Enhancing Well-Being and Alleviating Stress via Wearable-Driven Emotion Recognition and EQ Intentional Practice With Deep Reinforcement Learning

This research design delves into a groundbreaking study that highlights the innovative use of wearables and deep reinforcement learning to enhance emotional well-being and manage stress. With a focus on leveraging wearable sensor technology, specifically the Empatica EmbracePlus device, the research unfolds at the intersection of emotional intelligence (EQ) augmentation, emotion recognition, and intentional EQ practice. Leveraging the potential of wearables, participants were selected from the Master of Engineering Technical Management program at Texas A&M University based on their involvement in studies related to EQ and management. The objective is to investigate personalized strategies for improving emotional well-being through three interconnected aims: first, exploring the relationship between EQ, stress management, and physiological indicators using wearable technology; second, evaluating the effectiveness of intentional EQ practices in improving emotional well-being and reducing stress; and third, utilizing machine learning to optimize the impact of intentional practices on overall well-being. This approach underscores the potential of wearables to illuminate the physiological responses accompanying mindfulness practices, offering fresh insights into the dynamic relationship between EQ, stress management, and intentional well-being enhancement.