. Introducing wesad, a multimodal dataset for wearable stress and affect detection. In: Proceedings of the 20th ACM international conference on multimodal interaction; 2018. p. 400\u20138.","DOI":"10.1145\/3242969.3242985"},{"key":"4282_CR11","doi-asserted-by":"publisher","unstructured":"Lin Z, Harris J, Porras P. Generative models for privacy-preserving sensor data synthesis. In: Proceedings of the 2020 ACM SIGSAC conference on computer and communications security (CCS); 2020. p. 1205\u201322. https:\/\/doi.org\/10.1145\/3372297.3417266.","DOI":"10.1145\/3372297.3417266"},{"issue":"2","key":"4282_CR12","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1001953","volume":"13","author":"L Piwek","year":"2016","unstructured":"Piwek L, Ellis DA, Andrews S, Joinson A. The rise of consumer health wearables: promises and barriers. PLoS Med. 2016;13(2): e1001953.","journal-title":"PLoS Med"},{"issue":"1","key":"4282_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s41666-017-0012-7","volume":"2","author":"CE King","year":"2018","unstructured":"King CE, Sarrafzadeh M. A survey of smartwatches in remote health monitoring. J Healthc Inform Res. 2018;2(1):1\u201324.","journal-title":"J Healthc Inform Res"},{"key":"4282_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.micpro.2022.104546","volume":"91","author":"P Kiran","year":"2022","unstructured":"Kiran P, Parameshachari BD. Resource optimized selective image encryption of medical images using multiple chaotic systems. Microprocess Microsyst. 2022;91: 104546.","journal-title":"Microprocess Microsyst"},{"key":"4282_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.micpro.2023.104907","volume":"101","author":"K Prabhavathi","year":"2023","unstructured":"Prabhavathi K, Anandaraju MB. An efficient medical image encryption algorithm for telemedicine applications. Microprocess Microsyst. 2023;101: 104907.","journal-title":"Microprocess Microsyst"},{"issue":"1","key":"4282_CR16","doi-asserted-by":"publisher","first-page":"47","DOI":"10.3390\/info14010047","volume":"14","author":"Kiran","year":"2023","unstructured":"Kiran, Gururaj HL, Almeshari M, Alzamil Y, Ravi V, Sudeesh KV. Efficient SCAN and chaotic map encryption system for securing E-healthcare images. Information. 2023;14(1):47.","journal-title":"Information"},{"key":"4282_CR17","doi-asserted-by":"crossref","unstructured":"Kiran P, Panduranga HT, Yashwanth J. Efficient secure medical image transmission based on brownian system. In: Cybersecurity: a new approach using chaotic systems. Cham: Springer International Publishing; 2022. p. 207\u201320.","DOI":"10.1007\/978-3-030-92166-8_9"},{"key":"4282_CR18","doi-asserted-by":"crossref","unstructured":"Garbarino M, Lai M, Bender D, Picard RW, Tognetti S. Empatica E3\u2014a wearable wireless multi-sensor device for real-time computerized biofeedback and data acquisition. In: 2014 4th international conference on wireless mobile communication and healthcare-transforming healthcare through innovations in mobile and wireless technologies (MOBIHEALTH). IEEE; 2014. p. 39\u201342.","DOI":"10.4108\/icst.mobihealth.2014.257418"},{"key":"4282_CR19","doi-asserted-by":"crossref","unstructured":"McCarthy C, Pradhan N, Redpath C, Adler A. Validation of the Empatica E4 wristband. In: 2016 IEEE EMBS international student conference (ISC). IEEE; 2016. p. 1\u20134.","DOI":"10.1109\/EMBSISC.2016.7508621"},{"issue":"11","key":"4282_CR20","doi-asserted-by":"publisher","first-page":"190","DOI":"10.1007\/s10916-020-01648-w","volume":"44","author":"AAT Schuurmans","year":"2020","unstructured":"Schuurmans AAT, De Looff P, Nijhof KS, Rosada C, Scholte RHJ, Popma A, Otten R. Validity of the Empatica E4 wristband to measure heart rate variability (HRV) parameters: a comparison to electrocardiography (ECG). J Med Syst. 2020;44(11):190.","journal-title":"J Med Syst"},{"issue":"11","key":"4282_CR21","doi-asserted-by":"publisher","DOI":"10.1111\/psyp.13441","volume":"56","author":"L Menghini","year":"2019","unstructured":"Menghini L, Gianfranchi E, Cellini N, Patron E, Tagliabue M, Sarlo M. Stressing the accuracy: wrist-worn wearable sensor validation over different conditions. Psychophysiology. 2019;56(11): e13441.","journal-title":"Psychophysiology"},{"key":"4282_CR22","first-page":"200","volume":"2","author":"ME Dawson","year":"2007","unstructured":"Dawson ME, Schell AM, Filion DL. The electrodermal system. Handbook of psychophysiology. 2007;2:200\u201323.","journal-title":"Handbook of psychophysiology"},{"issue":"2","key":"4282_CR23","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1111\/j.1469-8986.1992.tb01693.x","volume":"29","author":"A Scerbo","year":"1992","unstructured":"Scerbo A, Scarpa L, Weinstock Freedman A, Raine ME, Dawson ME, Venables PH. A major effect of recording site on measurement of electrodermal activity. Psychophysiology. 1992;29(2):241\u20136.","journal-title":"Psychophysiology"},{"issue":"5","key":"4282_CR24","doi-asserted-by":"publisher","first-page":"1243","DOI":"10.1109\/TBME.2009.2038487","volume":"57","author":"M-Z Poh","year":"2010","unstructured":"Poh M-Z, Swenson NC, Picard RW. A wearable sensor for unobtrusive, long-term assessment of electrodermal activity. IEEE Trans Biomed Eng. 2010;57(5):1243\u201352.","journal-title":"IEEE Trans Biomed Eng"},{"issue":"2","key":"4282_CR25","doi-asserted-by":"publisher","first-page":"298","DOI":"10.1016\/j.physbeh.2012.01.020","volume":"106","author":"M van Dooren","year":"2012","unstructured":"van Dooren M, Janssen JH. Emotional sweating across the body: comparing 16 different skin conductance measurement locations. Physiol Behav. 2012;106(2):298\u2013304.","journal-title":"Physiol Behav"},{"issue":"4","key":"4282_CR26","doi-asserted-by":"publisher","first-page":"78","DOI":"10.5688\/aj710478","volume":"71","author":"LK McCorry","year":"2007","unstructured":"McCorry LK. Physiology of the autonomic nervous system. Am J Pharm Educ. 2007;71(4):78.","journal-title":"Am J Pharm Educ"},{"issue":"1","key":"4282_CR27","doi-asserted-by":"publisher","first-page":"440","DOI":"10.1109\/TAFFC.2019.2927337","volume":"13","author":"G Giannakakis","year":"2019","unstructured":"Giannakakis G, Grigoriadis D, Giannakaki K, Simantiraki O, Roniotis A, Tsiknakis M. Review on psychological stress detection using biosignals. IEEE Trans Affect Comput. 2019;13(1):440\u201360.","journal-title":"IEEE Trans Affect Comput"},{"issue":"7","key":"4282_CR28","doi-asserted-by":"publisher","first-page":"12305","DOI":"10.3390\/s140712305","volume":"14","author":"R Usamentiaga","year":"2014","unstructured":"Usamentiaga R, Venegas P, Guerediaga J, Vega L, Molleda J, Bulnes FG. Infrared thermography for temperature measurement and non-destructive testing. Sensors. 2014;14(7):12305\u201348.","journal-title":"Sensors"},{"issue":"1","key":"4282_CR29","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1152\/jappl.1971.31.1.80","volume":"31","author":"ER Nadel","year":"1971","unstructured":"Nadel ER, Bullard RW, Stolwijk JA. Importance of skin temperature in the regulation of sweating. J Appl Physiol. 1971;31(1):80\u20137. https:\/\/doi.org\/10.1152\/jappl.1971.31.1.80.","journal-title":"J Appl Physiol"},{"issue":"18","key":"4282_CR30","doi-asserted-by":"publisher","first-page":"2093","DOI":"10.1001\/archinte.1993.00410180039004","volume":"153","author":"BS McEwen","year":"1993","unstructured":"McEwen BS, Stellar E. Stress and the individual: mechanisms leading to disease. Arch Intern Med. 1993;153(18):2093\u2013101.","journal-title":"Arch Intern Med"},{"issue":"14","key":"4282_CR31","doi-asserted-by":"publisher","first-page":"1685","DOI":"10.1001\/jama.298.14.1685","volume":"298","author":"S Cohen","year":"2007","unstructured":"Cohen S, Janicki-Deverts D, Miller GE. Psychological stress and disease. JAMA. 2007;298(14):1685\u20137.","journal-title":"JAMA"},{"issue":"1","key":"4282_CR32","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1146\/annurev-publhealth-031912-114452","volume":"34","author":"A Steptoe","year":"2013","unstructured":"Steptoe A, Kivim\u00e4ki M. Stress and cardiovascular disease: an update on current knowledge. Annu Rev Public Health. 2013;34(1):337\u201354.","journal-title":"Annu Rev Public Health"},{"issue":"4","key":"4282_CR33","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1037\/0033-2909.130.4.601","volume":"130","author":"SC Segerstrom","year":"2004","unstructured":"Segerstrom SC, Miller GE. Psychological stress and the human immune system: a meta-analytic study of 30 years of inquiry. Psychol Bull. 2004;130(4):601.","journal-title":"Psychol Bull"},{"issue":"no. 5","key":"4282_CR34","doi-asserted-by":"publisher","first-page":"891","DOI":"10.1016\/j.pnpbp.2004.05.031","volume":"28","author":"HM Van Praag","year":"2004","unstructured":"Van Praag HM. Can stress cause depression? Prog Neuropsychopharmacol Biol Psychiatry. 2004;28(5):891\u2013907.","journal-title":"Prog Neuropsychopharmacol Biol Psychiatry"},{"issue":"2","key":"4282_CR35","doi-asserted-by":"publisher","first-page":"428","DOI":"10.1038\/oby.2011.95","volume":"20","author":"AM Heraclides","year":"2012","unstructured":"Heraclides AM, Chandola T, Witte DR, Brunner EJ. Work stress, obesity and the risk of type 2 diabetes: gender-specific bidirectional effect in the Whitehall II study. Obesity. 2012;20(2):428\u201333.","journal-title":"Obesity"},{"issue":"2","key":"4282_CR36","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1080\/09735070.2008.11886324","volume":"2","author":"A Mitra","year":"2008","unstructured":"Mitra A. Diabetes and stress: a review. Stud Ethno-Med. 2008;2(2):131\u20135.","journal-title":"Stud Ethno-Med"},{"key":"4282_CR37","doi-asserted-by":"publisher","first-page":"108519","DOI":"10.1016\/j.neuropharm.2021.108519","volume":"188","author":"M al\u2019Absi","year":"2021","unstructured":"al\u2019Absi M, Ginty AT, Lovallo WR. Neurobiological mechanisms of early life adversity, blunted stress reactivity and risk for addiction. Neuropharmacology. 2021;188:108519.","journal-title":"Neuropharmacology"},{"issue":"6","key":"4282_CR38","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1007\/BF03347487","volume":"27","author":"A Angeli","year":"2004","unstructured":"Angeli A, Minetto M, Dovio A, Paccotti P. The overtraining syndrome in athletes: a stress-related disorder. J Endocrinol Invest. 2004;27(6):603\u201312.","journal-title":"J Endocrinol Invest"},{"key":"4282_CR39","doi-asserted-by":"crossref","unstructured":"Gjoreski M, Gjoreski H, Lu\u0161trek M, Gams M. Continuous stress detection using a wrist device: in laboratory and real life. In: Proceedings of the 2016 ACM international joint conference on pervasive and ubiquitous computing: adjunct; 2016. p. 1185\u201393.","DOI":"10.1145\/2968219.2968306"},{"key":"4282_CR40","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1038\/133082a0","volume":"133","author":"WB Cannon","year":"1934","unstructured":"Cannon WB. The wisdom of the body. Nature. 1934;133:82. https:\/\/doi.org\/10.1038\/133082a0.","journal-title":"Nature"},{"key":"4282_CR41","doi-asserted-by":"crossref","unstructured":"Mirsamadi S, Barsoum E, Zhang C. Automatic speech emotion recognition using recurrent neural networks with local attention. In: 2017 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE; 2017. p. 2227\u201331.","DOI":"10.1109\/ICASSP.2017.7952552"},{"issue":"8","key":"4282_CR42","doi-asserted-by":"publisher","first-page":"1301","DOI":"10.1109\/JSTSP.2017.2764438","volume":"11","author":"P Tzirakis","year":"2017","unstructured":"Tzirakis P, Trigeorgis G, Nicolaou MA, Schuller BW, Zafeiriou S. End-to-end multimodal emotion recognition using deep neural networks. IEEE J Sel Top Signal Process. 2017;11(8):1301\u20139.","journal-title":"IEEE J Sel Top Signal Process"},{"issue":"10","key":"4282_CR43","doi-asserted-by":"publisher","first-page":"4857","DOI":"10.1109\/TIE.2010.2103538","volume":"58","author":"A de Santos Sierra","year":"2011","unstructured":"de Santos Sierra A, \u00c1vila CS, Casanova JG, Del Pozo GB. A stress-detection system based on physiological signals and fuzzy logic. IEEE Trans Ind Electron. 2011;58(10):4857\u201365.","journal-title":"IEEE Trans Ind Electron"},{"issue":"2","key":"4282_CR44","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1109\/TITS.2005.848368","volume":"6","author":"JA Healey","year":"2005","unstructured":"Healey JA, Picard RW. Detecting stress during real-world driving tasks using physiological sensors. IEEE Trans Intell Transp Syst. 2005;6(2):156\u201366.","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"4282_CR45","doi-asserted-by":"crossref","unstructured":"Siirtola P. Continuous stress detection using the sensors of commercial smartwatch. In: Adjunct proceedings of the 2019 ACM international joint conference on pervasive and ubiquitous computing and proceedings of the 2019 ACM international symposium on wearable computers; 2019. p. 1198\u2013201.","DOI":"10.1145\/3341162.3344831"},{"issue":"Suppl 11","key":"4282_CR46","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-020-01299-4","volume":"20","author":"R Li","year":"2020","unstructured":"Li R, Liu Z. Stress detection using deep neural networks. BMC Med Inform Decis Mak. 2020;20(Suppl 11): 285.","journal-title":"BMC Med Inform Decis Mak"},{"issue":"1","key":"4282_CR47","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1109\/MAES.2021.3115198","volume":"37","author":"M Gil-Martin","year":"2022","unstructured":"Gil-Martin M, San-Segundo R, Mateos A, Ferreiros-Lopez J. Human stress detection with wearable sensors using convolutional neural networks. IEEE Aerosp Electron Syst Mag. 2022;37(1):60\u201370.","journal-title":"IEEE Aerosp Electron Syst Mag"},{"key":"4282_CR48","doi-asserted-by":"crossref","unstructured":"de Souza A, Melchiades MD, Rigo SJ, Ramos GDO. Mostress: a sequence model for stress classification. In: 2022 International joint conference on neural networks (IJCNN). IEEE; 2022. p. 1\u20138.","DOI":"10.1109\/IJCNN55064.2022.9892953"},{"key":"4282_CR49","doi-asserted-by":"crossref","unstructured":"Eren E, Navruz TS. Stress detection with deep learning using BVP and EDA signals. In: 2022 International congress on human-computer interaction, optimization and robotic applications (HORA). IEEE; 2022. p. 1\u20137.","DOI":"10.1109\/HORA55278.2022.9799933"},{"key":"4282_CR50","doi-asserted-by":"publisher","unstructured":"Lange L, Degenkolb B, Rahm E. Privacy-preserving stress detection using smartwatch health data; 2023. p. 549\u201360. https:\/\/doi.org\/10.18420\/inf2023_66.","DOI":"10.18420\/inf2023_66"},{"issue":"1","key":"4282_CR51","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/T-AFFC.2011.15","volume":"3","author":"S Koelstra","year":"2012","unstructured":"Koelstra S, Muhl C, Soleymani M, Lee J-S, Yazdani A, Ebrahimi T, Pun T, Nijholt A, Patras I. DEAP: a database for emotion analysis using physiological signals. IEEE Trans Affect Comput. 2012;3(1):18\u201331. https:\/\/doi.org\/10.1109\/T-AFFC.2011.15.","journal-title":"IEEE Trans Affect Comput"}],"container-title":["SN Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-025-04282-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42979-025-04282-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-025-04282-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,10]],"date-time":"2025-09-10T01:45:49Z","timestamp":1757468749000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42979-025-04282-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,18]]},"references-count":51,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2025,8]]}},"alternative-id":["4282"],"URL":"https:\/\/doi.org\/10.1007\/s42979-025-04282-w","relation":{},"ISSN":["2661-8907"],"issn-type":[{"type":"electronic","value":"2661-8907"}],"subject":[],"published":{"date-parts":[[2025,8,18]]},"assertion":[{"value":"19 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 August 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 have no relevant financial or non-financial interests to disclose.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing Interests"}},{"value":"This is an observational study. The Research Ethics Committee has confirmed that no ethical approval is required.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics Approval and Consent to Participate"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Clinical Trial Number"}},{"value":"Not applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human Ethics and Consent to Participate declarations"}}],"article-number":"748"}}