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      Mood State Detection in Handwritten Tasks Using PCA–mFCBF and Automated Machine Learning

      , , , , ,
      Sensors
      MDPI AG

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          Abstract

          In this research, we analyse data obtained from sensors when a user handwrites or draws on a tablet to detect whether the user is in a specific mood state. First, we calculated the features based on the temporal, kinematic, statistical, spectral and cepstral domains for the tablet pressure, the horizontal and vertical pen displacements and the azimuth of the pen’s position. Next, we selected features using a principal component analysis (PCA) pipeline, followed by modified fast correlation–based filtering (mFCBF). PCA was used to calculate the orthogonal transformation of the features, and mFCBF was used to select the best PCA features. The EMOTHAW database was used for depression, anxiety and stress scale (DASS) assessment. The process involved the augmentation of the training data by first augmenting the mood states such that all the data were the same size. Then, 80% of the training data was randomly selected, and a small random Gaussian noise was added to the extracted features. Automated machine learning was employed to train and test more than ten plain and ensembled classifiers. For all three moods, we obtained 100% accuracy results when detecting two possible grades of mood severities using this architecture. The results obtained were superior to the results obtained by using state-of-the-art methods, which enabled us to define the three mood states and provide precise information to the clinical psychologist. The accuracy results obtained when detecting these three possible mood states using this architecture were 82.5%, 72.8% and 74.56% for depression, anxiety and stress, respectively.

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          Most cited references21

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          “Mini-mental state”

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            Social anxiety and self-presentation: A conceptualization model.

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              Psychological stress reactivity and future health and disease outcomes: A systematic review of prospective evidence

              Acute psychological stress activates the sympatho-adrenal medullary (SAM) system and hypothalamo-pituitary adrenal (HPA) axis. The relevance of this stress reactivity to long-term health and disease outcomes is of great importance. We examined prospective studies in apparently healthy adults to test the hypothesis that the magnitude of the response to acute psychological stress in healthy adults is related to future health and disease outcomes.
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                Author and article information

                Contributors
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                Journal
                SENSC9
                Sensors
                Sensors
                MDPI AG
                1424-8220
                February 2022
                February 21 2022
                : 22
                : 4
                : 1686
                Article
                10.3390/s22041686
                85634d8d-542f-4265-af81-c351d7cb9359
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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