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Creators/Authors contains: "Yu, Haoxiang"

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  1. ; ; ; ; (, 2023 IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems (MASS))
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  2. ; ; ; ; ; (, Proceedings of the Human Factors and Ergonomics Society Annual Meeting)
    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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  3. ; ; ; ; (, 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops))
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  4. ; ; (, SenSys '21: Proceedings of the 19th ACM Conference on Embedded Networked Sensor Systems)
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  5. ; ; ; ; ; ; (, 2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI))
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