{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T07:26:25Z","timestamp":1768980385007,"version":"3.49.0"},"reference-count":40,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T00:00:00Z","timestamp":1637107200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Unlocking the Food Value Chain: Australian industry transformation for ASEAN markets","award":["IH120100053"],"award-info":[{"award-number":["IH120100053"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>New and emerging non-invasive digital tools, such as eye-tracking, facial expression and physiological biometrics, have been implemented to extract more objective sensory responses by panelists from packaging and, specifically, labels. However, integrating these technologies from different company providers and software for data acquisition and analysis makes their practical application difficult for research and the industry. This study proposed a prototype integration between eye tracking and emotional biometrics using the BioSensory computer application for three sample labels: Stevia, Potato chips, and Spaghetti. Multivariate data analyses are presented, showing the integrative analysis approach of the proposed prototype system. Further studies can be conducted with this system and integrating other biometrics available, such as physiological response with heart rate, blood, pressure, and temperature changes analyzed while focusing on different label components or packaging features. By maximizing data extraction from various components of packaging and labels, smart predictive systems can also be implemented, such as machine learning to assess liking and other parameters of interest from the whole package and specific components.<\/jats:p>","DOI":"10.3390\/s21227641","type":"journal-article","created":{"date-parts":[[2021,11,17]],"date-time":"2021-11-17T09:16:11Z","timestamp":1637140571000},"page":"7641","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Digital Integration and Automated Assessment of Eye-Tracking and Emotional Response Data Using the BioSensory App to Maximize Packaging Label Analysis"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0377-5085","authenticated-orcid":false,"given":"Sigfredo","family":"Fuentes","sequence":"first","affiliation":[{"name":"Digital Agriculture Food and Wine Group, School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Parkville, VIC 3010, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9207-9307","authenticated-orcid":false,"given":"Claudia","family":"Gonzalez Viejo","sequence":"additional","affiliation":[{"name":"Digital Agriculture Food and Wine Group, School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Parkville, VIC 3010, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1482-2438","authenticated-orcid":false,"given":"Damir D.","family":"Torrico","sequence":"additional","affiliation":[{"name":"Department of Wine, Food and Molecular Biosciences, Faculty of Agriculture and Life Sciences, Lincoln University, Lincoln 7647, Canterbury, New Zealand"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3998-1240","authenticated-orcid":false,"given":"Frank R.","family":"Dunshea","sequence":"additional","affiliation":[{"name":"Digital Agriculture Food and Wine Group, School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Parkville, VIC 3010, Australia"},{"name":"Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, UK"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,17]]},"reference":[{"key":"ref_1","first-page":"26","article-title":"Food Companies Get Smart About Artificial Intelligence","volume":"72","author":"Buss","year":"2018","journal-title":"Food Technol."},{"key":"ref_2","first-page":"104","article-title":"Dynamics of autonomic nervous system responses and facial expressions to odors","volume":"5","author":"He","year":"2014","journal-title":"Appl. Olfactory Cogn."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"9616301","DOI":"10.1155\/2018\/9616301","article-title":"Neurophysiological responses to different product experiences","volume":"2018","author":"Modica","year":"2018","journal-title":"Comput. Intell. Neurosci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.foodqual.2017.06.017","article-title":"Sensory expectation, perception, and autonomic nervous system responses to package colours and product popularity","volume":"62","author":"Goedegebure","year":"2017","journal-title":"Food Qual. Prefer."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.physbeh.2018.03.003","article-title":"Consumers\u2019 physiological and verbal responses towards product packages: Could these responses anticipate product choices?","volume":"200","year":"2019","journal-title":"Physiol. Behav."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Gonzalez Viejo, C., Torrico, D., Dunshea, F., and Fuentes, S. (2019). Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages. Beverages, 5.","DOI":"10.3390\/beverages5040062"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/j.biopsycho.2010.03.010","article-title":"Autonomic nervous system activity in emotion: A review","volume":"84","author":"Kreibig","year":"2010","journal-title":"Biol. Psychol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.foodqual.2015.01.009","article-title":"Emotional responses towards food packaging: A joint application of self-report and physiological measures of emotion","volume":"42","author":"Liao","year":"2015","journal-title":"Food Qual. Prefer."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Vila-L\u00f3pez, N., Kuster-Boluda, I., and Alacreu-Crespo, A. (2021). Designing a Low-Fat Food Packaging: Comparing Consumers\u2019 Responses in Virtual and Physical Shopping Environments. Foods, 10.","DOI":"10.3390\/foods10020211"},{"key":"ref_10","unstructured":"Cuesta, U., Ni\u00f1o, J.I., and Mart\u00ednez-Mart\u00ednez, L. (2018, January 9\u201310). Neuromarketing: Analysis of Packaging Using Gsr, Eye-Tracking and Facial Expression. Proceedings of the Paper presented at The European Conference on Media, Communication & Film, Brighton, UK."},{"key":"ref_11","first-page":"4","article-title":"The conjoint effect of front-label claims\u2019 surface size and distance-to-center on customers\u2019 visual attention and emotional response","volume":"11","author":"Carbonell","year":"2019","journal-title":"J. Appl. Packag. Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1016\/j.foodqual.2018.04.008","article-title":"How do implicit\/explicit attitudes and emotional reactions to sustainable logo relate? A neurophysiological study","volume":"71","author":"Songa","year":"2019","journal-title":"Food Qual. Prefer."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.cofs.2021.03.014","article-title":"Novel digital technologies implemented in sensory science and consumer perception","volume":"41","author":"Fuentes","year":"2021","journal-title":"Curr. Opin. Food Sci."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Fuentes, S., Gonzalez Viejo, C., Torrico, D., and Dunshea, F. (2018). Development of a biosensory computer application to assess physiological and emotional responses from sensory panelists. Sensors, 18.","DOI":"10.3390\/s18092958"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"413","DOI":"10.1016\/j.compedu.2018.06.023","article-title":"A systematic review of eye tracking research on multimedia learning","volume":"125","author":"Alemdag","year":"2018","journal-title":"Comput. Educ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1080\/24721840.2018.1514978","article-title":"Eye-tracking measures in aviation: A selective literature review","volume":"28","author":"Wickens","year":"2018","journal-title":"Int. J. Aerosp. Psychol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1244","DOI":"10.1080\/13683500.2017.1367367","article-title":"A review of eye-tracking research in tourism","volume":"22","author":"Scott","year":"2019","journal-title":"Curr. Issues Tour."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1845","DOI":"10.3389\/fpsyg.2017.01845","article-title":"Eye-tracking technology and the dynamics of natural gaze behavior in sports: A systematic review of 40 years of research","volume":"8","author":"Kredel","year":"2017","journal-title":"Front. Psychol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"110389","DOI":"10.1016\/j.foodres.2021.110389","article-title":"Eye-tracking research on sensory and consumer science: A review, pitfalls and future directions","volume":"145","author":"Motoki","year":"2021","journal-title":"Food Res. Int."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Duerrschmid, K., and Danner, L. (2018). Eye tracking in consumer research. Methods in Consumer Research, Volume 2, Elsevier.","DOI":"10.1016\/B978-0-08-101743-2.00012-1"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"406","DOI":"10.5993\/AJHB.43.2.16","article-title":"Warning labels on sugar-sweetened beverages: An eye tracking approach","volume":"43","author":"Popova","year":"2019","journal-title":"Am. J. Health Behav."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.foodqual.2018.05.012","article-title":"Does attention to health labels predict a healthy food choice? An eye-tracking study","volume":"69","author":"Fenko","year":"2018","journal-title":"Food Qual. Prefer."},{"key":"ref_23","first-page":"524","article-title":"Perception of wine labels by generation Z: Eye-tracking experiment","volume":"10","year":"2016","journal-title":"Potravin. Slovak J. Food Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1108\/IJWBR-07-2019-0044","article-title":"Looking behind eye-catching design: An eye-tracking study on wine bottle design preference","volume":"33","author":"Merdian","year":"2020","journal-title":"Int. J. Wine Bus. Res."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Fazio, M., Reitano, A., and Loizzo, M.R. (2021). Consumer Preferences for New Products: Eye Tracking Experiment on Labels and Packaging for Olive Oil Based Dressing. Proceedings, 70.","DOI":"10.3390\/foods_2020-08124"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"103962","DOI":"10.1016\/j.foodqual.2020.103962","article-title":"The influence of taste-congruent soundtracks on visual attention and food choice: A cross-cultural eye-tracking study in Chinese and Danish consumers","volume":"85","author":"Byrne","year":"2020","journal-title":"Food Qual. Prefer."},{"key":"ref_27","first-page":"18393349211028676","article-title":"Elevating Food Perceptions Through Luxury Verbal Cues: An Eye-Tracking and Electrodermal Activity Experiment","volume":"2021","author":"Sung","year":"2021","journal-title":"Australas. Mark. J."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.measurement.2016.11.039","article-title":"Evaluation of psychological effects on human postural stability","volume":"98","author":"Frelih","year":"2017","journal-title":"Measurement"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Gonzalez Viejo, C., Fuentes, S., Torrico, D., and Dunshea, F. (2018). Non-Contact Heart Rate and Blood Pressure Estimations from Video Analysis and Machine Learning Modelling Applied to Food Sensory Responses: A Case Study for Chocolate. Sensors, 18.","DOI":"10.3390\/s18061802"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1177\/1359105317692856","article-title":"Emotional responses to disfigured faces and disgust sensitivity: An eye-tracking study","volume":"24","author":"Stone","year":"2019","journal-title":"J. Health Psychol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1108\/IJWBR-03-2019-0017","article-title":"Understanding the role of visual attention on wines\u2019 purchase intention: An eye-tracking study","volume":"32","author":"Monteiro","year":"2019","journal-title":"Int. J. Wine Bus. Res."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Gunaratne, N.M., Fuentes, S., Gunaratne, T.M., Torrico, D.D., Ashman, H., Francis, C., Gonzalez Viejo, C., and Dunshea, F.R. (2019). Consumer acceptability, eye fixation, and physiological responses: A study of novel and familiar chocolate packaging designs using eye-tracking devices. Foods, 8.","DOI":"10.3390\/foods8070253"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.physbeh.2018.02.051","article-title":"Integration of non-invasive biometrics with sensory analysis techniques to assess acceptability of beer by consumers","volume":"200","author":"Fuentes","year":"2019","journal-title":"Physiol. Behav."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.foodcont.2018.04.037","article-title":"Robotics and computer vision techniques combined with non-invasive consumer biometrics to assess quality traits from beer foamability using machine learning: A potential for artificial intelligence applications","volume":"92","author":"Fuentes","year":"2018","journal-title":"Food Control"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1080\/10454446.2017.1311815","article-title":"The effect of organic food labels on consumer attention","volume":"24","author":"Drexler","year":"2018","journal-title":"J. Food Prod. Mark."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.ijpsycho.2016.01.001","article-title":"Testing the effects of a disgust placebo with eye tracking","volume":"101","author":"Schienle","year":"2016","journal-title":"Int. J. Psychophysiol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1007\/s40708-016-0031-9","article-title":"Wavelet-based study of valence\u2013arousal model of emotions on EEG signals with LabVIEW","volume":"3","author":"Aydin","year":"2016","journal-title":"Brain Inform."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.foodqual.2016.01.009","article-title":"Visual attention accompanying food decision process: An alternative approach to choose the best models","volume":"51","author":"Gere","year":"2016","journal-title":"Food Qual. Prefer."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-019-42764-z","article-title":"Machine learning accurately classifies age of toddlers based on eye tracking","volume":"9","author":"Dalrymple","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1016\/j.lwt.2017.10.048","article-title":"Analysis of thermochromic label elements and colour transitions using sensory acceptability and eye tracking techniques","volume":"89","author":"Torrico","year":"2018","journal-title":"LWT Food Sci. Technol."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/22\/7641\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:31:38Z","timestamp":1760167898000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/22\/7641"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,17]]},"references-count":40,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["s21227641"],"URL":"https:\/\/doi.org\/10.3390\/s21227641","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,17]]}}}