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About this paper
Azmyin Md. Kamal, Mushfiqul Azad, Sumayia Jerin Chowdhury
This paper introduces a prototype smart home system that autonomously adjusts its environment by detecting a user's emotional arousal levels from real-time physiological signals. The system classifies arousal on an embedded wearable device using heart rate and galvanic skin response, then transmits this data to a hub that controls environmental parameters like lighting and sound.
Key insights
- It is feasible to perform real-time emotional arousal classification directly on embedded wearable devices using basic physiological signals (HR, GSR) without relying on cloud processing.
- A finite state machine model can ensure deterministic and robust smart home responses to emotion classifications, even in the presence of communication disruptions.
- Directly integrating physiological sensing and on-device emotion classification into smart home systems can create adaptive environments, bridging traditional automation with affective computing.
Summary by alphaXiv.
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