Gaggioli Andrea, Cipresso Pietro, Serino Silvia, Pioggia Giovanni, Tartarisco Gennaro, Baldus Giovanni, Corda Daniele, Riva Giuseppe
Applied Technology for Neuro-Psychology Lab, Istituto Auxologico Italiano, Milan, Italy.
Stud Health Technol Inform. 2012;173:136-8.
Self tracking is a recent trend in e-health that refers to the collection, elaboration and visualization of personal health data through ubiquitous computing tools such as mobile devices and wearable sensors. Here, we describe the design of a mobile self-tracking platform that has been specifically designed for clinical and research applications in the field of mental health. The smartphone-based application allows collecting a) self-reported feelings and activities from pre-programmed questionnaires; b) electrocardiographic (ECG) data from a wireless sensor platform worn by the user; c) movement activity information obtained from a tri-axis accelerometer embedded in the wearable platform. Physiological signals are further processed by the application and stored on the smartphone's memory. The mobile data collection platform is free and released under an open source licence to allow wider adoption by the research community (download at: http://sourceforge.net/projects/psychlog/).
自我追踪是电子健康领域最近的一种趋势，它指的是通过移动设备和可穿戴传感器等普适计算工具来收集、处理和可视化个人健康数据。在此，我们描述了一个专门为心理健康领域的临床和研究应用而设计的移动自我追踪平台的设计。这个基于智能手机的应用程序允许收集：a) 来自预编程问卷的自我报告的感受和活动；b) 用户佩戴的无线传感器平台的心电图（ECG）数据；c) 从可穿戴平台中嵌入的三轴加速度计获得的运动活动信息。生理信号由该应用程序进一步处理并存储在智能手机的内存中。这个移动数据收集平台是免费的，并根据开源许可发布，以允许研究社区更广泛地采用（下载地址：http://sourceforge.net/projects/psychlog/）。
