2017
DOI: 10.1016/j.jped.2016.06.011 View full text |Buy / Rent full text
|
|

Abstract: These results confirm that the proposed method has an efficient power to detect significant differences between neutral and sucrose stimuli. In conclusion, this evaluation method of hedonic facial reactions in newborns reflects the response to a specific taste.

Help me understand this report

Search citation statements

Order By: Relevance
Select...
3
1
1
3
5
0

Year Published

2019
2019
2021
2021

Publication Types

Select...
4

Relationship

0
4

Authors

Journals

3
5
0
Order By: Relevance
“…Recently, however, researchers [3,4,7,[22][23][24][25][26][27][28] have used much more convenient and accurate automated facial expression recognition systems, including sophisticated artificial network systems such as FaceReader or iMotions software (iMotions, Inc., Copenhagen, Denmark), which can classify facial expressions into the following basic universal human emotions suggested by Ekman and Friesen [29], with intensity ranging from 0 to 1: happy, sad, angry, surprised, scared, disgusted, and neutral. Analyses of these emotions are utilized effectively in various experimental situations in food research, e.g., a time course of changes in each emotion after tasting breakfast drinks [7], a comparison between implicit (spontaneous) and explicit (intentional) facial expressions after tasting different juices [22], a comparison between before and after sensory-specific satiety [24], a correlation between hedonic liking and facial expressions [27], a comparison of facial expressions in response to different tastes between persons with and without depressive disorders [4], and differences in responses to various food stimuli between Asians and Western populations [3,26].…”
Section: Plos Onementioning
See 1 more Smart Citation
Create an account to read the remaining citation statements from this report. You will also get access to:
  • Search over 1.2b+ citation statments to see what is being said about any topic in the research literature
  • Advanced Search to find publications that support or contrast your research
  • Citation reports and visualizations to easily see what publications are saying about each other
  • Browser extension to see Smart Citations wherever you read research
  • Dashboards to evaluate and keep track of groups of publications
  • Alerts to stay on top of citations as they happen
  • Automated reference checks to make sure you are citing reliable research in your manuscripts
  • 7 day free preview of our premium features.

Trusted by researchers and organizations around the world

Over 130,000 students researchers, and industry experts at use scite

See what students are saying

rupbmjkragerfmgwileyiopcupepmcmbcthiemesagefrontiersapsiucrarxivemeralduhksmucshluniversity-of-gavle
“…Recently, however, researchers [3,4,7,[22][23][24][25][26][27][28] have used much more convenient and accurate automated facial expression recognition systems, including sophisticated artificial network systems such as FaceReader or iMotions software (iMotions, Inc., Copenhagen, Denmark), which can classify facial expressions into the following basic universal human emotions suggested by Ekman and Friesen [29], with intensity ranging from 0 to 1: happy, sad, angry, surprised, scared, disgusted, and neutral. Analyses of these emotions are utilized effectively in various experimental situations in food research, e.g., a time course of changes in each emotion after tasting breakfast drinks [7], a comparison between implicit (spontaneous) and explicit (intentional) facial expressions after tasting different juices [22], a comparison between before and after sensory-specific satiety [24], a correlation between hedonic liking and facial expressions [27], a comparison of facial expressions in response to different tastes between persons with and without depressive disorders [4], and differences in responses to various food stimuli between Asians and Western populations [3,26].…”
Section: Plos Onementioning
“…Therefore, in this study, we aimed to analyze facial expressions with the aid of artificial intelligence (AI) technology to examine whether facial expressions can be used as a method for rating food and beverage hedonics. Essentially, the same approach has recently been assessed by several researchers in different fields of food research [3,4,[22][23][24][25][26][27][28]. Most researchers have used an automated facial expression recognition system (computer software with built-in information about changes in human facial expressions to different emotions) such as FaceReader (Noldus Information Technology, Wageningen, The Netherlands) to analyze facial expressions in response to various food and beverage stimuli under different experimental conditions using basic expressions of human emotions, such as happiness, anger, sadness, and disgust.…”
Section: Introductionmentioning
“…A previous study has analyzed videotaped facial reactions in human infants and non-human infant/adult primates during the ingestion of liquids of various tastes, and found that tongue protrusions and gapes to sucrose and quinine, respectively, were elicited universally across species [21]. Studies consistently observed mouth motions in response to sucrose solution in human infants [22][23][24][25][26] and adults [27,28]. These data suggest that mouth movements related to consumption could be modulated by hedonic experiences during tasting.…”
Section: Introductionmentioning
“…However, due to the absence of thresholds in the literature for a technical error of measurement in orofacial measurements, we chose to use the Bland-Altman graph (27) to evaluate possible discrepancies. However, it was observed that of the analyzed variables, the discards were justified on 1 or 2 occasions in each variable, resulting in at least 95.6% of the observations with reliability.…”
Section: Methodsmentioning