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Method Article
Commercial smartwatches equipped with wearable sensors are increasingly being used in population studies. However, their utility is often constrained by their limited battery duration, memory capacity, and data quality. This report provides examples of cost-effective solutions to real-life technical challenges encountered during studies involving asthmatic children and elderly cardiac patients.
Wearable sensors, which are often embedded in commercial smartwatches, allow for continuous and non-invasive health measurements and exposure assessments in clinical studies. Nevertheless, the real-life application of these technologies in studies involving a large number of participants for a significant observation period may be hindered by several practical challenges.
In this study, we present a modified protocol from a previous intervention study for the mitigation of health effects from desert dust storms. The study involved two distinct population groups: asthmatic children aged 6-11 years and elderly patients with atrial fibrillation (AF). Both groups were equipped with a smartwatch for the assessment of physical activity (using a heart rate monitor, pedometer, and accelerometer) and location (using GPS signals to locate individuals in indoor "at home" or outdoor microenvironments). The participants were required to wear the smartwatch equipped with a data collection application on a daily basis, and data were transmitted via a wireless network to a centrally administered data collection platform for the near real-time assessment of compliance.
Over a period of 26 months, more than 250 children and 50 patients with AF participated in the aforementioned study. The main technical challenges identified included restricting access to standard smartwatch features, such as gaming, internet browser, camera, and audio recording applications, technical issues, such as loss of GPS signal, especially in indoor environments, and the internal smartwatch settings interfering with the data collection application.
The aim of this protocol is to demonstrate how the use of publicly available application lockers and device automation applications made it possible to address most of these challenges in a simple and cost-effective way. In addition, the inclusion of a Wi-Fi received signal strength indicator significantly improved indoor localization and largely minimized GPS signal misclassification. The implementation of these protocols during the roll-out of this intervention study in the spring of 2020 led to significantly improved results in terms of data completeness and data quality.
Digital health technology applications and wearable sensors enable non-invasive and cost-effective patient monitoring both in healthcare and home settings1. At the same time, the large amount of data collected and the availability of wearable-based analytic platforms enable the development of algorithms for automated health event prediction, prevention, and intervention for a wide range of acute and chronic diseases2. Commercially available wearable sensors, primarily used for fitness tracking, are also increasingly being used by medical professionals in public health research and represent a promising tool for multimodal and continuous data collection under real-life conditions3. More importantly, though, unbiased data collection from wearables sensors allows researchers to overcome the challenges of recall bias that characterize traditional data collection methods such as interviews and diaries4.
However, for the purposes of clinical trials or other population studies, data accuracy, reliability, and integrity are essential. In addition, the credibility of the collected data may also be affected by several other parameters, such as age-group applicability as well as the memory capacity and energy efficiency of the device5. Recent systematic reviews of laboratory and field-based studies with limited numbers of participants have generally confirmed the applicability of commercial smartwatches for activity, heart rate, seizure, and behavior monitoring, although the reviews have also demonstrated poor suitability for elderly users, as well as battery, memory, and data quality limitations6,7. These limitations may be further amplified in larger population studies under real-life conditions where additional parameters such as inconsistent internet connectivity, device comfort, and incorrect smartwatch use come into play8. Specifically, appearance and inconvenience are significant barriers to wearing sensors daily9, while concerns relating to privacy and confidentiality issues may affect recruitment in studies involving wearable sensors10. Concerning the applicability of commercial smartwatches and fitness trackers for measuring physical activity in research studies, a recent study by Henriksen et al. suggested that the selection of an appropriate device for a particular study should not only be based on the available embedded sensors but rather also take into account validation and previous use in research, appearance, battery life, robustness, water resistance, connectivity, and usability11.
For the purposes of this study, we present a protocol to improve on the challenges encountered during the LIFE MEDEA project, an intervention study for the mitigation of the health effects of desert dust storms12. The study involved two distinct population groups: asthmatic children aged 6-11 years and elderly patients with atrial fibrillation (AF). Both groups were equipped with a commercial smartwatch for the assessment of physical activity (using a heart rate monitor, pedometer, and accelerometer) and location (using GPS signals to locate individuals in indoor "at home" or outdoor microenvironments). The participants were required to wear the smartwatch daily, and data were transmitted via a wireless network to a centrally administered data collection platform via the data collection application for the near real-time assessment of compliance. Additional details on the smartwatch and system setup are provided in a previous study13. During the first year of the project implementation, several technical and real-life challenges relating to the device emerged, which affected recruitment, the compliance of participants in wearing the device daily, and the completeness of the collected data. Some challenges were population-specific, such as the requirement of school administrators and many parents that the children wearing the smartwatches should not have access to standard smartwatch features, such as gaming, internet browser, camera, and audio-recording applications. Other challenges were technical in nature, such as loss of GPS signal, especially in indoor environments, and internal smartwatch settings interfering with the data collection application. A detailed overview of the main challenges identified as well as a brief description of their implications and solutions are presented in Table 1.
In this study, we suggest simple, cost-effective, and off-the-shelf solutions to improve user compliance, data quality, and data completeness in population studies employing wearable sensors and provide the relevant protocols. In addition, we demonstrate the data completeness improvements from the implementation of such protocols using representative results from the study13.
Administrative and ethics approvals were obtained from the Cyprus Ministry of Health (YY5.34.01.7.6E) and the Cyprus National Bioethics Committee (ΕΕΒΚ/ΕΠ/2016.01.23). Patients with atrial fibrillation and the guardians of the asthmatic children provided written informed consent prior to participation in the study.
1. Application lockers and device automation applications
NOTE: Freely available application lockers and device automation applications (taskers) can be found for both Android devices and IOS devices. The specific applications used in the present study are listed in the Table of Materials.
2. Development of the automated procedures using the tasker
NOTE: A tasker allows for the step-by-step development of automated processes. These can vary according to the requirements of the project. Previous coding or programming experience is not required. In the following steps, the following terms and definitions are used: trigger (a starting state that, when met, allows the tasker to initiate the process), condition (a condition that, when met, allows the process to continue to the next step), and action (the process outcome). In the provided figures, the parallelogram denotes a trigger, the diamond denotes a condition, and the rectangle denotes an action. Each process may result in more than one action, and these are labeled as actions a, b, c, (...) under each process. A separate process was set up for each individual problem identified during the field implementation of the project. This approach ensured there was no overlap between the conditions set and allowed the smooth operation of the automated process as a whole.
3. Exporting the created processes (steps 2.1-2.6)
4. Transferring and installing the files created to the smartwatch
5. Setting up the smartwatch for field use
The protocol describes simple and cost-effective solutions to real-life challenges affecting recruitment, compliance, and data quality in population studies employing wearable sensors. The steps described here allowed for the successful setup of a consumer wearable device for exposure and health monitoring in a large population study involving children with asthma and adults with atrial fibrillation. Figure 6 provides a graphical overview of the provided protocols and illustrates the key ste...
Wearable sensors are useful tools that allow the continuous and non-invasive monitoring of health parameters and patient behavior. Commercial smartwatches, which are equipped with a variety of sensors, provide a promising alternative to traditional data collection methods, and their use in clinical and public health research is only expected to rise as a result of increased variety and quality of built-in sensors, stronger academic-industry partnerships, and reductions in retail prices14. In this ...
The authors have no conflicts of interest to declare.
The authors are grateful to all the participants and their families, as well as to the teaching and administrative personnel of the participating primary schools in Cyprus and Greece. The study was financed by the European Union LIFE Project MEDEA (LIFE16 CCA/CY/000041).
Name | Company | Catalog Number | Comments |
APK Extractor | Meher | Version 4.21.08 | Application |
Charger/Adaptor with data cable | Jiangsu Chenyang Electron Co. Ltd | C-P17 | Charger |
Embrace application | EmbraceTech LTD | Version 1.5.4 | Application |
LEMFO LF25 Smartwatch | Shenzhen domino Times Technology Co. Ltd | DM368 Plus | Smartwatch |
Lock App - Smart App Locker | ANUJ TENANI | Version 4.0 | Application |
Macrodroid-Device Automation | ArloSoft | Version 5.5.2 | Application |
Xiaomi Redmi 6A | Xiaomi | M1804C3CG | Smartphone |
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