@article {2023,
	title = {AffectMachine-Classical: a novel system for generating affective classical music},
	journal = {Frontiers in Psychology 14:1158172. doi: 10.3389/fpsyg.2023.1158172},
	volume = {14:1158172},
	year = {2023},
	month = {06/2023},
	pages = {1-13},
	type = {Journal article},
	abstract = {This work introduces a new music generation system, called AffectMachine-Classical, that is capable of generating affective Classic music in real-time. AffectMachine was designed to be incorporated into biofeedback systems (such as brain-computer-interfaces) to help users become aware of, and ultimately mediate, their own dynamic affective states. That is, this system was developed for music-based MedTech to support real-time emotion self-regulation in users. We provide an overview of the rule-based, probabilistic system architecture, describing the main aspects of the system and how they are novel. We then present the results of a listener study that was conducted to validate the ability of the system to reliably convey target emotions to listeners. The findings indicate that AffectMachine-Classical is very effective in communicating various levels of Arousal (R2 = 0.96) to listeners, and is also quite convincing in terms of Valence (R2 = 0.90). Future work will embed AffectMachine-Classical into biofeedback systems, to leverage the efficacy of the affective music for emotional wellbeing in listeners.},
	keywords = {affective computing, algorithmic composition, automatic music generation system, emotion regulation, listener validation study, Music MedTech},
	doi = {doi.org/10.3389/fpsyg.2023.1158172},
	url = {https://www.frontiersin.org/articles/10.3389/fpsyg.2023.1158172/full},
	author = {Kat R. Agres and Adyasha Dash and Phoebe Chua}
}
@conference {2023,
	title = {Know Thyself: Improving interoceptive ability through ambient biofeedback in the workplace},
	booktitle = {SIGHCI 2023 Proceedings},
	year = {2023},
	month = {12/2023},
	publisher = {Association for Information Systems},
	organization = {Association for Information Systems},
	address = {Hyderabad, India},
	abstract = {Interoception, the perception of the body{\textquoteright}s internal state, is intimately connected to self-regulation and wellbeing. Grounded in the affective science literature, we design an ambient biofeedback system called Soni-Phy and a lab study to investigate whether, when and how an unobtrusive biofeedback system can be used to improve interoceptive sensibility and accuracy by amplifying a users{\textquoteright} internal state. This research has practical significance for the design and improvement of assistive technologies for the workplace. },
	keywords = {assistive augmentation, biofeedback, Interoception},
	url = {https://aisel.aisnet.org/sighci2023/3},
	author = {Phoebe Chua and Kat Agres and Suranga Nanayakkara}
}
@conference {2022,
	title = {Computational Music Systems for Emotional Health and Wellbeing: A Review},
	booktitle = {ACM Special Interest Group on Computer{\textendash}Human Interaction (SIGHCI) 2022},
	year = {2022},
	month = {12/2022},
	abstract = {Music is a powerful stimulus, and both active and receptive methods of engaging with music provide affordances for improving physical, mental and social health. The emergence of sophisticated computational methods also underscores the potential for novel music technologies to address a wider range of wellbeing outcomes. In this review, we focus on describing the current state of the literature on computational approaches to music generation for health and wellbeing and identifying possible future directions for research in this area.},
	author = {Phoebe Chua and Chitralekha Gupta and Kat R. Agres and Suranga Nanayakkara}
}
