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dc.contributor.authorMuzny, Miroslav
dc.contributor.authorHenriksen, André
dc.contributor.authorGiordanengo, Alain
dc.contributor.authorMužík, Jan
dc.contributor.authorGrøttland, Astrid
dc.contributor.authorBlixgård, Håvard Kvalvåg
dc.contributor.authorHartvigsen, Gunnar
dc.contributor.authorÅrsand, Eirik
dc.date.accessioned2019-11-04T08:05:29Z
dc.date.available2019-11-04T08:05:29Z
dc.date.issued2019-10-31
dc.description.abstract<i>Background</i> - Wearable devices with an ability to collect various type of physiological data are increasingly becoming seamlessly integrated into everyday life of people. In the area of electronic health (eHealth), many of these devices provide remote transfer of health data, as a result of the increasing need for ambulatory monitoring of patients. This has a potential to reduce the cost of care due to prevention and early detection.<p> <p><i>Objective</i> - The objective of this study was to provide an overview of available wearable sensor systems with data exchange possibilities. Due to the heterogeneous capabilities these systems possess today, we aimed to systematize this in terms of usage, where there is a need of, or users benefit from, transferring self‐ collected data to health care actors. <p> <p><i>Methods</i> - We searched for and reviewed relevant sensor systems (i.e., devices) and mapped these into 13 selected attributes related to data‐exchange capabilities. We collected data from the Vandrico database of wearable devices, and complemented the information with an additional internet search. We classified the following attributes of devices: type, communication interfaces, data protocols, smartphone/PC integration, connection to smartphone health platforms, 3rd party integration with health platforms, connection to health care system/middleware, type of gathered health data, integrated sensors, medical device certification, access to user data, developer‐access to device, and market status. Devices from the same manufacturer with similar functionalities/characteristics were identified under the same device family. Furthermore, we classified the systems in three subgroups of relevance for different actors in mobile health monitoring systems: EHR providers, software developers, and patient users.<p> <p><i>Results</i> - We identified 362 different mobile health monitoring devices belonging to 193 device families. Based on an analysis of these systems, we identified the following general challenges:<p> <ul> <li>Few systems have a Conformité Européene (CE) marking class II or above, or approval from the US Food and Drug Administration (FDA)</li> <li>Few systems use the standardized Bluetooth Low Energy GATT profile for wireless transfer of health data</li> <li>Few systems support health middleware</li> <li>Approximately 30% of the device families provide the user access to the source data. However, only 16% allow the transfer of data through direct communication with the device (i.e., without using a proprietary cloud‐based service)</li></ul><p> <p><i>Conclusions</i> - Few of the identified mobile health monitoring systems use standardized, open communication protocols, which would allow the user to directly acquire sensor data. Use of open protocols can provide mobile health (mHealth) application developers an alternative to proprietary cloud services and communication tools, which are often closely integrated with the devices. Emerging new types of sensors, often intended for everyday use, have a potential to supplement health records systems with data that can enrich patient care.en_US
dc.descriptionAccepted manuscript. Final version published in <i>International Journal of Medical Informatics</i> is available at <a href=https://doi.org/10.1016/j.ijmedinf.2019.104017>https://doi.org/10.1016/j.ijmedinf.2019.104017. </a>en_US
dc.identifier.citationMuzny, M., Henriksen, A., Giordanengo, A., Mužík, J., Grøttland, A., Blixgård, H. ... Årsand, E. (2019). Wearable Sensors with Possibilities for Data Exchange: Analyzing Statusand Needs of Different Actors in Mobile Health Monitoring Systems. <i>International Journal of Medical Informatics</i>, 104017. https://doi.org/10.1016/j.ijmedinf.2019.104017en_US
dc.identifier.cristinIDFRIDAID 1742916
dc.identifier.doi10.1016/j.ijmedinf.2019.104017
dc.identifier.issn1386-5056
dc.identifier.issn1872-8243
dc.identifier.urihttps://hdl.handle.net/10037/16577
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.ispartofFinal version of this paper is part of:<p> Giordanengo, A. (2020). Using FullFlow to manage the overwhelming flood of patients’ self-collected health data: A system that addresses acceptance barriers regarding the introduction of diabetes patients’ self-collected health data into electronic health records and medical consultations. (Doctoral thesis). <a href=https://hdl.handle.net/10037/17842>https://hdl.handle.net/10037/17842. </a>
dc.relation.journalInternational Journal of Medical Informatics
dc.rights.accessRightsopenAccessen_US
dc.subjectVDP::Technology: 500::Medical technology: 620en_US
dc.subjectVDP::Teknologi: 500::Medisinsk teknologi: 620en_US
dc.titleWearable Sensors with Possibilities for Data Exchange: Analyzing Statusand Needs of Different Actors in Mobile Health Monitoring Systemsen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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