Olfactory-induced Positive Affect and Autonomic Response as a Function of Hedonic and Intensity Attributes of Fragrances

Seet, Manuel S.; Amin, Md. Rafiul; Abbasi, Nida Itrat; Hamano, Junji; Chaudhury, Anumita; Bezerianos, Anastasios; Faghih, Rose T.; Thakor, Nitish V.; Dragomir, Andrei

doi:10.1109/embc44109.2020.9176095

Cited by 9 publications

(2 citation statements)

References 18 publications

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“…As mentioned above, GSR is also used as the elective, standalone method to assess autonomic activity. GSR was seen to decrease with increasing pleasantness, regardless of intensity, in a protocol conducted over a set of four fragrances, two of which elicited positive effect and two negatively judged [133].…”

Section: Gsr and Chemical Sensory Stimuli Emotional Reactionsmentioning

confidence: 91%

E-Senses, Panel Tests and Wearable Sensors: A Teamwork for Food Quality Assessment and Prediction of Consumer’s Choices

et al. 2022

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At present, food quality is of utmost importance, not only to comply with commercial regulations, but also to meet the expectations of consumers; this aspect includes sensory features capable of triggering emotions through the citizen’s perception. To date, key parameters for food quality assessment have been sought through analytical methods alone or in combination with a panel test, but the evaluation of panelists’ reactions via psychophysiological markers is now becoming increasingly popular. As such, the present review investigates recent applications of traditional and novel methods to the specific field. These include electronic senses (e-nose, e-tongue, and e-eye), sensory analysis, and wearables for emotion recognition. Given the advantages and limitations highlighted throughout the review for each approach (both traditional and innovative ones), it was possible to conclude that a synergy between traditional and innovative approaches could be the best way to optimally manage the trade-off between the accuracy of the information and feasibility of the investigation. This evidence could help in better planning future investigations in the field of food sciences, providing more reliable, objective, and unbiased results, but it also has important implications in the field of neuromarketing related to edible compounds.

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Section: Gsr and Chemical Sensory Stimuli Emotional Reactionsmentioning

confidence: 91%

E-Senses, Panel Tests and Wearable Sensors: A Teamwork for Food Quality Assessment and Prediction of Consumer’s Choices

et al. 2022

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“…For further accurate estimate of emotional arousal, we intend to utilize the inferred ANS activity from SC recordings with our approach and combine with other physiological signals similar to [50][51][52][53][54][55][56]. The proposed new model as well as the scalable ANS inference approach have enabled us to design a scalable control architecture to regulate the arousal level similar to the proposed framework in [57][58][59][60]. Finally, since some studies have reported inconsistencies in the poral valve model by Edlberg et al [33] while investigating both SC and skin potential response [61], we plan to continue our investigation of the mechanism of sweat secretion to achieve improvements in the model and its understanding.…”

Section: Plos Computational Biologymentioning

confidence: 99%

Physiological characterization of electrodermal activity enables scalable near real-time autonomic nervous system activation inference

Amin

Faghih

2022

PLoS Comput Biol

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Electrodermal activities (EDA) are any electrical phxenomena observed on the skin. Skin conductance (SC), a measure of EDA, shows fluctuations due to autonomic nervous system (ANS) activation induced sweat secretion. Since it can capture psychophysiological information, there is a significant rise in the research work for tracking mental and physiological health with EDA. However, the current state-of-the-art lacks a physiologically motivated approach for real-time inference of ANS activation from EDA. Therefore, firstly, we propose a comprehensive model for the SC dynamics. The proposed model is a 3D state-space representation of the direct secretion of sweat via pore opening and diffusion followed by corresponding evaporation and reabsorption. As the input to the model, we consider a sparse signal representing the ANS activation that causes the sweat glands to produce sweat. Secondly, we derive a scalable fixed-interval smoother-based sparse recovery approach utilizing the proposed comprehensive model to infer the ANS activation enabling edge computation. We incorporate a generalized-cross-validation to tune the sparsity level. Finally, we propose an Expectation-Maximization based deconvolution approach for learning the model parameters during the ANS activation inference. For evaluation, we utilize a dataset with 26 participants, and the results show that our comprehensive state-space model can successfully describe the SC variations with high scalability, showing the feasibility of real-time applications. Results validate that our physiology-motivated state-space model can comprehensively explain the EDA and outperforms all previous approaches. Our findings introduce a whole new perspective and have a broader impact on the standard practices of EDA analysis.

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State-Space Model with One Binary, Two Continuous, and a Spiking-Type Observation

Wickramasuriya,

Faghih

2023

Bayesian Filter Design for Computational Medicine

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Spiking-type observations are occasionally recorded in experiments. For instance, neural spiking activity may be recorded from a macaque monkey engaged in a learning experiment or an EKG signal may be recorded from a human subject in an experiment. In such instances, we can model the spiking-type variable using a conditional intensity function (CIF). The CIF is similar to the rate parameter in a Poisson distribution but is more general. With spiking-type observations, we usually assume that our state variable $$x_{k}$$ x k affects the rate of spiking through the CIF.

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Olfactory-induced Positive Affect and Autonomic Response as a Function of Hedonic and Intensity Attributes of Fragrances

Cited by 9 publications

References 18 publications

E-Senses, Panel Tests and Wearable Sensors: A Teamwork for Food Quality Assessment and Prediction of Consumer’s Choices

E-Senses, Panel Tests and Wearable Sensors: A Teamwork for Food Quality Assessment and Prediction of Consumer’s Choices

Physiological characterization of electrodermal activity enables scalable near real-time autonomic nervous system activation inference

State-Space Model with One Binary, Two Continuous, and a Spiking-Type Observation

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