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Towards the Interpretation of Sound Measurements from Smartphones Collected with Mobile Crowdsensing in the Healthcare Domain: An Experiment with Android Devices.

, , and . Sensors, 22 (1): 170 (2022)

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Ensuring compliance of distributed and collaborative workflows., , , , and . CollaborateCom, page 133-142. ICST / IEEE, (2013)Mobile Crowd Sensing in Clinical and Psychological Trials - A Case Study., , , , and . CBMS, page 23-24. IEEE Computer Society, (2015)Using Smart Mobile Devices for Collecting Structured Data in Clinical Trials: Results from a Large-Scale Case Study., , and . CBMS, page 13-18. IEEE Computer Society, (2015)Context-Based Prevention and Handling of Exceptions for Human-Centric Mobile Services., and . AIMS@SERVICES, page 100-104. IEEE Computer Society, (2017)Managing Processes on Mobile Devices: The MARPLE Approach., , and . CAiSE Forum, volume 592 of CEUR Workshop Proceedings, CEUR-WS.org, (2010)Using Insights from Cognitive Neuroscience to Investigate the Effects of Event-Driven Process Chains on Process Model Comprehension., , , , , and . Business Process Management Workshops, volume 308 of Lecture Notes in Business Information Processing, page 446-459. Springer, (2017)Applicability of Immersive Analytics in Mixed Reality: Usability Study., , , , , , , , , and 1 other author(s). IEEE Access, (2019)Prospective crowdsensing versus retrospective ratings of tinnitus variability and tinnitus-stress associations based on the TrackYourTinnitus mobile platform., , , , , , , and . Int. J. Data Sci. Anal., 8 (4): 327-338 (2019)Towards the Interpretation of Sound Measurements from Smartphones Collected with Mobile Crowdsensing in the Healthcare Domain: An Experiment with Android Devices., , and . Sensors, 22 (1): 170 (2022)End-User Programming of Mobile Services: Empowering Domain Experts to Implement Mobile Data Collection Applications., , , , , and . IEEE MS, page 1-8. IEEE Computer Society, (2016)