{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T02:24:17Z","timestamp":1775787857806,"version":"3.50.1"},"reference-count":69,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2020,8,25]],"date-time":"2020-08-25T00:00:00Z","timestamp":1598313600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100011033","name":"Agencia Estatal de Investigaci\u00f3n","doi-asserted-by":"publisher","award":["DPI2016-80894-R"],"award-info":[{"award-number":["DPI2016-80894-R"]}],"id":[{"id":"10.13039\/501100011033","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The detection of emotions is fundamental in many areas related to health and well-being. This paper presents the identification of the level of arousal in older people by monitoring their electrodermal activity (EDA) through a commercial device. The objective was to recognize arousal changes to create future therapies that help them to improve their mood, contributing to reduce possible situations of depression and anxiety. To this end, some elderly people in the region of Murcia were exposed to listening to various musical genres (flamenco, Spanish folklore, Cuban genre and rock\/jazz) that they heard in their youth. Using methods based on the process of deconvolution of the EDA signal, two different studies were carried out. The first, of a purely statistical nature, was based on the search for statistically significant differences for a series of temporal, morphological, statistical and frequency features of the processed signals. It was found that Flamenco and Spanish Folklore presented the highest number of statistically significant parameters. In the second study, a wide range of classifiers was used to analyze the possible correlations between the detection of the EDA-based arousal level compared to the participants\u2019 responses to the level of arousal subjectively felt. In this case, it was obtained that the best classifiers are support vector machines, with 87% accuracy for flamenco and 83.1% for Spanish Folklore, followed by K-nearest neighbors with 81.4% and 81.5% for Flamenco and Spanish Folklore again. These results reinforce the notion of familiarity with a musical genre on emotional induction.<\/jats:p>","DOI":"10.3390\/s20174788","type":"journal-article","created":{"date-parts":[[2020,8,25]],"date-time":"2020-08-25T09:30:07Z","timestamp":1598347807000},"page":"4788","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Arousal Detection in Elderly People from Electrodermal Activity Using Musical Stimuli"],"prefix":"10.3390","volume":"20","author":[{"given":"Almudena","family":"Bartolom\u00e9-Tom\u00e1s","sequence":"first","affiliation":[{"name":"Instituto de Investigaci\u00f3n en Inform\u00e1tica de Albacete, Universidad de Castilla-La Mancha, 02071 Albacete, Spain"},{"name":"Conservatorio de M\u00fasica de Cieza \u201cMaestro G\u00f3mez Villa\u201d, Calle Cadenas, 6, 30530 Cieza, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4455-370X","authenticated-orcid":false,"given":"Roberto","family":"S\u00e1nchez-Reolid","sequence":"additional","affiliation":[{"name":"Instituto de Investigaci\u00f3n en Inform\u00e1tica de Albacete, Universidad de Castilla-La Mancha, 02071 Albacete, Spain"},{"name":"Departamento de Sistemas Inform\u00e1ticos, Universidad de Castilla-La Mancha, 02071 Albacete, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alicia","family":"Fern\u00e1ndez-Sotos","sequence":"additional","affiliation":[{"name":"Conservatorio de M\u00fasica de Murcia, Calle Cartagena, 74, 30002 Murcia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6159-5074","authenticated-orcid":false,"given":"Jos\u00e9 Miguel","family":"Latorre","sequence":"additional","affiliation":[{"name":"Departamento de Psicolog\u00eda, Universidad de Castilla-La Mancha, 02071 Albacete, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8211-0398","authenticated-orcid":false,"given":"Antonio","family":"Fern\u00e1ndez-Caballero","sequence":"additional","affiliation":[{"name":"Instituto de Investigaci\u00f3n en Inform\u00e1tica de Albacete, Universidad de Castilla-La Mancha, 02071 Albacete, Spain"},{"name":"Departamento de Sistemas Inform\u00e1ticos, Universidad de Castilla-La Mancha, 02071 Albacete, Spain"},{"name":"CIBERSAM (Biomedical Research Networking Centre in Mental Health), 28029 Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2050031","DOI":"10.1142\/S0129065720500318","article-title":"Deep support vector machines for the identification of stress condition from electrodermal activity","volume":"30","year":"2020","journal-title":"Int. J. Neural Syst."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1177\/1754073914565517","article-title":"Multiple arousal theory and daily-life electrodermal activity asymmetry","volume":"8","author":"Picard","year":"2016","journal-title":"Emot. Rev."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Pecchia, L., Chen, L.L., Nugent, C., and Bravo, J. (2014). A Framework for Recognizing and Regulating Emotions in the Elderly. Ambient Assisted Living and Daily Activities, Springer.","DOI":"10.1007\/978-3-319-13105-4"},{"key":"ref_4","unstructured":"Picard, R.W. (2000). Affective Computing, The MIT Press."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/j.neucom.2020.05.078","article-title":"Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications","volume":"410","author":"Segovia","year":"2020","journal-title":"Neurocomputing"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Jamil, F., Ahmad, S., Iqbal, N., and Kim, D.H. (2020). Towards a Remote Monitoring of Patient Vital Signs Based on IoT-Based Blockchain Integrity Management Platforms in Smart Hospitals. Sensors, 20.","DOI":"10.3390\/s20082195"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Pala, D., Caldarone, A.A., Franzini, M., Malovini, A., Larizza, C., Casella, V., and Bellazzi, R. (2020). Deep Learning to Unveil Correlations between Urban Landscape and Population Health. Sensors, 20.","DOI":"10.3390\/s20072105"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Rathore, H., Mohamed, A., and Guizani, M. (2020). A Survey of Blockchain Enabled Cyber-Physical Systems. Sensors, 20.","DOI":"10.3390\/s20010282"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Hazer-Rau, D., Meudt, S., Daucher, A., Spohrs, J., Hoffmann, H., Schwenker, F., and Traue, H.C. (2020). The uulmMAC Database\u2014A Multimodal Affective Corpus for Affective Computing in Human-Computer Interaction. Sensors, 20.","DOI":"10.3390\/s20082308"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Pham, S., Yeap, D., Escalera, G., Basu, R., Wu, X., Kenyon, N.J., Hertz-Picciotto, I., Ko, M.J., and Davis, C.E. (2020). Wearable sensor system to monitor physical activity and the physiological effects of heat exposure. Sensors, 20.","DOI":"10.3390\/s20030855"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"441","DOI":"10.3390\/s20020441","article-title":"A Novel Cost-Efficient Framework for Critical Heartbeat Task Scheduling Using the Internet of Medical Things in a Fog Cloud System","volume":"20","author":"Lakhan","year":"2020","journal-title":"Sensors"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"714","DOI":"10.1016\/j.chb.2017.06.019","article-title":"From road distraction to safe driving: Evaluating the effects of boredom and gamification on driving behaviour, physiological arousal, and subjective experience","volume":"75","author":"Steinberger","year":"2017","journal-title":"Comput. Hum. Behav."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2276","DOI":"10.3390\/s20082276","article-title":"Determining the Optimal Restricted Driving Zone Using Genetic Algorithm in a Smart City","volume":"20","author":"Azami","year":"2020","journal-title":"Sensors"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.jbi.2016.09.015","article-title":"Smart environment architecture for emotion recognition and regulation","volume":"64","author":"Pastor","year":"2016","journal-title":"J. Biomed. Informatics"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Lay-Ekuakille, A., and Mukhopadhyay, S.C. (2010). Wearable and Autonomous Biomedical Devices and Systems for Smart Environment, Springer.","DOI":"10.1007\/978-3-642-15687-8"},{"key":"ref_16","unstructured":"Mehrabian, A., and Russell, J.A. (1974). An Approach to Environmental Psychology, The MIT Press."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1161","DOI":"10.1037\/h0077714","article-title":"A circumplex model of affect","volume":"39","author":"Russell","year":"1980","journal-title":"J. Personal. Soc. Psychol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1007\/s12144-014-9219-4","article-title":"Pleasure, arousal, dominance: Mehrabian and Russell revisited","volume":"33","author":"Bakker","year":"2014","journal-title":"Curr. Psychol."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Bravo, J., Herv\u00e1s, R., and Villarreal, V. (2015). Arousal Level Classification in the Ageing Adult by Measuring Electrodermal Skin Conductivity. Ambient Intelligence for Health, Springer.","DOI":"10.1007\/978-3-319-26508-7"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.3389\/fneur.2018.01029","article-title":"Arousal effects on pupil size, heart rate, and skin conductance in an emotional face task","volume":"9","author":"Wang","year":"2018","journal-title":"Front. Neurol."},{"key":"ref_21","first-page":"159","article-title":"The electrodermal system","volume":"Volume 1","author":"Dawson","year":"2007","journal-title":"Handbook of Psychophysiology"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pone.0007487","article-title":"The rewarding aspects of music listening are related to degree of emotional arousal","volume":"4","author":"Salimpoor","year":"2009","journal-title":"PLOS ONE"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/0005-7916(94)90063-9","article-title":"Measuring emotion: The self-assessment manikin and the semantic differential","volume":"25","author":"Bradley","year":"1994","journal-title":"J. Behav. Ther. Exp. Psychiatry"},{"key":"ref_24","first-page":"63","article-title":"Observations: SAM: The Self-Assessment Manikin; an efficient cross-cultural measurement of emotional response","volume":"35","author":"Morris","year":"1995","journal-title":"J. Advert. Res."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Agrawal, A., and An, A. (2012, January 4\u20137). Unsupervised emotion detection from text using semantic and syntactic relations. Proceedings of the 2012 IEEE\/WIC\/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, Macau, China.","DOI":"10.1109\/WI-IAT.2012.170"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Canales, L., and Mart\u00ednez-Barco, P. (2014, January 20\u201324). Emotion detection from text: A survey. Proceedings of the Workshop on Natural Language Processing in the 5th Information Systems Research Working Days, Quito, Ecuador.","DOI":"10.3115\/v1\/W14-6905"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1750054","DOI":"10.1142\/S012906571750054X","article-title":"Neural Correlates of Phrase Quadrature Perception in Harmonic Rhythm: An EEG Study Using a Brain\u2013Computer Interface","volume":"28","author":"Latorre","year":"2018","journal-title":"Int. J. Neural Syst."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"29","DOI":"10.3389\/fninf.2017.00029","article-title":"Neural Correlates of Phrase Rhythm: An EEG Study of Bipartite vs. Rondo Sonata Form","volume":"11","author":"Latorre","year":"2017","journal-title":"Front. Neuroinformatics"},{"key":"ref_29","first-page":"80","article-title":"Influence of Tempo and Rhythmic Unit in Musical Emotion Regulation","volume":"10","author":"Latorre","year":"2016","journal-title":"Front. Comput. Neurosci."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Ferr\u00e1ndez Vicente, J.M., \u00c1lvarez-S\u00e1nchez, J.R., de la Paz L\u00f3pez, F., Toledo-Moreo, F.J., and Adeli, H. (2015). Elicitation of Emotions through Music: The Influence of Note Value. Artificial Computation in Biology and Medicine, Springer.","DOI":"10.1007\/978-3-319-18914-7_51"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1037\/0033-295X.85.2.59","article-title":"A theory of memory retrieval","volume":"85","author":"Ratcliff","year":"1978","journal-title":"Psychol. Rev."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1037\/0882-7974.19.2.272","article-title":"Life review therapy using autobiographical retrieval practice for older adults with depressive symptomatology","volume":"19","author":"Serrano","year":"2004","journal-title":"Psychol. Aging"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1002\/acp.2891","article-title":"Performance in autobiographical memory of older adults with depression symptoms","volume":"27","author":"Latorre","year":"2013","journal-title":"Appl. Cogn. Psychol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1177\/0963721413497013","article-title":"Emotional experience across adulthood: The theoretical model of strength and vulnerability integration","volume":"22","author":"Charles","year":"2013","journal-title":"Curr. Dir. Psychol. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"e12203","DOI":"10.1111\/exsy.12203","article-title":"Gerontechnologies\u2013Current achievements and future trends","volume":"34","author":"Navarro","year":"2017","journal-title":"Expert Syst."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1177\/1754073917749016","article-title":"Experimental methods for inducing basic emotions: A qualitative review","volume":"11","author":"Siedlecka","year":"2019","journal-title":"Emot. Rev."},{"key":"ref_37","unstructured":"Critchley, H., Nagai, Y., and Electrodermal Activity (EDA) (2013). Encyclopedia of Behavioral Medicine, Springer."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1111\/j.1469-8986.1993.tb03352.x","article-title":"Looking at pictures: Affective, facial, visceral, and behavioral reactions","volume":"30","author":"Lang","year":"1993","journal-title":"Psychophysiology"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Sarchiapone, M., Gramaglia, C., Iosue, M., Carli, V., Mandelli, L., Serretti, A., Marangon, D., and Zeppegno, P. (2018). The association between electrodermal activity (EDA), depression and suicidal behaviour: A systematic review and narrative synthesis. BMC Psychiatry, 18.","DOI":"10.1186\/s12888-017-1551-4"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez-Reolid, R., Mart\u00ednez-Rodrigo, A., and Fern\u00e1ndez-Caballero, A. (2019). Stress Identification from Electrodermal Activity by Support Vector Machines. Understanding the Brain Function and Emotions, Springer.","DOI":"10.1007\/978-3-030-19591-5_21"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Zangr\u00f3niz, R., Mart\u00ednez-Rodrigo, A., Pastor, J.M., L\u00f3pez, M.T., and Fern\u00e1ndez-Caballero, A. (2017). Electrodermal activity sensor for classification of calm\/distress condition. Sensors, 17.","DOI":"10.3390\/s17102324"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Posada-Quintero, H.F., and Chon, K.H. (2020). Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review. Sensors, 20.","DOI":"10.3390\/s20020479"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Mohino-Herranz, I., Gil-Pita, R., Rosa-Zurera, M., and Seoane, F. (2019). Activity Recognition Using Wearable Physiological Measurements: Selection of Features from a Comprehensive Literature Study. Sensors, 19.","DOI":"10.3390\/s19245524"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Silva Moreira, P., Chaves, P., Dias, R., Dias, N., and Almeida, P.R. (2019). Validation of Wireless Sensors for Psychophysiological Studies. Sensors, 19.","DOI":"10.3390\/s19224824"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.3758\/s13428-012-0314-x","article-title":"Norms of valence, arousal, and dominance for 13,915 English lemmas","volume":"45","author":"Warriner","year":"2013","journal-title":"Behav. Res. Methods"},{"key":"ref_46","first-page":"91","article-title":"Flamenco: De la marginalidad social a la referencia cultural pasando por la apropiaci\u00f3n pol\u00edtica","volume":"15","year":"2018","journal-title":"Revista de Investigaci\u00f3n sobre Flamenco La Madrug\u00e1"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.jneumeth.2010.04.028","article-title":"A continuous measure of phasic electrodermal activity","volume":"190","author":"Benedek","year":"2010","journal-title":"J. Neurosci. Methods"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"e12425","DOI":"10.1111\/exsy.12425","article-title":"Film mood induction and emotion classification using physiological signals for health and wellness promotion in older adults living alone","volume":"37","author":"Latorre","year":"2020","journal-title":"Expert Syst."},{"key":"ref_49","first-page":"237","article-title":"Instrumentalizaci\u00f3n pol\u00edtica de la m\u00fasica desde el franquismo hasta la consolidaci\u00f3n de la democracia en Espa\u00f1a","volume":"25","year":"2013","journal-title":"Revista del Centro de Estudios Hist\u00f3ricos de Granada y su Reino"},{"key":"ref_50","first-page":"343","article-title":"La m\u00fasica en el sistema propagand\u00edstio franquista","volume":"3","year":"1998","journal-title":"Hist. Comun. Soc."},{"key":"ref_51","first-page":"119","article-title":"(Re)construyendo la identidad musical espa\u00f1ola: el jazz y el discurso cultural del franquismo durante la Segunda Guerra Mundial","volume":"23","author":"Iglesias","year":"2010","journal-title":"Hist. Actual Online"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Al Machot, F., Ali, M., Ranasinghe, S., Mosa, A.H., and Kyandoghere, K. (2018, January 25-29). Improving subject-independent human emotion recognition using electrodermal activity sensors for active and assisted living. Proceedings of the 11th Pervasive Technologies Related to Assistive Environments Conference, Corfu, Greece.","DOI":"10.1145\/3197768.3201523"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Amalan, S., Shyam, A., Anusha, A., Preejith, S., Tony, A., Jayaraj, J., and Mohanasankar, S. (2018, January 11\u201313). Electrodermal activity based classification of induced stress in a controlled setting. Proceedings of the 2018 IEEE International Symposium on Medical Measurements and Applications, Rome, Italy.","DOI":"10.1109\/MeMeA.2018.8438703"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1109\/JSEN.2016.2623677","article-title":"Arousal and valence recognition of affective sounds based on electrodermal activity","volume":"17","author":"Greco","year":"2016","journal-title":"IEEE Sens. J."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Silveira, F., Eriksson, B., Sheth, A., and Sheppard, A. (2013, January 8\u201312). Predicting audience responses to movie content from electro-dermal activity signals. Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Zurich, Switzerland.","DOI":"10.1145\/2493432.2493508"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.neucom.2011.10.047","article-title":"A k-nearest-neighbor classifier with heart rate variability feature-based transformation algorithm for driving stress recognition","volume":"116","author":"Wang","year":"2013","journal-title":"Neurocomputing"},{"key":"ref_57","unstructured":"Mu\u00f1oz Exp\u00f3sito, J., Gal\u00e1n, S., Reyes, N., Candeas, P., and Pe\u00f1a, F. (2004, January 5\u20138). Speech\/music discrimination based on a new warped LPC-based feature and linear discriminant analysis. Proceedings of the 7th International Conference on Digital Audio Effects, Naples, Italy."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Bandara, D., Song, S., Hirshfield, L., and Velipasalar, S. (2016, January 17\u201322). A more complete picture of emotion using electrocardiogram and electrodermal activity to complement cognitive data. Proceedings of the 10th International Conference on Augmented Cognition, Toronto, ON, Canada.","DOI":"10.1007\/978-3-319-39955-3_27"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Jang, E.H., Park, B.J., Kim, S.H., Chung, M.A., Park, M.S., and Sohn, J.H. (2014, January 26\u201328). Emotion classification based on bio-signals emotion recognition using machine learning algorithms. Proceedings of the 2014 International Conference on Information Science, Electronics and Electrical Engineering, Sapporo City, Hokkaido, Japan.","DOI":"10.1109\/InfoSEEE.2014.6946144"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-018-35147-3","article-title":"Automatic detection of major depressive disorder using electrodermal activity","volume":"8","author":"Kim","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.bbr.2017.12.021","article-title":"Psychological stress level detection based on electrodermal activity","volume":"341","author":"Liu","year":"2018","journal-title":"Behav. Brain Res."},{"key":"ref_62","first-page":"1","article-title":"Mood classification through physiological parameters","volume":"106","author":"Cavallo","year":"2019","journal-title":"J. Ambient Intell. Humanized Comput."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Xin, S.Q., Yahya, N., and Izhar, L.I. (2019, January 15\u201317). Classification of Neurological States from Biosensor Signals Based on Statistical Features. Proceedings of the 2019 IEEE Student Conference on Research and Development, Perak, Malaysia.","DOI":"10.1109\/SCORED.2019.8896286"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Taylor, S., Jaques, N., Chen, W., Fedor, S., Sano, A., and Picard, R. (2015, January 25\u201329). Automatic identification of artifacts in electrodermal activity data. Proceedings of the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, Milan, Italy.","DOI":"10.1109\/EMBC.2015.7318762"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1177\/0305735696241005","article-title":"Cross-cultural comparisons in the affective response to music","volume":"24","author":"Gregory","year":"1996","journal-title":"Psychol. Music."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1525\/mp.2008.25.3.213","article-title":"Lost in translation: An enculturation effect in music memory performance","volume":"25","author":"Demorest","year":"2008","journal-title":"Music. Percept."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Pereira, C.S., Teixeira, J., Figueiredo, P., Xavier, J., Castro, S.L., and Brattico, E. (2011). Music and emotions in the brain: Familiarity matters. PlOS ONE, 6.","DOI":"10.1371\/journal.pone.0027241"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1177\/1029864915597567","article-title":"The impact of song-specific age and affective qualities of popular songs on music-evoked autobiographical memories (MEAMs)","volume":"19","author":"Platz","year":"2015","journal-title":"Music. Sci."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-018-35899-y","article-title":"The effect of memory in inducing pleasant emotions with musical and pictorial stimuli","volume":"8","author":"Maksimainen","year":"2018","journal-title":"Sci. Rep."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/17\/4788\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:06:17Z","timestamp":1760177177000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/17\/4788"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,25]]},"references-count":69,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2020,9]]}},"alternative-id":["s20174788"],"URL":"https:\/\/doi.org\/10.3390\/s20174788","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,8,25]]}}}