探讨慢性广泛性疼痛患者日常生活中应激生理与疼痛的关系

IF 9.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE IEEE Transactions on Affective Computing Pub Date : 2025-02-25 DOI:10.1109/TAFFC.2025.3545477
Emilie Pattyn;Nattapong Thammasan;Hannah Davidoff;Walter De Raedt;Gudrun Vera Eisele;Ruud van Stiphout;Maarten De Vos;Olivia J. Kirtley;Peter Van Wambeke;Bart Morlion;Elfi Vergaelen;Chris Van Hoof
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引用次数: 0

摘要

慢性广泛性疼痛仍然是一种复杂且不完全了解的疾病。为了补充现有的疼痛评估策略,本研究探索了日常生活中不显眼的生理信号作为疼痛指标的生态有效性。因此,我们使用可穿戴腕带收集了46名慢性广泛疼痛患者7天的生理数据。线性混合效应模型揭示了生理信号(如平均心率和瞬时疼痛强度)之间的一些显著关联。然而,用多元机器学习模型进行个体疼痛预测并没有增加价值。虽然这项研究强调了动态生理学对疼痛评估的潜力,但未来的研究应该验证和扩展这些初步发现,以进一步加强疼痛管理策略。
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Exploring the Relationship Between Stress-Physiology and Pain in the Daily Life of Patients With Chronic Widespread Pain
Chronic widespread pain remains a complex and incompletely understood condition. To complement existing pain assessment strategies, this study explored the ecological validity of unobtrusively captured daily life physiological signals as indicators of pain. Therefore, we collected physiological data using a wearable wristband from 46 patients with chronic widespread pain for seven days. Linear mixed-effect models revealed several significant associations between physiological signals, such as mean heart rate and momentary pain intensity. However, making individual pain predictions with multivariate machine learning models did not add value. While this study underscores the potential of ambulatory physiology for pain assessment, future research should validate and expand upon these initial findings to further enhance pain management strategies.
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来源期刊
IEEE Transactions on Affective Computing
IEEE Transactions on Affective Computing COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
15.00
自引率
6.20%
发文量
174
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.
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