Emotion recognition based on weighted kernel support vector machine using wearable inertial sensors Article Swipe
Yan Zhao
,
Ming Guo
,
Xiangyong Chen
,
Feng Zhao
,
Jianlong Qiu
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-1629621/v1
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-1629621/v1
Emotion recognition has various applications closely linked with people's daily life, such as human-computer interaction and psychotherapy. So this paper focuses on the research of emotion recognition of body movement and proposes a novel emotion recognition approach based on weighted kernel support vector machine (SVM) using wearable inertial sensors. Specifically, the mapping relationship from emotions to body movements is established by fuzzy comprehensive evaluation. The subjects wear inertial sensors on their arms and wrists to collect data in six emotions including sleepy, bored, excited, tense, anger and distressed. In recognition phase, the weighted kernel SVM model is constructed, in which the fuzzy function is auxiliary to improve the weight calculation method of kernel functions in multiple kernel SVM. It also explores the effect of different combinations of inertial sensors on the recognition. The results show that compared with other methods, the proposed method achieves 98.4% accuracy for six emotions, which is effective and applicable.
Related Topics
Concepts
Support vector machine
Artificial intelligence
Kernel (algebra)
Computer science
Inertial measurement unit
Pattern recognition (psychology)
Wearable computer
Inertial frame of reference
Radial basis function kernel
Anger
Fuzzy logic
Kernel method
Mathematics
Psychology
Psychiatry
Quantum mechanics
Combinatorics
Physics
Embedded system
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-1629621/v1
- https://www.researchsquare.com/article/rs-1629621/latest.pdf
- OA Status
- green
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4281642476
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4281642476Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.21203/rs.3.rs-1629621/v1Digital Object Identifier
- Title
-
Emotion recognition based on weighted kernel support vector machine using wearable inertial sensorsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-05-31Full publication date if available
- Authors
-
Yan Zhao, Ming Guo, Xiangyong Chen, Feng Zhao, Jianlong QiuList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-1629621/v1Publisher landing page
- PDF URL
-
https://www.researchsquare.com/article/rs-1629621/latest.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.researchsquare.com/article/rs-1629621/latest.pdfDirect OA link when available
- Concepts
-
Support vector machine, Artificial intelligence, Kernel (algebra), Computer science, Inertial measurement unit, Pattern recognition (psychology), Wearable computer, Inertial frame of reference, Radial basis function kernel, Anger, Fuzzy logic, Kernel method, Mathematics, Psychology, Psychiatry, Quantum mechanics, Combinatorics, Physics, Embedded systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
35Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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