Hossain Syed Monowar, Hnat Timothy, Saleheen Nazir, Nasrin Nusrat Jahan, Noor Joseph, Ho Bo-Jhang, Condie Tyson, Srivastava Mani, Kumar Santosh
University of Memphis.
University of California, Los Angeles.
Proc Int Conf Embed Netw Sens Syst. 2017 Nov;2017. doi: 10.1145/3131672.3131694.
The development and validation studies of new multisensory biomarkers and sensor-triggered interventions requires collecting raw sensor data with associated labels in the natural field environment. Unlike platforms for traditional mHealth apps, a software platform for such studies needs to not only support high-rate data ingestion, but also share raw high-rate sensor data with researchers, while supporting high-rate sense-analyze-act functionality in real-time. We present , a realization of such a platform, which supports high-rate data collections from multiple sensors with realtime assessment of data quality. A scalable storage architecture (with near optimal performance) ensures quick response despite rapidly growing data volume. Micro-batching and efficient sharing of data among multiple source and sink apps allows reuse of computations to enable real-time computation of multiple biomarkers without saturating the CPU or memory. Finally, it has a reconfigurable scheduler which manages all prompts to participants that is burden- and context-aware. With a modular design currently spanning 23+ apps, mCerebrum provides a comprehensive ecosystem of system services and utility apps. The design of mCerebrum has evolved during its concurrent use in scientific field studies at ten sites spanning 106,806 person days. Evaluations show that compared with other platforms, mCerebrum's architecture and design choices support 1.5 times higher data rates and 4.3 times higher storage throughput, while causing 8.4 times lower CPU usage.
• ; • → Embedded and cyber-physical systems.
Syed Monowar Hossain, Timothy Hnat, Nazir Saleheen, Nusrat Jahan Nasrin, Joseph Noor, Bo-Jhang Ho, Tyson Condie, Mani Srivastava, and Santosh Kumar. 2017. mCerebrum: A Mobile Sensing Software Platform for Development and Validation of Digital Biomarkers and Interventions. In , 14 pages.
新型多感官生物标志物和传感器触发干预措施的开发与验证研究需要在自然场景环境中收集带有相关标注的原始传感器数据。与传统移动健康应用程序的平台不同，此类研究的软件平台不仅需要支持高速数据摄取，还需要与研究人员共享原始高速传感器数据，同时实时支持高速传感-分析-行动功能。我们展示了mCerebrum，这样一个平台的实现，它支持从多个传感器进行高速数据收集，并对数据质量进行实时评估。一种可扩展的存储架构（具有近乎最佳的性能）确保了尽管数据量快速增长仍能快速响应。微批处理以及在多个源应用程序和接收应用程序之间高效共享数据允许重复使用计算，从而能够在不使CPU或内存饱和的情况下实时计算多个生物标志物。最后，它有一个可重新配置的调度器，该调度器管理所有对参与者的提示，且具有负担感知和情境感知能力。凭借目前涵盖23个以上应用程序的模块化设计，mCerebrum提供了一个全面的系统服务和实用程序应用程序生态系统。mCerebrum的设计在其于十个地点进行的科学实地研究中同时使用期间不断演变，这些研究涵盖了106,806人日。评估表明，与其他平台相比，mCerebrum的架构和设计选择支持的数据速率高出1.5倍，存储吞吐量高出4.3倍，同时CPU使用率低8.4倍。
CCS概念：• ；• → 嵌入式和信息物理系统。
ACM参考格式：Syed Monowar Hossain、Timothy Hnat、Nazir Saleheen、Nusrat Jahan Nasrin、Joseph Noor、Bo-Jhang Ho、Tyson Condie、Mani Srivastava和Santosh Kumar。2017年。mCerebrum：用于数字生物标志物和干预措施开发与验证的移动传感软件平台。在 ，第14页。
