mDebugger: Assessing and diagnosing the fidelity and yield of mobile sensor data

Mahbubur M. Rahman, Nasir Ali, Rummana Bari, Nazir Saleheen, Mustafa al'Absi, Emre Ertin, Ashley Kennedy, Kenzie L. Preston, Santosh Kumar

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations

Abstract

Mobile sensor data collected in the natural environment are subject to numerous sources of data loss and quality deterioration. This may be due to degradation in attachment, change in placement, battery depletion, wireless interference, or movement artifacts. Identifying and fixing the major sources of data loss is critical to ensuring high data yield from mobile sensors. This chapter describes a systematic approach for identifying the major sources of data loss that can then be used to improve mobile sensor data yield.

Original languageEnglish (US)
Title of host publicationMobile Health
Subtitle of host publicationSensors, Analytic Methods, and Applications
PublisherSpringer International Publishing
Pages121-143
Number of pages23
ISBN (Electronic)9783319513942
ISBN (Print)9783319513935
DOIs
StatePublished - Jul 12 2017

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Rahman, M. M., Ali, N., Bari, R., Saleheen, N., al'Absi, M., Ertin, E., Kennedy, A., Preston, K. L., & Kumar, S. (2017). mDebugger: Assessing and diagnosing the fidelity and yield of mobile sensor data. In Mobile Health: Sensors, Analytic Methods, and Applications (pp. 121-143). Springer International Publishing. https://doi.org/10.1007/978-3-319-51394-2_7