Collecting and analyzing smartphone sensor data for health

被引:2
|
作者
Drake, Justin A. [1 ]
Gaither, Kelly [1 ]
Schulz, Karl W. [2 ]
Bukowski, Radek [2 ]
机构
[1] Texas Adv Comp Ctr, Austin, TX 78758 USA
[2] Dell Med Sch, Austin, TX USA
基金
美国国家科学基金会;
关键词
smartphone; sensors; digital biomarker; open-source; time-series;
D O I
10.1145/3437359.3465599
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Evidence suggests that signatures of health and disease, or digital biomarkers, exist within the heterogeneous, temporally-dense data gathered from smartphone sensors and wearable devices that can be leveraged for medical applications. Modern smartphones contain a collection of energy-efficient sensors capable of capturing the device's movement, orientation, and location as well characteristics of its external environment (e.g. ambient temperature, sound, pressure). When paired with peripheral wearable devices like smart watches, smartphones can also facilitate the collection/aggregation of important vital signs like heart rate and oxygen saturation. Here we discuss our recent experiences with deploying an open-source, cloud-native framework to monitor and collect smartphone sensor data from a cohort of pregnant women over a period of one year. We highlight two open-source integrations into the pipeline we found particularly useful: 1) a dashboard-built with Grafana and backed by Graphite-to monitor and manage production server loads and data collection metrics across the study cohort and 2) a back-end storage solution with InfluxDB, a multi-tenant time series database and data exploration ecosystem, to support biomarker discovery efforts of a multidisciplinary research team.
引用
收藏
页数:4
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