Haneen Reda Banjar, Lujain Alsefri, Aseel Alshomrani, Morouj Hamdhy, Sara Alahmari, Sanaa Sharaf
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Utilizing principles of EI, the app customizes the mobile interface color settings, suggesting activities and providing advice suited to the user’s emotional state confirmed by the chatbot. The emotion recognition model is trained and tested using the SEED-IV dataset, ensuring compatibility with consumer EEG headbands and accurate detection of complex emotions like sadness and fear. Thorough static and dynamic testing has validated the app’s design and operational efficacy, confirming its preparedness for practical use. By combining real-time EEG data analysis with intelligent chatbot interactions, “Motus Up” stands out as an innovative mental health tool that enhances EI and offers a responsive experience for emotional self-regulation. 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引用次数: 0
摘要
心理健康取决于情商(EI),即识别、理解和管理情绪的能力。由于情绪(积极和消极情绪)会影响我们的行动、决策和健康,因此在当今快节奏的社会中,情商变得更加重要。特别是负面情绪,由于其复杂性和有效管理的难度,给我们带来了挑战。Motus Up "移动应用程序将基于脑电图的情绪识别与基于规则的聊天机器人相结合,帮助用户管理负面情绪,是个人心理健康管理领域的一次重大飞跃。该应用程序利用情绪识别原理,根据聊天机器人确认的用户情绪状态,定制手机界面颜色设置、建议活动和提供建议。情绪识别模型通过 SEED-IV 数据集进行训练和测试,确保与消费者脑电图头带兼容,并能准确检测出悲伤和恐惧等复杂情绪。全面的静态和动态测试验证了该应用程序的设计和运行效果,确认其已准备好投入实际使用。通过将实时脑电图数据分析与智能聊天机器人互动相结合,"Motus Up "作为一款创新的心理健康工具脱颖而出,增强了 EI,为情绪自我调节提供了响应式体验。这种在移动平台上将技术与心理学相结合的做法有望改善个人的心理健康和情感指数。
Activating the Mobile User Interface With a Rule-Based Chatbot and EEG-Based Emotion Recognition to Aid in Coping With Negative Emotions
Mental health depends on emotional intelligence (EI), the ability to recognize, understand, and manage emotions. As emotions—positive and negative—influence our actions, decisions, and health, EI has become more important in today’s fast-paced society. Negative emotions, in particular, pose a challenge due to their complexity and the difficulty in managing them effectively. The “Motus Up” mobile app represents a significant leap in personal mental health management by merging EEG-based emotion recognition with a rule-based chatbot to aid users in managing negative emotions. Utilizing principles of EI, the app customizes the mobile interface color settings, suggesting activities and providing advice suited to the user’s emotional state confirmed by the chatbot. The emotion recognition model is trained and tested using the SEED-IV dataset, ensuring compatibility with consumer EEG headbands and accurate detection of complex emotions like sadness and fear. Thorough static and dynamic testing has validated the app’s design and operational efficacy, confirming its preparedness for practical use. By combining real-time EEG data analysis with intelligent chatbot interactions, “Motus Up” stands out as an innovative mental health tool that enhances EI and offers a responsive experience for emotional self-regulation. This integration of technology and psychology in a mobile platform is poised to improve mental well-being and EI on a personal scale.
期刊介绍:
Human Behavior and Emerging Technologies is an interdisciplinary journal dedicated to publishing high-impact research that enhances understanding of the complex interactions between diverse human behavior and emerging digital technologies.