TY - Jour A2 - Riziotis，Christos Au - Dealard，Glen Au - De Witte，Nele Au - Sels，Romy Au - Mertens，Marc Au - Van Daele，Tom Au - Bonroy，Bert PY - 2020 DA - 2020 / 11/25TI - 通过具有应力检测算法的在线平台可用于精神医疗保健的可穿戴技术：Carewear Project SP - 8846077 VL - 2020 AB - 在过去几年中，移动健康（MHealth）应用以及专门的可穿戴物能够收集增加心理健康质量的数据。尽管可穿戴技术的潜力较大，但目前缺乏缺乏工具和知识的精神医疗保健专业人员在实践中妥善实施和利用这项技术。Carewear项目旨在开发和评估在线平台，允许医疗保健专业人员在临床实践中使用可穿戴物的数据。科咨机通过自我跟踪实现数据收集，旨在帮助人们在行为改变过程中，作为精神医疗保健专业人员指导的更广泛的干预或治疗的组成部分。EMPatica E4可穿戴物用于在现实生活中收集加速度计数据，电熨斗活动（EDA）和血容量脉冲（BVP）。该数据上传到Carewear平台，其中算法计算急性应力，平均休息心率（HR），HR变异性（HRV），步数，活动期间和总活动分钟的瞬间。检测到的急性应力的瞬间可以注释，以指示它们是否与负应力感相关联。此外，可以详细阐述当天的情绪。 The online platform presents this information in a structured way to both the client and their mental healthcare professional. The goal of the current study was a first assessment of the accuracy of the algorithms in real life through comparisons with comprehensive annotated data in a small sample of five healthy participants without known stress-related complaints. Additionally, we assessed the usability of the application through user reports concerning their experiences with the wearable and online platform. While the current study shows that a substantial amount of false positives are detected in a healthy sample and that usability could be improved, the concept of a user-friendly platform to combine physiological data with self-report to inform on stress and mental health is viewed positively in our pilots. SN - 1687-725X UR - https://doi.org/10.1155/2020/8846077 DO - 10.1155/2020/8846077 JF - Journal of Sensors PB - Hindawi KW - ER -