Name: protocol for data collection and analysis applied to automated facial expression analysis technology and temporal analysis for sensory evaluation
Uploaded: 2016-08-26T13:00:00
Description: Watch this Scientific Journal Video about Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation at JoVE.com

This project was funded, in part, by ConAgra Foods (Omaha, NE, USA), the Virginia Agricultural Experiment Station, the Hatch Program of the National Institute of Food and Agriculture, U.S. Department of Agriculture, and the Virginia Tech Water INTERface Interdisciplinary Graduate Education Program.

Etikk Uttalelse: Denne studien ble forhåndsgodkjent av Virginia Tech Institutional Review Board (IRB) (IRB 14-229) før du starter prosjektet. Forsiktig: Human lagt forskning krever informert samtykke før deltakelse. I tillegg til IRB-godkjenning, samtykke til bruk av stillbilder eller videobilder er også nødvendig før slippe noen bilder for utskrift, video eller grafisk avbildning. I tillegg er matallergenene beskrevet før testing. Deltakerne blir bedt om før panel start om de har noen intoleranse, allergi eller andre bekymr...

<ol>
	<li>De Wijk, R. A., Kooijman, V., Verhoeven, R. H. G., Holthuysen, N. T. E., De Graaf, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Autonomic+nervous+system+responses+on+and+facial+expressions+to+the+sight,+smell,+and+taste+of+liked+and+disliked+foods.">Autonomic nervous system responses on and facial expressions to the sight, smell, and taste of liked and disliked foods.</a> Food Qual Prefer. 26 (2), 196-203 (2012).</li><li>De Wijk, R. A., He, W., Mensink, M. G. J., Verhoeven, R. H. 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Optimization of a verbal measurement of odor-elicited emotions.</a> Food Qual Prefer. 21, 938-947 (2010).</li><li>Warrenburg, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+fragrance+on+emotions:+Moods+and+physiology.">Effects of fragrance on emotions: Moods and physiology.</a> Chem. Senses. 30, i248-i249 (2005).</li><li>Bredie, W. L. P., Tan, H. S. G., Wendin, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+comparative+study+on+facially+expressed+emotions+in+response+to+basic+tastes.">A comparative study on facially expressed emotions in response to basic tastes.</a> Chem. Percept. 7 (1), 1-9 (2014).</li><li>Wendin, K., Allesen-Holm, B. H., Bredie, L. 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Afea program i litteratur knyttet til mat og drikke er svært begrenset 1-11. Søknaden til mat er ny, og skaper en mulighet for å etablere metodikk og data tolkning. Arnade (2013) 7 funnet høy individuell variasjon blant enkelte følelsesmessig reaksjon på sjokolademelk og hvit melk kan bruke under kurven analyse og analyse av varians. Men selv med deltaker variabilitet, deltakere generert en lykkelig svar lengre mens trist og kvalm hadde kortere tid respons 7. I en separat studie me...

Automatisert ansiktsuttrykk analyse (Afea) er en potensiell analytisk verktøy for å karakterisere emosjonelle reaksjoner på drikkevarer og mat. Emosjonell analyse kan legge en ekstra dimensjon til eksisterende sensoriske vitenskap metoder, mat evalueringspraksis og hedonisk skala karakterer vanligvis brukes både i forskning og industri innstillinger. Emosjonell analyse kan gi en ekstra beregning som viser et mer nøyaktig svar på mat og drikke. Hedonic scoring kan omfatte deltaker skjevhet på grunn av manglende opptak reaksjoner 1. Afea forskning har blitt brukt i mange forskningssøknader, inkludert dataspill, brukeratferd, utdanning / pedagogikk, og psykologistudier på empati og bedrag. De fleste mat-forbundet forskning har fokusert på å karakterisere følelsesmessig reaksjon på mat kvalitet og menneskelig atferd med mat. Med den siste trenden i å få innsikt i nærings atferd, en økende mengde litteratur rapporter bruker av Afeafor å karakterisere det menneskelige følelsesmessig reaksjon i forbindelse med matvarer, drikkevarer og luktstoffer 1-12. Afea er avledet fra det Facial Handling Coding System (FACS). Ansikts handling kodesystem (FACS) diskriminerer ansikts bevegelser preget av handlingsenheter (AUS) på en 5-punkts intensitetsskalaen 13. Den FACS tilnærmingen krever trente gjennomgang eksperter, manuell koding, betydelig evaluering tid, og gir begrensede dataanalyse alternativer. Afea ble utviklet som en rask evaluering metode for å bestemme følelser. Afea programvare er avhengig av ansikts muskel bevegelse, ansikts databaser, og algoritmer for å karakterisere den følelsesmessige responsen 14-18. Den Afea programvaren som brukes i denne studien nådde en &quot;FACS indeks over enighet på 0,67 i gjennomsnitt på både Warszawa Sett av emosjonelle ansiktsuttrykk Bilder (WSEFEP) og Amsterdam Dynamic Facial Expression Set (ADFES), som er nær en standardavtale på 0,70 for manuell koding &quot;19 </sup&gt;. Universal følelser inngår i analysen er glade (positiv), trist (negativ), kvalm (negativ), overrasket (positivt eller negativt), sint (negativ), redd (negativ) og nøytral hver på en egen skala fra 0-1 ( 0 = ikke uttrykt; 1 = fullt uttrykt) 20. I tillegg inneholder psykologi litteratur glad, overrasket og sint som &quot;tilnærming&quot; følelser (mot stimuli) og trist, redd, og kvalm som &quot;abstinens&quot; følelser (bort fra aversive stimuli) 21. En begrensning av den nåværende afea programvare for å karakterisere følelser assosiert med matvarer er forstyrrelser fra ansiktsbevegelser i forbindelse med å tygge og svelge så vel som andre grovmotoriske bevegelser, som ekstrem hodebevegelser. Programvaren er rettet mot mindre ansikts muskel bevegelser, om posisjon og grad av bevegelse, basert på over 500 muskel punkter i ansiktet 16,17. Tygge bevegelser forstyrre klassifisering av uttrykk. denne grensenasjon kan rettes ved hjelp av flytende matvarer. Imidlertid kan andre metodeutfordringene også redusere video følsomhet og Afea analyse med datainnsamling miljø, teknologi, forsker instruksjoner, deltaker atferd, og deltaker attributter. En standard metodikk har ikke blitt utviklet og verifisert for optimal videoopptak og dataanalyse ved hjelp Afea for emosjonell respons på mat og drikke i en sensorisk evaluering laboratorium setting. Mange aspekter kan påvirke videoopptak miljø blant annet belysning, skygge på grunn av belysning, deltaker retninger, deltaker atferd, deltaker høyde, samt, kamera høyde, kamera sportsfiske, og utstyrs innstillinger. Videre dataanalyse metoder er inkonsekvent og mangler en standard metodikk for vurdering av emosjonell respons. Her vil vi vise vår standard prosedyre for å fange emosjonelle data og bearbeiding av data inn i meningsfulle resultater ved hjelp av drikkevarer (smaksatt melk, unflavored melk og unflavored vann) for evaluering. Så vidt vi vet bare en fagfellevurdert publikasjon, fra vår lab gruppe, har benyttet tidsserier for tolking for følelser analyse 8; Imidlertid har metoden blitt oppdatert for vår presentert metode. Vårt mål er å utvikle en bedre og konsistent metodikk for å hjelpe med reproduserbarhet i en sensorisk evaluering laboratorium setting. For demonstrasjon, formålet med studien modellen er å vurdere om Afea kunne supplere tradisjonell hedonic aksept vurdering av smakstilsatt melk, unflavored melk og unflavored vann. Hensikten med denne videoen protokollen er å bidra til å etablere Afea metodikk, standard videoopptak kriteriene i en sensorisk evaluering laboratorium (sensorisk messe innstilling), og illustrerer en metode for tidsmessig emosjonelle data analyse av en befolkning.

<table border="0" cellpadding="0" cellspacing="0" width="1087">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">2% Reduced Fat Milk</td>
			<td style="width:436px;">Kroger Brand, Cincinnati, OH or DZA Brands, LLC, Salisbury, NC</td>
			<td style="width:119px;">na</td>
			<td style="width:316px;">for solutions</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Drinking Water</td>
			<td>Kroger Brand, Cincinnati, OH</td>
			<td style="width:119px;">na</td>
			<td>for solutions</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Imitation Clear Vanilla Flavor</td>
			<td>Kroger Brand, Cincinnati, OH</td>
			<td style="width:119px;">na</td>
			<td>for solutions</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Iodized Salt</td>
			<td>Kroger Brand, Cincinnati, OH</td>
			<td style="width:119px;">na</td>
			<td>for solutions</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">FaceReader 6</td>
			<td style="width:436px;">Noldus Information Technology, Wageningen, The Netherlands</td>
			<td style="width:119px;">na</td>
			<td>For Facial Analysis</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">Sensory Information Management System (SIMS) 2000</td>
			<td style="width:436px;">Sensory Computer Systems, Berkeley Heights, NJ</td>
			<td style="width:119px;">Version 6</td>
			<td>For Sensory Data Capture</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Rhapsody</td>
			<td style="width:436px;">Acuity Brands Lighting, Inc., Conyers, GA</td>
			<td style="width:119px;"></td>
			<td>For Environment Illumination</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">R Version&#160;</td>
			<td style="width:436px;">R Core Team 2015</td>
			<td style="width:119px;">3.1.1</td>
			<td>For Statistical Analysis</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Microsoft Office</td>
			<td style="width:436px;">Microsoft</td>
			<td style="width:119px;">na</td>
			<td>For Statistical Analysis</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">JMP</td>
			<td style="width:436px;">Statistical Analysis Software (SAS) Version 9.2, SAS Institute, Cary, NC</td>
			<td style="width:119px;">na</td>
			<td>For Statistical Analysis</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Media Recorder 2.5</td>
			<td style="width:436px;">Noldus Information Technology, Wageningen, The Netherlands</td>
			<td style="width:119px;">na</td>
			<td>For capturing participants sensory evaluation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Axis M1054 Camera</td>
			<td style="width:436px;">Axis Communications, Lund, Sweden</td>
			<td style="width:119px;">na</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Beverage</td>
			<td style="width:436px;"></td>
			<td style="width:119px;">na</td>
			<td>Beverage or soft food for evaluation</td>
		</tr>
	</tbody>
</table>

protocol for data collection and analysis applied to automated facial expression analysis technology and temporal analysis for sensory evaluation

We demonstrate a method for capturing emotional response to beverages and liquefied foods in a sensory evaluation laboratory using automated facial expression analysis (AFEA) software. Additionally, we demonstrate a method for extracting relevant emotional data output and plotting the emotional response of a population over a specified time frame. By time pairing each participant's treatment response to a control stimulus (baseline), the overall emotional response over time and across multiple participants can be quantified. AFEA is a prospective analytical tool for assessing unbiased response to food and beverages. At present, most research has mainly focused on beverages. Methodologies and analyses have not yet been standardized for the application of AFEA to beverages and foods; however, a consistent standard methodology is needed. Optimizing video capture procedures and resulting video quality aids in a successful collection of emotional response to foods. Furthermore, the methodology of data analysis is novel for extracting the pertinent data relevant to the emotional response. The combinations of video capture optimization and data analysis will aid in standardizing the protocol for automated facial expression analysis and interpretation of emotional response data.

Fremgangsmåten foreslår en standard protokoll for afea datainnsamling. Om det er tatt foreslåtte protokoll trinn, ubrukelig følelsesmessig datautgangs (figur 1) som følge av dårlig datainnsamling (Figur 2: A; Venstre bilde) kan være begrenset. Tidsserieanalyse kan ikke benyttes hvis loggfiler (.txt) hovedsakelig inneholde &quot;FIT_FAILED&quot; og &quot;FIND_FAILED&quot; som dette er dårlige data (figur 1). Videre omfatter fremga...

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Protocol for Data Collection and Analysis Applied to Automated Facial Expression Analysis Technology and Temporal Analysis for Sensory Evaluation

En protokoll for å fange og statistisk analyse av følelsesmessig reaksjon av en befolkning til å drikke og flytende matvarer i en sensorisk evaluering laboratorium ved hjelp av automatisert ansiktsuttrykk analyseprogramvare er beskrevet.

Protokoll for datainnsamling og analyse for automatiserte Facial Expression Analysis Teknologi og Temporal analyse for sensorisk evaluering

We demonstrate a method for capturing emotional response to beverages and liquefied foods in a sensory evaluation laboratory using automated facial ...

Research

JoVE Journal

Behavior

Contextual and Cued Fear Conditioning Test Using a Video Analyzing System in Mice

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The contextual and cued fear conditioning test is one of the behavioral tests that assesses the ability of mice to learn and remember an association ...

Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia

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Adolescence is a critical developmental period where the early symptoms of schizophrenia frequently emerge. First-degree relatives of people with ...

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Mice emit ultrasonic vocalizations in different contexts throughout development and in adulthood. These vocal signals are now currently used as proxies ...

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This protocol describes how to conduct temporal-order experiments to measure visual processing speed and the attentional resource distribution. The ...

Automated Analysis of a Nematode Population-based Chemosensory Preference Assay

Automatisert analyse av en nematode-populasjonsbasert kjemosensorisk preferanseanalyse

The nematode, Caenorhabditis elegans' compact nervous system of only 302 neurons underlies a diverse repertoire of behaviors. To facilitate the dissection ...

Virtual Reality Experiments with Physiological Measures

Virtual Reality eksperimenter med fysiologiske tiltak

Virtual reality (VR) experiments are increasingly employed because of their internal and external validity compared to real-world observation and ...

Biomechanical Analysis Methods to Assess Professional Badminton Players' Lunge Performance

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Under the condition of simulating a badminton court in the laboratory, this study used the injury mechanism model to analyze the maximal right lunge ...

Low-cost Protocol of Footprint Analysis and Hanging Box Test for Mice Applied the Chronic Restraint Stress

Rimelig protokollen fotavtrykk analyse og hengende boks Test for mus brukes kronisk tilbakeholdenhet Stress

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Modified Blood Collection from Tail Veins of Non-anesthetized Mice with a Vacuum Blood Collection System and Eyeglass Magnifier

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Blood sample collection is the basis of experimental animal research. It is of importance to obtain adequate blood samples for various research purposes. ...

Using Facial Electromyography to Assess Facial Muscle Reactions to Experienced and Observed Affective Touch in Humans

Bruke ansikts Elektromyografi å vurdere ansikts muskler reaksjoner til erfarne og observerte affektive Touch hos mennesker

"Affective" touch is believed to be processed in a manner distinct from discriminatory touch and to involve activation of C-tactile (CT) afferent fibers. ...