{"title":"抗压力:一种可穿戴设备与实时呼吸反馈压力缓解","authors":"Jin-Wei Hou;Edward T.-H. Chu;Chia-Rong Lee","doi":"10.1109/TAFFC.2025.3564868","DOIUrl":null,"url":null,"abstract":"Relieving stress is crucial for the health of modern individuals. Deep breathing exercises have been shown to be effective for stress relief. However, the effectiveness of deep breathing exercises is limited if feedback on breathing patterns is not provided instantly. For this, we propose a wearable device called Anti-Stress, which can provide users with breathing patterns in real-time, enabling them to dynamically adjust their breathing according to Anti-Stress instructions for optimal relaxation. In addition, Anti-Stress provides users with objective stress indices by measuring the user's heart rate variability (HRV). The accuracy of Anti-Stress in detecting breathing patterns is up to 99%, and its response time is less than 200 ms, ensuring users can receive immediate guidance. To evaluate the effectiveness of Anti-Stress, we recruited 60 participants to conduct an empirical experiment. The ANCOVA analysis shows that the experimental group significantly reduces stress by using Anti-Stress compared to the control group without it. Furthermore, the usability questionnaires including SUS and QUIS demonstrate Anti-Stress's higher usability compared to a traditional non-biofeedback app. Our analysis also reveals that people with high openness or neuroticism personalities had better stress relief by using Anti-Stress. The results of this study demonstrate the feasibility and practicality of our respiratory feedback mechanism in helping users relieve stress and enhancing the effectiveness of deep breathing exercises.","PeriodicalId":13131,"journal":{"name":"IEEE Transactions on Affective Computing","volume":"16 3","pages":"2479-2490"},"PeriodicalIF":9.8000,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Anti-Stress: A Wearable Device With Real-Time Breathing Feedback for Stress Relief\",\"authors\":\"Jin-Wei Hou;Edward T.-H. Chu;Chia-Rong Lee\",\"doi\":\"10.1109/TAFFC.2025.3564868\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Relieving stress is crucial for the health of modern individuals. Deep breathing exercises have been shown to be effective for stress relief. However, the effectiveness of deep breathing exercises is limited if feedback on breathing patterns is not provided instantly. For this, we propose a wearable device called Anti-Stress, which can provide users with breathing patterns in real-time, enabling them to dynamically adjust their breathing according to Anti-Stress instructions for optimal relaxation. In addition, Anti-Stress provides users with objective stress indices by measuring the user's heart rate variability (HRV). The accuracy of Anti-Stress in detecting breathing patterns is up to 99%, and its response time is less than 200 ms, ensuring users can receive immediate guidance. To evaluate the effectiveness of Anti-Stress, we recruited 60 participants to conduct an empirical experiment. The ANCOVA analysis shows that the experimental group significantly reduces stress by using Anti-Stress compared to the control group without it. Furthermore, the usability questionnaires including SUS and QUIS demonstrate Anti-Stress's higher usability compared to a traditional non-biofeedback app. Our analysis also reveals that people with high openness or neuroticism personalities had better stress relief by using Anti-Stress. The results of this study demonstrate the feasibility and practicality of our respiratory feedback mechanism in helping users relieve stress and enhancing the effectiveness of deep breathing exercises.\",\"PeriodicalId\":13131,\"journal\":{\"name\":\"IEEE Transactions on Affective Computing\",\"volume\":\"16 3\",\"pages\":\"2479-2490\"},\"PeriodicalIF\":9.8000,\"publicationDate\":\"2025-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Affective Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10979488/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Affective Computing","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10979488/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Anti-Stress: A Wearable Device With Real-Time Breathing Feedback for Stress Relief
Relieving stress is crucial for the health of modern individuals. Deep breathing exercises have been shown to be effective for stress relief. However, the effectiveness of deep breathing exercises is limited if feedback on breathing patterns is not provided instantly. For this, we propose a wearable device called Anti-Stress, which can provide users with breathing patterns in real-time, enabling them to dynamically adjust their breathing according to Anti-Stress instructions for optimal relaxation. In addition, Anti-Stress provides users with objective stress indices by measuring the user's heart rate variability (HRV). The accuracy of Anti-Stress in detecting breathing patterns is up to 99%, and its response time is less than 200 ms, ensuring users can receive immediate guidance. To evaluate the effectiveness of Anti-Stress, we recruited 60 participants to conduct an empirical experiment. The ANCOVA analysis shows that the experimental group significantly reduces stress by using Anti-Stress compared to the control group without it. Furthermore, the usability questionnaires including SUS and QUIS demonstrate Anti-Stress's higher usability compared to a traditional non-biofeedback app. Our analysis also reveals that people with high openness or neuroticism personalities had better stress relief by using Anti-Stress. The results of this study demonstrate the feasibility and practicality of our respiratory feedback mechanism in helping users relieve stress and enhancing the effectiveness of deep breathing exercises.
期刊介绍:
The IEEE Transactions on Affective Computing is an international and interdisciplinary journal. Its primary goal is to share research findings on the development of systems capable of recognizing, interpreting, and simulating human emotions and related affective phenomena. The journal publishes original research on the underlying principles and theories that explain how and why affective factors shape human-technology interactions. It also focuses on how techniques for sensing and simulating affect can enhance our understanding of human emotions and processes. Additionally, the journal explores the design, implementation, and evaluation of systems that prioritize the consideration of affect in their usability. We also welcome surveys of existing work that provide new perspectives on the historical and future directions of this field.