Respostas emocionais na interação física entre usuários e produtos
EEG como alternativa metodológica - estudo de caso
DOI:
https://doi.org/10.29147/datjournal.v11i2.1036Palavras-chave:
Design de Produto, Resposta Emocional, Eletroencefalografia, ValenciaResumo
Métodos de Design dependem de instrumentos que avaliam as respostas emocionais como componentes da usabilidade das interfaces. Entre os instrumentos fisiológicos destaca-se a eletroencefalografia (EEG), a qual baseia-se em tecnologias computacionais e na neurociência. Entretanto a aplicação do EEG nos processos de interação física entre usuários e produtos é incipiente. O presente estudo de caso objetivou avaliar as respostas emocionais na interação física entre usuários e produtos, visando verificar se o design dos produtos influenciam os valores (Alpha µV²) e as valências emocionais. De caráter experimental, aplicado e com amostra de conveniência (n=2), o EEG foi empregado durante a interação física com quatro produtos de uso cotidiano; e os dados analisados a partir de princípios da “assimetria cortical”. Os resultados apontam que não houve diferença significativa (p>0,05) entre Left Alpha µV² e Right Alpha µV², para nenhum dos produtos, apesar de diferenças maiores que 10%, tanto na análise geral para cada produto, como para cada uma das etapas de interação, impactando na valência alcançada. O EEG demonstrou-se viável na avaliação da valência, em atividades reais.
Downloads
Referências
ACHARYA, Jayant; HANI, Abeer; CHEEK, Janna; THIRUMALA, Parthasaraty; TSUCHIDAK, Tammy. American Clinical Neurophysiology Society Guideline 2: Guidelines for Standard Electrode Position Nomenclature. Journal of Clinical Neurophysiology, v.33, n. 04, p. 308-311, 2016. DOI: https://doi.org/10.1080/21646821.2016.1245558.
AGUIAR, Débora; NASCIMENTO FILHO, Paulo; MOREIRA, Amanda; ALVES, Gabriella; HOTTA, Gisele; SANTOS-JÚNIOR, Francisco. People with amputation and musculoskeletal pain show reduced electrical activity of Alpha brain waves: cross-sectional study. Brazilian Journal of Pain, v. 05, n. 03, p. 226-232, 2022. DOI: http://dx.doi.org/10.5935/2595-0118.20220040-en.
ALBUQUERQUE, Thayse; NASCIMENTO FILHO, Paulo; MESQUITA, Yara; OLIVEIRA, Liana; HOTTA, Gisele; OLIVEIRA, Francisco; SANTOS-JÚNIOR, Francisco. Modulation of Brain Waves in Spinal Cord Injury Patients With Pain: Cross-Sectional Analysis. Coluna/Columna, v. 22, n. 04, 2023. DOI: https://doi.org/10.1590/s1808-185120222204276734
ALVES, Nelson; AZNAR-CASANOVA, Jose; FUKUSIMA, Sergio. Patterns of brain asymmetry in the perception of positive and negative facial expressions. Laterality, v. 14, n. 03, p. 256–272, 2009. DOI: https://doi.org/10.1080/13576500802362927
ALVES, Nelson; FUKUSIMA, Sergio; AZNAR-CASANOVA, Jose. Models of brain asymmetry in emotional processing. Psychology & Neuroscience, v 01, n. 01, p. 63–66, 2008. DOI: https://doi.org/10.3922/j.psns.2008.1.010
BARROS, Catarina; PEREIRA, Ana; SAMPAIO, Adriana; BUJÁN, Ana; PINAL, Diego. Frontal Alpha Asymmetry and Negative Mood: A Cross-Sectional Study in Older and Younger Adults. Symmetry, v. 18, n. 8; a. 1579, 2022. DOI: https://doi.org/10.3390/sym14081579
BERKMAN, Elliot; LIEBERMAN, Matthew. Approaching the bad and avoiding the good: Lateral prefrontal cortical asymmetry distinguishes between action and valence. Journal of Cognitive Neuroscience, v. 22, n. 9, p. 1970-1979, 2010. DOI: https://doi.org/10.1162/jocn.2009.21317
BIASIUCCIL, Andrea; FRANCESCHIELLO, Benedetta; MURRAY, Micah. Electroencephalography. Current Biology, v. 29, n. 03, a. p.R80-R85, 2019. DOI: https://doi.org/10.1016/j.cub.2018.11.052
CHOI, Ga-Young; SHIN, Jong-Gyu; LEE, Ji-Yoon; LEE, Jun-Seok; HEO, In-Seok, YOON, Ha-Ye-ong; LIM, Wansu; JEONG, Jin-Woo; KIM, Sang-Ho; HWANG, Han-Jeong. EEG Dataset for the Recognition of Different Emotions Induced in Voice-User Interaction. Scientific Data,v. 11, a. 1084, 2024. DOI: https://doi.org/10.1038/s41597-024-03887-9
DAMÁSIO, António. A estranha ordem das coisas: as origens biológicas dos sentimentos e da cultura. São Paulo: Companhia das Letras, 2018. 344p.
DAMÁSIO, António. O erro de Descartes: emoção, razão e o cérebro humano. São Paulo: Companhia das Letras, 2012. 264p.
DAMÁSIO, António. Sentir e saber: as origens da consciência. São Paulo: Companhia das Letras, 2022. 200p.
DARWIN, Charles. The Expression of the Emotions in Man and Animals. Cambridge, Cambridge University Press, 2009, 424p.
DAVIDSON, Richard. Affective Neuroscience: A Case for Interdisciplinary Research. In Frank Kessel, Patricia Rosenfield, and Norman Anderson (eds), Interdisciplinary Research: Case Studies from Health and Social Science. New York, Oxford Academic, 2008. DOI: https://doi.org/10.1093/acprof:oso/9780195324273.003.0009
DAVIDSON, Richard. Neuropsychological perspectives on affective styles and their cognitive consequences. In: T. Dalgleish & M. J. Power (Eds.), Handbook of cognition and emotion (pp. 103–123). John Wiley & Sons Ltd. 1999. DOI: https://doi.org/10.1002/0470013494.ch6
ERAT, K.; ŞAHIN, Elif; DOGAN, Furkan; MERDANOGLU, Nur; AKCAKAYA, Ahmet; DURDU,
Pınar. Emotion recognition with EEG-based brain-computer interfaces: a systematic
literature review. Multimedia Tools and Applications, v. 83, p. 79647–79694, 2024. DOI:
https://doi.org/10.1007/s11042-024-18259-z
FREY, Jérémy; MÜHL, Christian; LOTTE, Fabien; HACHET, Martin. Review of the Use of Elec-
troencephalography as an Evaluation Method for Human-Computer Interaction. Pro-
ceedings of the International Conference on Physiological Computing Systems PhyCS, v. 01,
p. 214-223, 2014. DOI: https://doi.org/10.5220/0004708102140223
GADA, Tina; CHUDASAMA, Shreya. The role of user experience in effective product de-
sign exercise: strategies for incorporating user centric approaches and data analysis
with business intelligence. International Research Journal of Modernization in Enginee-
ring Technology and Science, v. 06, n. 05, p. 6856-6860, 2024. DOI: https://doi.org/10.56726/
IRJMETS56245
GKINTONI, Evgenia; AROUTZIDIS, Anthimos; ANTONOPOULO, Hera; HALKIOPOULOS, Cons-
tantinos. From Neural Networks to Emotional Networks: A Systematic Review of EEG-
Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications.
Brain Sciences, v. 15, n. 03, 220, 2024. DOI: https://doi.org/10.3390/brainsci15030220
GUO, Fu; DING, Yi; WANG, Tianbo; LIU, Weilin; JIN, Haizhe. Applying event related po-
tentials to evaluate user preferences toward smartphone form design. InternationalJournal of Industrial Ergonomics, v. 54, p. 57-64, 2016. DOI: https://doi.org/10.1016/j.er-
gon.2016.04.006
GUO, Fu; LI, Mingming; HU, Mingcai; LI, Fengxiang; LIN, Bozhao. Distinguishing and quan-
tifying the visual aesthetics of a product: an integrated approach of eye-tracking and
EEG. International Journal of Industrial Ergonomics, v. 71, p. 47-56, 2019. DOI: https://doi.
org/10.1016/j.ergon.2019.02.006
HARMON-JONES, Eddie. Clarifying the emotive functions of asymmetrical frontal cortical
activity. Psychophysiology, v. 40, n. 6, p. 838-848, 2003. DOI: https://doi.org/10.1111/1469-
8986.00121
HARMON-JONES, Eddie; GABLE, Philip; PETERSON, Carly. The role of asymmetric frontal
cortical activity in emotion-related phenomena: A review and update. Biological Psy-
chology, v. 84, n. 3, p. 451-462, 2010. DOI: https://doi.org/10.1016/j.biopsycho.2009.08.010
HESKETT, John. Toothpicks and Logos: Design in Everyday Life. Oxford, Oxford Univer-
sity Press, 2002. 224p.
HOUSSEIN, Essam, HAMMAD, Asmaa; ALI, Abdelmgeid. Human emotion recognition
from EEG-based brain–computer interface using machine learning: a comprehensi-
ve review. Neural Computing and Applications, v. 34, p. 12527–12557, 2022. https://doi.
org/10.100
7/s00521-022-07292-4
JONES, Nancy; FOX, Nathan. Electroencephalogram asymmetry during emotionally evocative films and its relation to positive and negative affectivity. Brain and Cognition, v. 20, n. 02, p. 280–299, 1992. DOI: https://doi.org/10.1016/0278-2626(92)90021-D
KIM, Nayeon, CHUNG, Seohyeon; KIM, Da. Exploring EEG-based Design Studies: A Systematic Review. Archives of Design Research, v. 35, n. 04, p. 91-113, 2022. DOI: http://dx.doi.org/10.15187/adr.2022.11.35.4.91
LANUTTI, Jamille; PASCHOARELLI, Luis. Avaliação de produto de uso cotidiano por meio de critérios de usabilidade: espremedores de fruta. Human Factors in Design, .v. 4, n. 7, p. 003–015, 2015. URL: https://www.revistas.udesc.br/index.php/hfd/article/view/6062
LEES, Ty; RAM, Nilam; SWINGLER, Margaret; GATZKE-KOPP, Lisa. The effect of hair type and texture on electroencephalography and event-related potential data quality. Psychophysiology, v. 61, a. e14499. 2024. DOI: https://doi.org/10.1111/psyp.14499
LEES-MAFFEI, Grace. Juicy Salif Lemon Squeezer, Italy/France (Philippe Starck, 1990). In: Iconic Designs: 50 stories about 50 things. London: Bloomsbury Design Library, p. 184-187, 2014. DOI: https://doi.org/10.5040/9781474293921.ch-039
LI, Xiang; ZHANG, Yazhou; TIWARI, Prayag; SONG, Dawei; HU, Bin; YANG, Meihong; ZHAO, Zhigang; KUMAR, Neeraj; MARTTINEN, Pekka. EEG Based Emotion Recognition: A Tutorial and Review. ACM Computing Surveys, v. 55, n. 4, p. 1–57, 2022. DOI: https://doi.org/10.1145/3524499
LUCCAS, Francisco; BRAGA, Nadia; SILVADO, Carlos. Recomendações técnicas para o registro do eletrencefalograma (EEG) na suspeita da morte encefálica. Arquivos de Neuro-psiquiatria, v. 56, n. 3B, 1998. DOI: https://doi.org/10.1590/S0004-282X1998000400030
MISHRA, Prabhaker; PANDEY, Chandra; SINGH, Uttam; GUPTA, Anshul; SAHU, Chinmoy; KE-SHRI, Amit. Descriptive Statistics and Normality Tests for Statistical Data. Annals of Cardiac Anaesthesia, v. 22, n. 1, p. 67–72, 2019. DOI: https://doi.org/10.4103/aca.ACA_157_18
MOON, Seong-Eun; KIM,Jun-Hyuk; KIM, Sun-Wook; LEE, Jong-Seok. Prediction of car design perception using EEG and gaze patterns. IEEE Transactions on Affective Computing, v. 12, n. 04, p. 84–856, 2019. DOI: https://doi.org/10.1109/TAFFC.2019.2901733
NASCIMENTO, Lisandra Batista do. Avaliação afetiva de produtos de cutelaria: o estudo de caso da marca Herdmar - PT [Dissertação de Mestrado em Design]. Recife, Universidade Federal de Pernambuco, 2024. URI: https://repositorio.ufpe.br/handle/123456789/64946
PALINKAS, Lawrence; HORWITZ, Sara; GREEN, Carla; WISDOM, Jennifer; DUAN, Naihua; HO-AGWOOD, Kimberly. Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research. Administration and Policy in Mental Health and Mental Health Services Research, v. 42, n. 05, p. 533–544 , 2015. DOI: https://doi.org/10.1007/s10488-013-0528-y
RUSSO, Bernard; Moraes, Anamaria. (2003). The Usability of Iconic Designs a Case Study of Juicy Salif. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, v. 47, n. 5, p. 844-847, 2003. DOI: https://doi.org/10.1177/154193120304700512
SCHERER, Klaus; EKMAN, Paul. Approaches to Emotion. Abingdon, Psychology Press, 1984. 440p.
SOROUSH, Morteza; ZENG, Yong. EEG-based study of design creativity: a review on research design, experiments, and analysis. Frontiers in Behavioral Neuroscience, v. 18, a. 1331396, 2024. DOI: https://doi.org/10.3389/fnbeh.2024.1331396
SUGIONO, Sugiono; PUTRA, Andi; PRASETYA, Renaldi; FANANI, Angga; CAHYAWATI, Amanda; OKTAVIANTY, Oke. A new concept of product design by involving emotional factors using EEG: a case study of computer mouse design. Acta Neuropsychologica, v. 19, n. 01, P. 63–80, 2021. DOI: https://doi.org/10.5604/01.3001.0014.7021
WAGER, Tor; PHAN, Kinh; LIBERZON, Israel; TAYLOR, Stephan. Valence, gender, and lateralization of functional brain anatomy in emotion: a meta-analysis of findings from neuroimaging. Neuroimage, v. 19, n. 3, p. 513–531, 2003. DOI: https://doi.org/10.1016/s1053-8119(03)00078-8
YILMAZ, Bülent; KORKMAZ, Sümeyye; ARSLAM, Dilek; GÜNGÖR, Evrim; ASYALI Musa. Like/dislike analysis using EEG: determination of most discriminative channels and frequencies. Computer Methods and Programs in Biomedicine, v. 113, n. 2; p. 705–713, 2014. DOI: https://doi.org/10.1016/j.cmpb.2013.11.010
YU, Chaofei; WANG, Mei. Survey of emotion recognition methods using EEG information. Cognitive Robotics, v. 02, p. 132-146, 2022. DOI: https://doi.org/10.1016/j.cogr.2022.06.001
ZHANG, Zhihui; FORT, Josep; GIMÉNEZ MATEU, Lluis. Mini review: Challenges in EEG emotion recognition. Frontiers in Psychology, v. 14, 2024. DOI: https://doi.org/10.3389/fpsyg.2023.1289816
ZHU, Siyu; QI, Jin; HU, Jie; HAO, Sheng. A new approach for product evaluation based on integration of EEG and eye-tracking. Advanced Engineering Informatics, v. 52, a. 101601, 2022. DOI: https://doi.org/10.1016/j.aei.2022.101601
![Capa da publicação científica DAT Journal (Design, Art and Technology Journal). No topo, destaca-se a tipografia em caixa alta e verde-limão com o nome da revista, intercalada pelo logotipo estilizado "dat]" em minúsculas. Abaixo do título, encontra-se a identificação da edição: "v.11 n.2 2026". A composição visual apresenta um fundo gráfico abstrato com formas geométricas e texturas digitais contrastantes.](https://datjournal.anhembi.br/public/journals/1/cover_issue_36_pt_BR.jpg)
Downloads
Publicado
Como Citar
Edição
Seção
Licença
Copyright (c) 2026 DAT Journal
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.
