@Article{信息:doi 10.2196 / / jmir。6903，作者=“Almalki, Manal and Gray, Kathleen and Martin-Sanchez, Fernando”，标题=“健康自我量化测量特征分类学的开发和验证”，期刊=“J Med Internet Res”，年=“2017”，月=“11月”，日=“03”，卷=“19”，数=“11”，页=“e378”，关键词=“健康;自我管理;self-experimentation;衣物;量化自我;分类;背景:使用可穿戴工具进行健康自我量化(SQ)引入了对一个人的身体和如何实现预期健康结果的新思路。对个人的测量，如心率、呼吸量、皮肤温度、睡眠、情绪、血压、食物消耗和周围空气质量，可以以一种从未有过的整体方式获得、量化和汇总。然而，健康SQ仍然缺乏一种正式的通用语言或分类来描述这些类型的测量。 Establishing such taxonomy is important because it would enable systematic investigations that are needed to advance in the use of wearable tools in health self-care. For a start, a taxonomy would help to improve the accuracy of database searching when doing systematic reviews and meta-analyses in this field. Overall, more systematic research would contribute to build evidence of sufficient quality to determine whether and how health SQ is a worthwhile health care paradigm. Objective: The aim of this study was to investigate a sample of SQ tools and services to build and test a taxonomy of measurements in health SQ, titled: the classification of data and activity in self-quantification systems (CDA-SQS). Methods: Eight health SQ tools and services were selected to be examined: Zeo Sleep Manager, Fitbit Ultra, Fitlinxx Actipressure, MoodPanda, iBGStar, Sensaris Senspod, 23andMe, and uBiome. An open coding analytical approach was used to find all the themes related to the research aim. Results: This study distinguished three types of measurements in health SQ: body structures and functions, body actions and activities, and around the body. Conclusions: The CDA-SQS classification should be applicable to align health SQ measurement data from people with many different health objectives, health states, and health conditions. CDA-SQS is a critical contribution to a much more consistent way of studying health SQ. ", issn="1438-8871", doi="10.2196/jmir.6903", url="//www.mybigtv.com/2017/11/e378/", url="https://doi.org/10.2196/jmir.6903", url="http://www.ncbi.nlm.nih.gov/pubmed/29101092" }