Correction: Analysis of facial expressions in response to basic taste stimuli using artificial intelligence to predict perceived hedonic ratings

Yamamoto, Takashi; Mizuta, Haruno; Ueji, Kayoko

doi:10.1371/journal.pone.0258707

Cited by 3 publications

(1 citation statement)

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“…Older children can also use VAS scales [ 70 ]. For younger children, it may be necessary to use trained observers or automated facial recognition methodologies to assess the child’s reaction from their facial responses and their action (e.g., whether they grimace or spit out the sample) [ 71 , 72 ]. Where the sample can actually be taken by a child, the CAST system [ 73 ], which has recently received a letter of support from the EMA for acceptability testing [ 74 ], can provide a structured, multifaceted assessment of overall sample acceptability [ 75 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 ].…”

Section: Human Sensory Analysismentioning

confidence: 99%

A Guide to Best Practice in Sensory Analysis of Pharmaceutical Formulations

Clapham,

Belissa,

Inghelbrecht

et al. 2023

Pharmaceutics

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It is well established that treatment regime compliance is linked to the acceptability of a pharmaceutical formulation, and hence also to therapeutic outcomes. To that end, acceptability must be assessed during the development of all pharmaceutical products and especially for those intended for paediatric patients. Although acceptability is a multifaceted concept, poor sensory characteristics often contribute to poor patient acceptability. In particular, poor taste is often cited as a major reason for many patients, especially children, to refuse to take their medicine. It is thus important to understand and, as far as possible, optimise the sensory characteristics and, in particular, the taste/flavour/mouthfeel of the formulation throughout the development of the product. Sensory analysis has been widely practiced, providing objective data concerning the sensory aspects of food and cosmetic products. In this paper, we present proposals concerning how the well-established principles of sensory analysis can best be applied to pharmaceutical product development, allowing objective, scientifically valid, sensory data to be obtained safely. We briefly discuss methodologies that may be helpful in reducing the number of samples that may need to be assessed by human volunteers. However, it is only possible to be sure whether or not the sensory characteristics of a pharmaceutical product are non-aversive to potential users by undertaking sensory assessments in human volunteers. Testing is also required during formulation assessment and to ensure that the sensory characteristics remain acceptable throughout the product shelf life. We provide a risk assessment procedure to aid developers to define where studies are low risk, the results of a survey of European regulators on their views concerning such studies, and detailed guidance concerning the types of sensory studies that can be undertaken at each phase of product development, along with guidance about the practicalities of performing such sensory studies. We hope that this guidance will also lead to the development of internationally agreed standards between industry and regulators concerning how these aspects should be measured and assessed throughout the development process and when writing and evaluating regulatory submissions. Finally, we hope that the guidance herein will help formulators as they seek to develop better medicines for all patients and, in particular, paediatric patients.

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Section: Human Sensory Analysismentioning

confidence: 99%

A Guide to Best Practice in Sensory Analysis of Pharmaceutical Formulations

Clapham,

Belissa,

Inghelbrecht

et al. 2023

Pharmaceutics

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Real-time Evaluation of Food Acceptance From Facial Expressions Based on Exponential Decay

Han

Gopalakrishnan

2023

2023 15th International Conference on Knowledge and Smart Technology (KST)

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Predicting Perceived Hedonic Ratings through Facial Expressions of Different Drinks

Matsufuji,

Ueji,

Yamamoto

2023

Foods

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Previous studies have established the utility of facial expressions as an objective assessment approach for determining the hedonics (overall pleasure) of food and beverages. This study endeavors to validate the conclusions drawn from preceding research, illustrating that facial expressions prompted by tastants possess the capacity to forecast the perceived hedonic ratings of these tastants. Facial expressions of 29 female participants, aged 18–55 years, were captured using a digital camera during their consumption of diverse concentrations of solutions representative of five basic tastes. Employing the widely employed facial expression analysis application FaceReader, the facial expressions were meticulously assessed, identifying seven emotions (surprise, happiness, scare, neutral, disgust, sadness, and anger) characterized by scores ranging from 0 to 1—a numerical manifestation of emotional intensity. Simultaneously, participants rated the hedonics of each solution, utilizing a scale spanning from −5 (extremely unpleasant) to +5 (extremely pleasant). Employing a multiple linear regression analysis, a predictive model for perceived hedonic ratings was devised. The model’s efficacy was scrutinized by assessing emotion scores from 11 additional taste solutions, sampled from 20 other participants. The anticipated hedonic ratings demonstrated robust alignment and agreement with the observed ratings, underpinning the validity of earlier findings even when incorporating diverse software and taste stimuli across a varied participant base. We discuss some limitations and practical implications of our technique in predicting food and beverage hedonics using facial expressions.

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Correction: Analysis of facial expressions in response to basic taste stimuli using artificial intelligence to predict perceived hedonic ratings

Cited by 3 publications

References 1 publication

A Guide to Best Practice in Sensory Analysis of Pharmaceutical Formulations

A Guide to Best Practice in Sensory Analysis of Pharmaceutical Formulations

Real-time Evaluation of Food Acceptance From Facial Expressions Based on Exponential Decay

Predicting Perceived Hedonic Ratings through Facial Expressions of Different Drinks

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