Abstract
The present research proposes a method for the construction of a corpus for the early detection of Alzheimer’s, by identifying basic patterns of emotions on video, from the collection of patient information in the form of videos, analysis and identification of emotions based on facial expressions and finally validation by two statistical measures: weighted Kappa and Kappa. Applying the method on a corpus of 40 videos, an average score of 0.60 obtained in the Kappa index and 0.67 in the weighted Kappa index, which indicates a good agreement among the observers, and provides encouraging results for the use of the corpus in automatic learning, on the patterns of emotions that allow the detection of Alzheimer’s disease.
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Change history
28 March 2018
The original version of the book was inadvertently published with incorrect third author name as “Pablo Torres Carrión”, which has been corrected as “Pablo Torres-Carrión” in Chapter 15, Frontmatter and Backmatter, and the affiliation of first and second authors “Faculty of Engineering Sciences, Universidad Tecnolgica Equinoccial, Quito, Ecuador” has been updated as “Faculty of Engineering Sciences, Universidad Tecnológica Equinoccial, Quito, Ecuador” in Chapter 49. The erratum book has been updated with the changes.
Notes
- 1.
Video Pad, available online on http://www.nchsoftware.com/videopad/index.html.
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Gómez, P., González-Eras, A., Torres-Carrión, P. (2018). Method for Emotion Corpus Validation from the Consensual Identification of Patterns in Alzheimer’s Patients. In: Rocha, Á., Guarda, T. (eds) Proceedings of the International Conference on Information Technology & Systems (ICITS 2018). ICITS 2018. Advances in Intelligent Systems and Computing, vol 721. Springer, Cham. https://doi.org/10.1007/978-3-319-73450-7_15
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