The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
Collection and Processing of Data from Wrist Wearable Devices in Heterogeneous and Multiple-User Scenarios
Open accessAbstract
Over recent years, we have witnessed the development of mobile and wearable technologies to collect data from human vital signs and activities. Nowadays, wrist wearables including sensors (e.g., heart rate, accelerometer, pedometer) that provide valuable data are common in market. We are working on the analytic exploitation of this kind of data towards the support of learners and teachers in educational contexts. More precisely, sleep and stress indicators are defined to assist teachers and learners on the regulation of their activities. During this development, we have identified interoperability challenges related to the collection and processing of data from wearable devices. Different vendors adopt specific approaches about the way data can be collected from wearables into third-party systems. This hinders such developments as the one that we are carrying out. This paper contributes to identifying key interoperability issues in this kind of scenario and proposes guidelines to solve them. Taking into account these topics, this work is situated in the context of the standardization activities being carried out in the Internet of Things and Machine to Machine domains.
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“Previous research has highlighted risks stemming from inadequate data protection, opaque third-party sharing practices, and regulatory gaps that leave users vulnerable to breaches 33,42,54 .”
From Privacy in consumer wearable technologies: a living systematic analysis of data policies across leading manufacturers (2025) · cites this paper as [54]
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“Therefore, rather than comprising only standardised functional test data, as would be the case in a clinical setting, the patient ambulatory movement dataset contains data corresponding to all patient movements whilst wearing each IMU sensor, including rest, casual walking, strenuous exercise and sleeping [36].”
From Review of Wearable Devices and Data Collection Considerations for Connected Health (2021) · cites this paper as [36]
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“In a similar way, this problem is being replicated in wearable devices. a similar way, this problem is being replicated in wearable devices”
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Metadata
- Authors
- De Arriba-Pérez, F., Caeiro-Rodríguez, M., & Santos-Gago, J.
- Affiliations
- Universidade de Vigo (ES)
- Department of Telematics Engineering, University of Vigo, Campus Lagoas-Marcosende, Vigo 36310, Spain
- Corresponding author
- De Arriba-Pérez, Francisco
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2016-09-21
- Volume
- 16
- Issue
- 9
- Pages
- 1538
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC5038811
- OpenAlex
- W2523343665
- Semantic Scholar
- 25fb7987917007358083b5e826ad57c75f5f4694
- Cited by
- 153
- References
- 42
- Citations by year
- 2026: 10 · 2025: 12 · 2024: 16 · 2023: 13 · 2022: 12 · 2021: 26 · 2020: 23 · 2019: 25 · 2018: 12 · 2017: 4
- FWCI
- 9.29
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Investigo Institutional repository of UVigo (Universidade de Vigo) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Xunta de Galicia (GRC2013-006)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
- Keywords
- wearable sensor data, interoperability, heterogeneous devices, sleep monitoring, stress symptoms, heart rate, accelerometer, pedometers, machine-to-machine communication, data collection and processing
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