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

Arriba-Pérez, Francisco de; Caeiro-Rodríguez, Manuel; Santos-Gago, Juan M.

doi:10.3390/s16091538

Cited by 130 publications

(79 citation statements)

References 37 publications

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“…Only lately FDA approved devices capable of providing ECG tracking; (2) Data processing and optimization, which requires threshold-based methods [129]; (3) Data transfer which is usually done by third-party systems which might result in random and partial data transfers. This can be addressed by applications that provide fixed transfers times [130]; (4) Data storage, especially of the large volume longitudinal signals such as blood pressure, ECG etc. An efficient solution requires cloud storage services [131].…”

Section: Utilization Of Smart Devicesmentioning

confidence: 99%

Novel Approaches to Air Pollution Exposure and Clinical Outcomes Assessment in Environmental Health Studies

et al. 2020

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An accurate assessment of pollutants’ exposure and precise evaluation of the clinical outcomes pose two major challenges to the contemporary environmental health research. The common methods for exposure assessment are based on residential addresses and are prone to many biases. Pollution levels are defined based on monitoring stations that are sparsely distributed and frequently distanced far from residential addresses. In addition, the degree of an association between outdoor and indoor air pollution levels is not fully elucidated, making the exposure assessment all the more inaccurate. Clinical outcomes’ assessment, on the other hand, mostly relies on the access to medical records from hospital admissions and outpatients’ visits in clinics. This method differentiates by health care seeking behavior and is therefore, problematic in evaluation of an onset, duration, and severity of an outcome. In the current paper, we review a number of novel solutions aimed to mitigate the aforementioned biases. First, a hybrid satellite-based modeling approach provides daily continuous spatiotemporal estimations with improved spatial resolution of 1 × 1 km2 and 200 × 200 m2 grid, and thus allows a more accurate exposure assessment. Utilizing low-cost air pollution sensors allowing a direct measurement of indoor air pollution levels can further validate these models. Furthermore, the real temporal-spatial activity can be assessed by GPS tracking devices within the individuals’ smartphones. A widespread use of smart devices can help with obtaining objective measurements of some of the clinical outcomes such as vital signs and glucose levels. Finally, human biomonitoring can be efficiently done at a population level, providing accurate estimates of in-vivo absorbed pollutants and allowing for the evaluation of body responses, by biomarkers examination. We suggest that the adoption of these novel methods will change the research paradigm heavily relying on ecological methodology and support development of the new clinical practices preventing adverse environmental effects on human health.

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Section: Utilization Of Smart Devicesmentioning

confidence: 99%

Novel Approaches to Air Pollution Exposure and Clinical Outcomes Assessment in Environmental Health Studies

et al. 2020

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“…In addition, the reliability of biosignal data collected from wearable devices has noticeably increased owing to the recent evolution of wearable devices such as smartwatches [27]. Diverse platforms have been developed to collect data, and it is now possible to measure patients' status and information on their surrounding environments using sensors through IoT and wearable devices [28]. Products such as S-Health by Samsung [29], Google Fit by Google [30], HealthKit by Apple [31], and Fitbit by Fitbit Inc. [32] all use their respective platforms to save data collected from smartwatches and various IoT devices onto a cloud server.…”

Section: Healthcare Platform and Analysismentioning

confidence: 99%

A Study of Prescriptive Analysis Framework for Human Care Services Based On CKAN Cloud

2018

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A number of sensor devices are widely distributed and used today owing to the accelerated development of IoT technology. In particular, this technological advancement has allowed users to carry IoT devices with more convenience and efficiency. Based on the IoT sensor data, studies are being actively carried out to recognize the current situation or to analyze and predict future events. However, research for existing smart healthcare services is focused on analyzing users' behavior from single sensor data and is also focused on analyzing and diagnosing the current situation of the users. Therefore, a method for effectively managing and integrating a large amount of IoT sensor data has become necessary, and a framework considering data interoperability has become necessary. In addition, an analysis framework is needed not only to provide the analysis of the users' environment and situation from the integrated data, but also to provide guide information to predict future events and to take appropriate action by users. In this paper, we propose a prescriptive analysis framework using a 5W1H method based on CKAN cloud. Through the CKAN cloud environment, IoT sensor data stored in individual CKANs can be integrated based on common concepts. As a result, it is possible to generate an integrated knowledge graph considering interoperability of data, and the underlying data is used as the base data for prescriptive analysis. In addition, the proposed prescriptive analysis framework can diagnose the situation of the users through analysis of user environment information and supports users' decision making by recommending the possible behavior according to the coming situation of the users. We have verified the applicability of the 5W1H prescriptive analysis framework based on the use case of collecting and analyzing data obtained from various IoT sensors.

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“…For instance, the process of implicit authentication using biological data is now possible with COTS(Commercial, Off-The-Shelf) components. A smartwatch can access multiple kinds of information including heart rate data and more [6]. The matching a set of recorded data to a user accessing a work terminal.…”

Section: Introductionmentioning

confidence: 99%

On the Emerging Area of Biocybersecurity and Relevant Considerations

Palmer

Potter

Karahan

2020

Advances in Intelligent Systems and Computing

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Biocybersecurity is a novel space for the 21st century that meets our innovations in biotechnology and computing head on. Within this space, many considerations are open for and demand consideration as groups endeavor to develop products and policies that adequately ensure asset management and protection. Herein, simplified and brief exploration is given followed by some surface discussion of impacts. These impacts concern the end user, ethical and legal considerations, international proceedings, business, and limitations. It is hoped that this will be helpful in future considerations towards biocybersecurity policy developments and implementations. AQ1 AQ2 Notice: This article has been queued for publication in the Proceedings of the 2020 Future of Information and Communication Conference (FICC)

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

Cited by 130 publications

References 37 publications

Novel Approaches to Air Pollution Exposure and Clinical Outcomes Assessment in Environmental Health Studies

Novel Approaches to Air Pollution Exposure and Clinical Outcomes Assessment in Environmental Health Studies

A Study of Prescriptive Analysis Framework for Human Care Services Based On CKAN Cloud

On the Emerging Area of Biocybersecurity and Relevant Considerations

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