2017
DOI: 10.1080/21681015.2017.1324528
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Using fuzzy c-means clustering based on integration of psychological and physiological data for therapeutic music design

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Cited by 5 publications
(4 citation statements)
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“…Fuzzy clustering was applied by the authors to classify musical characteristics (tempo, volume, amplitude) for music treatment. However, such a method differs from the one used in the current study where fuzzy clustering was applied to classify the users with similar psychological states [34]. Consequently, users with a high fuzzy membership degree for Groups 1 and 3 were recommended with choices of music falling under "high" depression and anxiety.…”
Section: Discussionmentioning
confidence: 95%
See 1 more Smart Citation
“…Fuzzy clustering was applied by the authors to classify musical characteristics (tempo, volume, amplitude) for music treatment. However, such a method differs from the one used in the current study where fuzzy clustering was applied to classify the users with similar psychological states [34]. Consequently, users with a high fuzzy membership degree for Groups 1 and 3 were recommended with choices of music falling under "high" depression and anxiety.…”
Section: Discussionmentioning
confidence: 95%
“…Likewise, M.C. Chiu et al (2017) also categorized music to alleviate negative psychological conditions. Fuzzy clustering was applied by the authors to classify musical characteristics (tempo, volume, amplitude) for music treatment.…”
Section: Discussionmentioning
confidence: 99%
“…The fuzzy c-means clustering (FCM) algorithm is one of the most used soft clustering methods [49]. Fuzzy c-means clustering has been successfully used in previous psychological clustering research to examine and find the music features that can calm individuals and which form the most relaxing music for therapeutic use [50], to analyze missing data [51], to analyze employee branding typology [52] and to investigate language processing [53].…”
Section: Fuzzy C-means Clustering Resultsmentioning
confidence: 99%
“…Most teachers tend to demonstrate moderate or even low levels of interaction (Zhang et al, 2017). Insufficient peer interaction has become a major challenge in online teacher training (Chiu et al, 2018). Previous studies have revealed that collaborative learning has positive effects of boosting communications and interactions (De Jong et al, 2022), enhancing learners' knowledge construction (Ye & Pennisi, 2022).…”
Section: Introductionmentioning
confidence: 99%