Literature DB >> 33050320

Design of an Interactive Mind Calligraphy System by Affective Computing and Visualization Techniques for Real-Time Reflections of the Writer's Emotions.

Chao-Ming Wang1, Yu-Chen Chen1.   

Abstract

A novel interactive system for calligraphy called mind calligraphy that reflects the writer's emotions in real time by affective computing and visualization techniques is proposed. Differently from traditional calligraphy, which emphasizes artistic expression, the system is designed to visualize the writer's mental-state changes during writing using audio-visual tools. The writer's mental state is measured with a brain wave machine to yield attention and meditation signals, which are classified next into the four types of emotion, namely, focusing, relaxation, calmness, and anxiety. These emotion types then are represented both by animations and color palettes for by-standing observers to appreciate. Based on conclusions drawn from data collected from on-site observations, surveys via Likert-scale questionnaires, and semi-structured interviews, the proposed system was improved gradually. The participating writers' cognitive, emotional, and behavioral engagements in the system were recorded and analyzed to obtain the following findings: (1) the interactions with the system raise the writer's interest in calligraphy; (2) the proposed system reveals the writer's emotions during the writing process in real time via animations of mixtures of fish swimming and sounds of raindrops, insects, and thunder; (3) the dynamic visualization of the writer's emotion through animations and color-palette displays makes the writer understand better the connection of calligraphy and personal emotions; (4) the real-time audio-visual feedback increases the writer's willingness to continue in calligraphy; and (5) the engagement of the writer in the system with interactions of diversified forms provides the writer with a new experience of calligraphy.

Entities:  

Keywords:  affective computing; brain wave; calligraphy; emotion; human–computer interaction; mental state; visualization

Mesh:

Year:  2020        PMID: 33050320      PMCID: PMC7601501          DOI: 10.3390/s20205741

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  8 in total

1.  Brain-computer interface technology: a review of the first international meeting.

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Authors:  L I Aftanas; S A Golocheikine
Journal:  Neurosci Lett       Date:  2001-09-07       Impact factor: 3.046

3.  Power Analysis in Covariance Structure Modeling Using GFI and AGFI.

Authors:  R C MacCallum; S Hong
Journal:  Multivariate Behav Res       Date:  1997-04-01       Impact factor: 5.923

4.  A Study Of A Measure Of Sampling Adequacy For Factor-Analytic Correlation Matrices.

Authors:  B A Cerny; H F Kaiser
Journal:  Multivariate Behav Res       Date:  1977-01-01       Impact factor: 5.923

5.  Development and evaluation of an observational method for assessing repetition in hand tasks.

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6.  Reliability and validity test of the Korean version of Noe's evaluation.

Authors:  Yedam Ho; Oh Young Kwon; So Youn Park; Tai Young Yoon; Young-Eun Kim
Journal:  Korean J Med Educ       Date:  2017-02-28

7.  Validation of Electroencephalographic Recordings Obtained with a Consumer-Grade, Single Dry Electrode, Low-Cost Device: A Comparative Study.

Authors:  Héctor Rieiro; Carolina Diaz-Piedra; José Miguel Morales; Andrés Catena; Samuel Romero; Joaquin Roca-Gonzalez; Luis J Fuentes; Leandro L Di Stasi
Journal:  Sensors (Basel)       Date:  2019-06-23       Impact factor: 3.576

Review 8.  A review on the computational methods for emotional state estimation from the human EEG.

Authors:  Min-Ki Kim; Miyoung Kim; Eunmi Oh; Sung-Phil Kim
Journal:  Comput Math Methods Med       Date:  2013-03-24       Impact factor: 2.238

  8 in total

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