Human Taste-Perception: Brain Computer Interface (BCI) and Its Application as an Engineering Tool for Taste-Driven Sensory Studies

Anbarasan, R.; Gómez-Carmona, Diego; Radhakrishnan, Mahendran

doi:10.1007/s12393-022-09308-0

Cited by 25 publications

(10 citation statements)

References 143 publications

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“…In this regard, consumers' perceptions of food products can be analyzed through the brain-computer interface method to obtain unbiased results from the consumers. 164 Therefore, Coutinho et al 165 surveyed the perception of chocolate milk with 1085 participants. The study revealed that consumers are more concerned about the CP-treated product price and feel the plasma-treated product will be costlier than the conventionally processed products.…”

Section: Sensory and Consumer Perception Of Plasma Treated-food Productsmentioning

confidence: 99%

Plasma processing: a sustainable technology in agri-food processing

Rajan

Boopathy

Radhakrishnan

et al. 2023

Sustainable Food Technol.

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Section: Sensory and Consumer Perception Of Plasma Treated-food Productsmentioning

confidence: 99%

Plasma processing: a sustainable technology in agri-food processing

Rajan

Boopathy

Radhakrishnan

et al. 2023

Sustainable Food Technol.

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“…Researching other modalities of interaction as well as multimodal XR experiences, could provide interesting opportunities to cater to different patients' needs and scenarios. Capitalizing on new advances in designing novel interfaces for XR such as olfactory (Wang et al, 2020), gustatory (Anbarasan et al, 2022), and haptic feedback could also provide options for building adaptive interfaces that provide a customized user experience in therapeutic applications. An ambitious but very promising opportunity lies in the development of XR serious games for mental health that allow for multimodal interactions while capturing the patients' biofeedback.…”

Section: Multimodal Interaction and Adaptive Interfacesmentioning

confidence: 99%

Extended reality for mental health: Current trends and future challenges

Pons

Navas-Medrano

Soler-Domínguez

2022

Front. Comput. Sci.

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Virtual and augmented reality have been used to diagnose and treat several mental health disorders for decades. Technological advances in these fields have facilitated the availability of commercial solutions for end customers and practitioners. However, there are still some barriers and limitations that prevent these technologies from being widely used by professionals on a daily basis. In addition, the COVID-19 pandemic has exposed a variety of new scenarios in which these technologies could play an essential role, like providing remote treatment. Disorders that traditionally had received less attention are also getting in the spotlight, such as depression or obsessive-compulsive disorder. Improvements in equipment and hardware, like Mixed Reality Head Mounted Displays, could help open new opportunities in the mental health field. Extended reality (XR) is an umbrella term meant to comprise Virtual reality (VR), mixed reality (MR), and augmented reality (AR). While XR applications are eminently visual, other senses are being explored in literature around multisensory interactions, such as auditory, olfactory, or haptic feedback. Applying such stimuli within XR experiences around mental disorders is still under-explored and could greatly enrich the therapeutic experience. This manuscript reviews recent research regarding the use of XR for mental health scenarios, highlighting trends, and potential applications as well as areas for improvement. It also discusses future challenges and research areas in upcoming topics such as the use of wearables, multisensory, and multimodal interaction. The main goal of this paper is to unpack how these technologies could be applied to XR scenarios for mental health to exploit their full potential and follow the path of other health technologies by promoting personalized medicine.

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“…On the other hand, developing The process of food tasting starts from tongue, where different taste receptors respond to various taste stimuli and pass the signals to the cortex of the brain region. Several important factors influence the taste perception and brain response, as age, gender, ethnicity, habits, stimuli type, temperature, and state of mind (41). Monitoring brain activity is an alternative to access psychological factors.…”

Section: Signal Processing and Convolutional Neural Network Trainingmentioning

confidence: 99%

The convolutional neural network as a tool to classify electroencephalography data resulting from the consumption of juice sweetened with caloric or non-caloric sweeteners

Atzingen¹,

Arteaga

Silva³

et al. 2022

Front. Nutr.

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Sweetener type can influence sensory properties and consumer’s acceptance and preference for low-calorie products. An ideal sweetener does not exist, and each sweetener must be used in situations to which it is best suited. Aspartame and sucralose can be good substitutes for sucrose in passion fruit juice. Despite the interest in artificial sweeteners, little is known about how artificial sweeteners are processed in the human brain. Here, we applied the convolutional neural network (CNN) to evaluate brain signals of 11 healthy subjects when they tasted passion fruit juice equivalently sweetened with sucrose (9.4 g/100 g), sucralose (0.01593 g/100 g), or aspartame (0.05477 g/100 g). Electroencephalograms were recorded for two sites in the gustatory cortex (i.e., C3 and C4). Data with artifacts were disregarded, and the artifact-free data were used to feed a Deep Neural Network with tree branches that applied a Convolutions and pooling for different feature filtering and selection. The CNN received raw signal as input for multiclass classification and with supervised training was able to extract underling features and patterns from the signal with better performance than handcrafted filters like FFT. Our results indicated that CNN is an useful tool for electroencephalography (EEG) analyses and classification of perceptually similar tastes.

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Human Taste-Perception: Brain Computer Interface (BCI) and Its Application as an Engineering Tool for Taste-Driven Sensory Studies

Cited by 25 publications

References 143 publications

Plasma processing: a sustainable technology in agri-food processing

Plasma processing: a sustainable technology in agri-food processing

Extended reality for mental health: Current trends and future challenges

The convolutional neural network as a tool to classify electroencephalography data resulting from the consumption of juice sweetened with caloric or non-caloric sweeteners

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