“Zeitgeist – A deep learning visualization of Social Flow” by Gingrich, Rahman and
Conference:
Type(s):
Title:
- Zeitgeist - A deep learning visualization of Social Flow
Session/Category Title: Art & Design
Presenter(s)/Author(s):
Abstract:
Zeitgeist – the participatory artwork uses deep-learning algorithms to indicate creative ?Flow? mental states visualised on a holographic Pepper?s ghost display. Based on real-time analysis of physiological brainwave data through deep-learning algorithms, participants visually experience the probability of being in Flow – a mental state of creative peak performance.
References:
[1]
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[2]
Shama Sarwat Rahman, Kim Christensen, Henrik Jeldtoft Jensen, Peter Vuust, Joydeep Bhattacharya. 2021. The Neural Signature and Objective Indicator of Musical Creativity in Jazz Improvisation and Classical Interpretation. BioRxiv
[3]
H. S. Adnan, S. Real, and S. Rahman. 2020. Measuring Creative Flow in Real-Time with Consumer-Grade EEG and Deep Learning Networks, Marconi Institute of Creativity conference.
[4]
O. Gingrich, U. Tymoszuk, E. Emets, A. Renaud, and D. Negrao. 2019. KIMA: Voice – Participatory Arts as means for Social Connection. EVA Proceedings.
[5]
S. Cohen. 2004. Social relationships and health. American psychologist, 59(8), 676
[6]
S. Stansfeld, and B. Candy. 2006. Psychosocial work environment and mental health?a meta-analytic review. Scandinavian journal of work, environment & health, 443-462.
[7]
E. Diener. 2000. Subjective well-being: The science of happiness and a proposal for a national index. American psychologist, 55(1), 34.
[8]
Arthur Aron, Elaine Aron, and Danny Smollan. 1992. Inclusion of Other in the Self Scale and the structure of interpersonal closeness. Journal of Personality and Social Psychology, 63(4), p. 596?612.
