Levy Lital, Ambaw Asmare, Ben-Itzchak Esther, Holdengreber Eldad
The Department of Mechanical Engineering and Mechatronics, Ariel University, Ariel, Israel.
The Department of Communication Disorders, Ariel University, Ariel, Israel.
Sci Rep. 2024 Dec 28;14(1):31527. doi: 10.1038/s41598-024-83229-2.
Autism spectrum disorder (ASD) involves challenges in communication and social interaction, including challenges in recognizing emotions. Existing technological solutions aim to improve social behaviors in individuals with ASD by providing learning aids. This paper presents a real-time environmental translator designed to enhance social behaviors in individuals with ASD using sensory substitution. Our system utilizes vibrotactile and visual feedback to interpret and convey emotional states through vibration patterns emitted from small vibration motors on the user's temple, complemented by color-coded displays of emotional intensity. It can detect seven emotions: neutral, sad, happy, angry, disgust, surprise, and fear. Testing with adults with ASD showed they could adapt to the system in about 19 min, enabling them to intuitively and immediately recognize others' emotions. This innovative approach presents a promising advancement in emotion recognition technology for individuals with ASD, offering potential benefits in enhancing their social interactions and communication skills.
自闭症谱系障碍（ASD）涉及沟通和社交互动方面的挑战，包括识别情绪的挑战。现有的技术解决方案旨在通过提供学习辅助工具来改善自闭症患者的社交行为。本文介绍了一种实时环境翻译器，旨在通过感官替代来增强自闭症患者的社交行为。我们的系统利用振动触觉和视觉反馈，通过用户太阳穴上的小型振动电机发出的振动模式来解释和传达情绪状态，并辅以情绪强度的颜色编码显示。它可以检测七种情绪：中性、悲伤、快乐、愤怒、厌恶、惊讶和恐惧。对成年自闭症患者的测试表明，他们可以在大约19分钟内适应该系统，从而能够直观且立即识别他人的情绪。这种创新方法在自闭症患者的情绪识别技术方面取得了有前景的进展，在增强他们的社交互动和沟通技巧方面具有潜在益处。
