COMPASS App: A Patient-centered Physiological based Pain Assessment System

Wenchao Zhu, Chang Liu, Haoxiang Yu, Yikang Guo, Yan Xiao, Yingzi Lin
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Abstract

Chronic pain patients lack at-home pain assessment and management tools. The existing chronic-pain mobile applications are either solely relying on self-report pain levels or restricted to formal clinical settings. Our app, abbreviated from an NSF-funded project entitled Novel Computational Methods for Continuous Objective Multimodal Pain Assessment Sensing System (COMPASS), is a multi-dimensional pain app that collects physiological signals to predict objective pain levels and trace daily at-home activities by incorporating a daily check-in section. We conducted a usability test with 33 healthy participants under pain conditions. The results provided initial support for the validity of the signals in predicting internalizing pain levels among the participants. With further development and testing, we believe the COMPASS app system has the potential to be used by both patients and clinicians as an additional tool to better assess and manage pain, especially for mobile healthcare applications.
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COMPASS 应用程序:以患者为中心的生理疼痛评估系统
慢性疼痛患者缺乏家庭疼痛评估和管理工具。现有的慢性疼痛移动应用程序要么完全依赖于自我报告的疼痛水平,要么仅限于正式的临床设置。我们的应用程序,缩写自一个由美国国家科学基金会资助的项目,名为“连续客观多模态疼痛评估传感系统(COMPASS)的新型计算方法”,是一个多维疼痛应用程序,通过收集生理信号来预测客观疼痛水平,并通过纳入日常登记部分来跟踪日常家庭活动。我们对33名处于疼痛状态的健康参与者进行了可用性测试。结果初步支持了信号在预测参与者内化疼痛水平方面的有效性。随着进一步的开发和测试,我们相信COMPASS应用系统有潜力被患者和临床医生用作更好地评估和管理疼痛的额外工具,特别是在移动医疗保健应用中。
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