{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T05:10:56Z","timestamp":1736140256825,"version":"3.32.0"},"reference-count":37,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2019,8,9]],"date-time":"2019-08-09T00:00:00Z","timestamp":1565308800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2015M3C7A1065052"],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Institute of Information & Communications Technology Planning & Evaluation","award":["2017-0-00432"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"Internet gaming disorder in adolescents and young adults has become an increasing public concern because of its high prevalence rate and potential risk of alteration of brain functions and organizations. Cue exposure therapy is designed for reducing or maintaining craving, a core factor of relapse of addiction, and is extensively employed in addiction treatment. In a previous study, we proposed a machine-learning-based method to detect craving for gaming using multimodal physiological signals including photoplethysmogram, galvanic skin response, and electrooculogram. Our previous study demonstrated that a craving for gaming could be detected with a fairly high accuracy; however, as the feature vectors for the machine-learning-based detection of the craving of a user were selected based on the physiological data of the user that were recorded on the same day, the effectiveness of the reuse of the machine learning model constructed during the previous experiments, without any further calibration sessions, was still questionable. This \u201chigh test-retest reliability\u201d characteristic is of importance for the practical use of the craving detection system because the system needs to be repeatedly applied to the treatment processes as a tool to monitor the efficacy of the treatment. We presented short video clips of three addictive games to nine participants, during which various physiological signals were recorded. This experiment was repeated with different video clips on three different days. Initially, we investigated the test-retest reliability of 14 features used in a craving detection system by computing the intraclass correlation coefficient. Then, we classified whether each participant experienced a craving for gaming in the third experiment using various classifiers\u2014the support vector machine, k-nearest neighbors (kNN), centroid displacement-based kNN, linear discriminant analysis, and random forest\u2014trained with the physiological signals recorded during the first or second experiment. Consequently, the craving\/non-craving states in the third experiment were classified with an accuracy that was comparable to that achieved using the data of the same day; thus, demonstrating a high test-retest reliability and the practicality of our craving detection method. In addition, the classification performance was further enhanced by using both datasets of the first and second experiments to train the classifiers, suggesting that an individually customized game craving detection system with high accuracy can be implemented by accumulating datasets recorded on different days under different experimental conditions.<\/jats:p>","DOI":"10.3390\/s19163475","type":"journal-article","created":{"date-parts":[[2019,8,9]],"date-time":"2019-08-09T15:11:31Z","timestamp":1565363491000},"page":"3475","source":"Crossref","is-referenced-by-count":5,"title":["Machine-Learning-Based Detection of Craving for Gaming Using Multimodal Physiological Signals: Validation of Test-Retest Reliability for Practical Use"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0439-6236","authenticated-orcid":false,"given":"Hodam","family":"Kim","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea"}]},{"given":"Laehyun","family":"Kim","sequence":"additional","affiliation":[{"name":"Center for Bionics, Korea Institute of Science and Technology, Seoul 02792, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3795-3318","authenticated-orcid":false,"given":"Chang-Hwan","family":"Im","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Hanyang University, Seoul 04763, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1186","DOI":"10.1111\/add.12162","article-title":"Internet gaming disorder and the dsm-5","volume":"108","author":"Petry","year":"2013","journal-title":"Addiction"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1007\/s11920-015-0610-0","article-title":"Internet gaming disorder in the dsm-5","volume":"17","author":"Petry","year":"2015","journal-title":"Curr. Psychiatry Rep."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1023\/A:1021275130071","article-title":"Neurodevelopment, impulsivity, and adolescent gambling","volume":"19","author":"Chambers","year":"2003","journal-title":"J. Gambl. Stud."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.pbb.2006.12.001","article-title":"Adolescent cortical development: A critical period of vulnerability for addiction","volume":"86","author":"Crews","year":"2007","journal-title":"Pharmacol. Biochem. Behav."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/s00213-011-2376-3","article-title":"Stress-and cue-elicited craving and reactivity in marijuana-dependent individuals","volume":"218","author":"Carter","year":"2011","journal-title":"Psychopharmacology"},{"key":"ref_6","first-page":"404","article-title":"Gaming increases craving to gaming-related stimuli in individuals with internet gaming disorder","volume":"2","author":"Dong","year":"2017","journal-title":"Biol. Psychiatry Cogn. Neurosci. Neuroimaging"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1089\/cyber.2009.0254","article-title":"Differentiation of internet addiction risk level based on autonomic nervous responses: The internet-addiction hypothesis of autonomic activity","volume":"13","author":"Lu","year":"2010","journal-title":"Cyberpsychol. Behav. Soc. Netw."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.biopsycho.2015.07.016","article-title":"Altered cardiorespiratory coupling in young male adults with excessive online gaming","volume":"110","author":"Chang","year":"2015","journal-title":"Biol. Psychol."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Kim, H., Ha, J., Chang, W.-D., Park, W., Kim, L., and Im, C.-H. (2018). Detection of craving for gaming in adolescents with internet gaming disorder using multimodal biosignals. Sensors, 18.","DOI":"10.3390\/s18010102"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1007\/s10484-013-9218-5","article-title":"Neurofeedback training for opiate addiction: Improvement of mental health and craving","volume":"38","author":"Rostami","year":"2013","journal-title":"Appl. Psychophysiol. Biofeedback"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1037\/adb0000078","article-title":"Computer-assisted behavioral therapy and contingency management for cannabis use disorder","volume":"29","author":"Budney","year":"2015","journal-title":"Psychol. Addict. Behav."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"232","DOI":"10.14704\/nq.2017.15.2.1067","article-title":"Neuro-feedback training for overweight women: Improvement of food craving and mental health","volume":"15","author":"Fattahi","year":"2017","journal-title":"NeuroQuantology"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1046\/j.1360-0443.1999.9433273.x","article-title":"Meta-analysis of cue-reactivity in addiction research","volume":"94","author":"Carter","year":"1999","journal-title":"Addiction"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.jbtep.2009.12.004","article-title":"Smoking behavior in context: Where and when do people smoke?","volume":"41","author":"Beckers","year":"2010","journal-title":"J. Behav. Ther. Exp. Psychiatry"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"675","DOI":"10.3389\/fpsyg.2016.00675","article-title":"Cue-induced behavioral and neural changes among excessive internet gamers and possible application of cue exposure therapy to internet gaming disorder","volume":"7","author":"Zhang","year":"2016","journal-title":"Front. Psychol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Shin, Y.-B., Kim, J.-J., Kim, M.-K., Kyeong, S., Jung, Y.H., Eom, H., and Kim, E. (2018). Development of an effective virtual environment in eliciting craving in adolescents and young adults with internet gaming disorder. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0195677"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1089\/109493101300210286","article-title":"Modification in the proposed diagnostic criteria for internet addiction","volume":"4","author":"Beard","year":"2001","journal-title":"CyberPsychol. Behav."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1089\/cpb.1998.1.237","article-title":"Internet addiction: The emergence of a new clinical disorder","volume":"1","author":"Young","year":"1998","journal-title":"CyberPsychol. Behav."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1109\/TNSRE.2016.2542524","article-title":"Real-time \u201ceye-writing\u201d recognition using electrooculogram","volume":"25","author":"Lee","year":"2017","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Kim, H., Kim, J.-Y., and Im, C.-H. (2016). Fast and robust real-time estimation of respiratory rate from photoplethysmography. Sensors, 16.","DOI":"10.3390\/s16091494"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.cmpb.2015.10.011","article-title":"Detection of eye blink artifacts from single prefrontal channel electroencephalogram","volume":"124","author":"Chang","year":"2016","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1186\/s12984-017-0303-5","article-title":"Development of an electrooculogram-based eye-computer interface for communication of individuals with amyotrophic lateral sclerosis","volume":"14","author":"Chang","year":"2017","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_23","first-page":"27","article-title":"Libsvm: A library for support vector machines","volume":"2","author":"Chang","year":"2011","journal-title":"ACM Trans. Intell. Syst. Technol. (TIST)"},{"key":"ref_24","unstructured":"Duda, R.O., Hart, P.E., and Stork, D.G. (2012). Pattern Classification, John Wiley & Sons."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Fix, E., and Hodges, J.L. (1951). Discriminatory Analysis-Nonparametric Discrimination: Consistency Properties, California University Berkeley.","DOI":"10.1037\/e471672008-001"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1109\/THMS.2015.2453203","article-title":"Robust biometric recognition from palm depth images for gloved hands","volume":"45","author":"Nguyen","year":"2015","journal-title":"IEEE Trans. Hum. -Mach. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"451","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1037\/1082-989X.1.1.30","article-title":"Forming inferences about some intraclass correlation coefficients","volume":"1","author":"McGraw","year":"1996","journal-title":"Psychol. Methods"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1037\/0033-2909.86.2.420","article-title":"Intraclass correlations: Uses in assessing rater reliability","volume":"86","author":"Shrout","year":"1979","journal-title":"Psychol. Bull."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.jcm.2016.02.012","article-title":"A guideline of selecting and reporting intraclass correlation coefficients for reliability research","volume":"15","author":"Koo","year":"2016","journal-title":"J. Chiropr. Med."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3034","DOI":"10.1016\/j.addbeh.2007.07.010","article-title":"Smoking-related videos for use in cue-induced craving paradigms","volume":"32","author":"Tong","year":"2007","journal-title":"Addict. Behav."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1111\/adb.12338","article-title":"Activation of the ventral and dorsal striatum during cue reactivity in internet gaming disorder","volume":"22","author":"Liu","year":"2017","journal-title":"Addict. Biol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.addbeh.2016.06.012","article-title":"Cue-induced craving for internet among internet addicts","volume":"62","author":"Niu","year":"2016","journal-title":"Addict. Behav."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1109\/3468.618255","article-title":"Application of majority voting to pattern recognition: An analysis of its behavior and performance","volume":"27","author":"Lam","year":"1997","journal-title":"IEEE Trans. Syst. Man Cybern. -Part A Syst. Hum."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1186\/s12984-018-0365-z","article-title":"Assessment of user voluntary engagement during neurorehabilitation using functional near-infrared spectroscopy: A preliminary study","volume":"15","author":"Han","year":"2018","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_36","unstructured":"Van Erp, M., Vuurpijl, L., and Schomaker, L. (2002, January 6\u20138). An overview and comparison of voting methods for pattern recognition. Proceedings of the 8th International Workshop on Frontiers in Handwriting Recognition, Ontario, ON, Canada."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.bspc.2013.11.009","article-title":"A novel steady-state visually evoked potential-based brain\u2013computer interface design: Character plotter","volume":"10","author":"Dokur","year":"2014","journal-title":"Biomed. Signal Process. Control"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/16\/3475\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,5]],"date-time":"2025-01-05T22:41:50Z","timestamp":1736116910000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/16\/3475"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,9]]},"references-count":37,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2019,8]]}},"alternative-id":["s19163475"],"URL":"https:\/\/doi.org\/10.3390\/s19163475","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2019,8,9]]}}}