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dc.contributor.authorViejo, CG
dc.contributor.authorFuentes, S
dc.contributor.authorTorrico, DD
dc.contributor.authorDunshea, FR
dc.date.accessioned2020-12-17T04:21:18Z
dc.date.available2020-12-17T04:21:18Z
dc.date.issued2018-06-01
dc.identifierpii: s18061802
dc.identifier.citationViejo, C. G., Fuentes, S., Torrico, D. D. & Dunshea, F. R. (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 (6), https://doi.org/10.3390/s18061802.
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/11343/255272
dc.description.abstractTraditional methods to assess heart rate (HR) and blood pressure (BP) are intrusive and can affect results in sensory analysis of food as participants are aware of the sensors. This paper aims to validate a non-contact method to measure HR using the photoplethysmography (PPG) technique and to develop models to predict the real HR and BP based on raw video analysis (RVA) with an example application in chocolate consumption using machine learning (ML). The RVA used a computer vision algorithm based on luminosity changes on the different RGB color channels using three face-regions (forehead and both cheeks). To validate the proposed method and ML models, a home oscillometric monitor and a finger sensor were used. Results showed high correlations with the G color channel (R² = 0.83). Two ML models were developed using three face-regions: (i) Model 1 to predict HR and BP using the RVA outputs with R = 0.85 and (ii) Model 2 based on time-series prediction with HR, magnitude and luminosity from RVA inputs to HR values every second with R = 0.97. An application for the sensory analysis of chocolate showed significant correlations between changes in HR and BP with chocolate hardness and purchase intention.
dc.languageEnglish
dc.publisherMDPI
dc.titleNon-Contact Heart Rate and Blood Pressure Estimations from Video Analysis and Machine Learning Modelling Applied to Food Sensory Responses: A Case Study for Chocolate
dc.typeJournal Article
dc.identifier.doi10.3390/s18061802
melbourne.affiliation.departmentAgriculture and Food Systems
melbourne.source.titleSensors
melbourne.source.volume18
melbourne.source.issue6
dc.rights.licenseCC BY
melbourne.elementsid1332705
melbourne.contributor.authorTorrico, Damir
melbourne.contributor.authorFuentes Jara, Sigfredo Augusto
melbourne.contributor.authorDunshea, Frank
melbourne.contributor.authorGonzalez Viejo Duran, Claudia
melbourne.contributor.authorGonzalez Viejo Duran, Claudia
dc.identifier.eissn1424-8220
melbourne.accessrightsOpen Access


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