Emotion assessment using Machine Learning and low-cost wearable devices
Abstract
The advancement in bioelectrical measurement technologies and the push towards a higher impact of the Brain Computer Interfaces and Affective Computing in the daily life have made non-invasive and low-priced devices available to the large population to record physiological states. The aim of this study is the assessment of the abilities of the MUSE headband, together with the Shimmer GSR+ device, to assess the emotional state of people during stimuli exposure. Twenty-four pictures from the IAPS database were showed to 54 subjects and were evaluated in their emotional values by means of the Self-Assessment Manikin (SAM). Using a Machine Learning approach, fifty-two scalar features were extracted from the signals and used to train 6 binary classifiers to predict the valence and arousal elicited by each stimulus. In all classifiers we obtained accuracies ranging from 53.6% to 69.9%, confirming that these devices are able to give information about the emotional state.
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Authors in [104] and [105] introduce TinyML as a medical embedded system for diagnosis of focal liver lesion (FLL) using a DNN model trained on liver images obtained using ultrasound imaging.
“The authors in [104] and [105] introduce TinyML as a medical embedded system for the diagnosis of of focal liver lesion (FLL) using a DNN model trained on liver images that were priory obtained using ultrasound imaging.”
From A Comprehensive Survey on TinyML (2023) · cites this paper as [105]
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- Authors
- Laureanti, R., Bilucaglia, M., Zito, M., Circi, R., Fici, A., Rivetti, F., Valesi, R., Oldrini, C., Mainardi, L. T., & Russo, V.
- Affiliations
- Politecnico di Milano (IT)
- IULM University (IT)
- Venue
- 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
- Publisher
- IEEE
- Published
- 2020-07
- Volume
- 2020
- Pages
- 576-579
- ISSN
- 2375-7477 (ISSN-L)
- OpenAlex
- W3082775944
- Cited by
- 33
- References
- 24
- Citations by year
- 2025: 2 · 2024: 6 · 2023: 8 · 2022: 9 · 2021: 8
- FWCI
- 6.08
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (publishedVersion)
- PubMed (publishedVersion)
- Aisberg (University of Bergamo) (submittedVersion)
- Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (submittedVersion)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Emotion and Mood Recognition
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Keywords
- emotion measurement, Muse headband, skin conductance, electrodermal activity, valence and arousal prediction, IAPS images, Self-Rating Manikin, low-cost wearable device, affective computing
- MeSH terms
- Machine Learning, Wearable Electronic Devices, Arousal, Emotions, Humans, Brain-Computer Interfaces
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