Over the past years, mobile health (mHealth) applications and specifically wearables have become able and available to collect data of increasing quality of relevance for mental health. Despite the large potential of wearable technology, mental healthcare professionals are currently lacking tools and knowledge to properly implement and make use of this technology in practice. The Carewear project is aimed at developing and evaluating an online platform, allowing healthcare professionals to use data from wearables in their clinical practice. Carewear implements data collection through self-tracking, which is aimed at helping people in their behavioral change process, as a component of a broader intervention or therapy guided by a mental healthcare professional. The Empatica E4 wearables are used to collect accelerometer data, electrodermal activity (EDA), and blood volume pulse (BVP) in real life. This data is uploaded to the Carewear platform where algorithms calculate moments of acute stress, average resting heart rate (HR), HR variability (HRV), step count, active periods, and total active minutes. The detected moments of acute stress can be annotated to indicate whether they are associated with a negative feeling of stress. Also, the mood of the day can be elaborated on. 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.

中文翻译：

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通过带有压力检测算法的在线平台使可穿戴技术可用于精神保健：Carewear项目

在过去的几年中，移动健康（mHealth）应用程序（特别是可穿戴设备）已经能够并且可以用来收集与心理健康相关的质量不断提高的数据。尽管可穿戴技术潜力巨大，但精神保健专业人员目前仍缺乏在实践中正确实施和利用该技术的工具和知识。Carewear项目旨在开发和评估在线平台，使医疗保健专业人员可以在临床实践中使用可穿戴设备中的数据。Carewear通过自我跟踪来实现数据收集，该跟踪旨在帮助人们进行行为改变，这是心理保健专业人员进行的广泛干预或治疗的一部分。Empatica E4可穿戴设备用于收集加速度计数据，现实生活中的皮肤电活动（EDA）和血容量脉冲（BVP）。将该数据上传到Carewear平台，在该平台上，算法会计算出急性压力的时刻，平均静息心率（HR），HR变异性（HRV），步数，活动时间和总活动时间。可以对检测到的急性压力瞬间进行注释，以指示它们是否与压力的负面感觉有关。此外，可以阐述一天的心情。在线平台以结构化的方式向客户及其心理保健专业人员提供此信息。本研究的目标是通过与五个有健康压力的参与者（没有已知的压力相关抱怨）的一小样本中的综合注释数据进行比较，来首次评估算法在现实生活中的准确性。另外，我们通过用户报告有关他们在可穿戴和在线平台上的使用经验，评估了该应用程序的可用性。尽管当前的研究表明，在健康的样本中检测到大量的误报，并且可以改善可用性，但还是采用了用户友好平台的概念，该平台将生理数据与自我报告相结合，以告知压力和心理健康积极地在我们的飞行员中。