Collection and Processing of Data from Wrist Wearable Devices in Heterogeneous and Multiple-User Scenarios

De Arriba-Pérez, Francisco; Caeiro-Rodríguez, Manuel; Santos-Gago, Juan

doi:10.3390/s16091538

Cited by 153Context-Aware Activity Recognition SystemsIoT and Edge/Fog ComputingWireless Body Area Networks

Collection and Processing of Data from Wrist Wearable Devices in Heterogeneous and Multiple-User Scenarios

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De Arriba-Pérez, Francisco, Caeiro-Rodríguez, Manuel, Santos-Gago, Juan·2016·Sensors

DOI 10.3390/s16091538PMC PMC5038811

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Abstract

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.
“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]
Section 5.2 describes user permission for third-party access to private wearable data and says access tokens have limited lifetimes because of security concerns. The Conclusions frame the paper’s findings as interoperability and standardization issues. Our copy does not address inadequate data protection, opaque sharing practices, regulatory gaps, or breaches; those risks cannot be verified from this source. (LLM, conf=0.73)
Experimental — accuracy not yet measured
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.
“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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Authors: De Arriba-Pérez, F., Caeiro-Rodríguez, M., & Santos-Gago, J.
Affiliations: Department of Telematics Engineering, University of Vigo, Campus Lagoas-Marcosende, Vigo 36310, Spain
Universidade de Vigo (ES)
ORCID: Santos-Gago, Juan
Venue: Sensors
Publisher: MDPI AG
Published: 2016-09-21
Volume: 16
Issue: 9
Pages: 1538
ISSN: 1424-8220 (ISSN-L)
DOI: 10.3390/s16091538
PMC: PMC5038811
OpenAlex: W2523343665
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: cc-by
creativecommons.org/licenses/by/4.0/ (vor)
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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Collection and Processing of Data from Wrist Wearable Devices in Heterogeneous and Multiple-User Scenarios

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