Name: setup of consumer wearable devices for exposure and health monitoring in population studies
Uploaded: 2023-02-03T12:30:00
Description: Watch this Scientific Journal Video about Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies at JoVE.com

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).

Administrative and ethics approvals were obtained from the Cyprus Ministry of Health (YY5.34.01.7.6E) and the Cyprus National Bioethics Committee (&#917;&#917;&#914;&#922;/&#917;&#928;/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 dev...

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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 ...

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 &#34;at home&#34; 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.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>APK Extractor</td>
			<td>Meher</td>
			<td>Version 4.21.08</td>
			<td>Application</td>
		</tr>
		<tr>
			<td>Charger/Adaptor with data cable</td>
			<td>Jiangsu Chenyang Electron Co. Ltd</td>
			<td>C-P17</td>
			<td>Charger</td>
		</tr>
		<tr>
			<td>Embrace application</td>
			<td>EmbraceTech LTD</td>
			<td>Version 1.5.4</td>
			<td>Application</td>
		</tr>
		<tr>
			<td>LEMFO LF25 Smartwatch</td>
			<td>Shenzhen domino Times Technology Co. Ltd</td>
			<td>DM368 Plus</td>
			<td>Smartwatch</td>
		</tr>
		<tr>
			<td>Lock App - Smart App Locker</td>
			<td>ANUJ TENANI</td>
			<td>Version 4.0</td>
			<td>Application</td>
		</tr>
		<tr>
			<td>Macrodroid-Device Automation</td>
			<td>ArloSoft</td>
			<td>Version 5.5.2</td>
			<td>Application</td>
		</tr>
		<tr>
			<td>Xiaomi Redmi 6A</td>
			<td>Xiaomi</td>
			<td>M1804C3CG</td>
			<td>Smartphone</td>
		</tr>
	</tbody>
</table>

setup of consumer wearable devices for exposure and health monitoring in population studies

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.

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...

Watch this Scientific Journal Video about Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies at JoVE.com

Setup of Consumer Wearable Devices for Exposure and Health Monitoring in Population Studies

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 ...

The aim of this video is to provide our experience from deploying wearable sensors embedded in commercial smartwatches for the proposals of the live media project, a population study focusing on the mitigation of health effect. The project involved two distinct population groups patient with atrial fibrillation, asthmatic children aged six to 11 years old for the assessment of their physical activity and their personal location. Both groups were equipped with a commercial smartwatch.The participants were required to wear the smartwatch daily and data were transmitted over their home's wireless network to a collection platform for almost realtime assessment of compliance and data quality. In this video, we displayed a simple, cost-effective and off-the-shelf solutions that we implemented in the field to improve user compliance, data quality, and data completeness. In addition, we showcased data completeness improvements from of such protocols using the representative results from the live media study.Launch the device automation application and navigate to the interface complete tasks. Add a macro or a task by clicking the plus sign. Click the plus sign on the trigger tab.Select Date and Time. Select the Regular Interval tab. Don't use the reference time.Set the regular interval. Set the fixed time interval to act as a trigger to initiate the procedure. Click OK.To add an action, click the plus sign on the action tab.Select the Conditions/Loops tab. Select close. Add a condition by clicking the plus sign.Select the Date/Time tab. Select Stopwatch. Click OK.Set a fixed duration to be added as a condition.As part of the procedure, the condition being tested is whether a stopwatch is either more than 29 minutes, or less than one second. The former reflects our preference to systematically activate the data collection application at least every 30 minutes. And the latter represents a case that the stopwatch is not working or has stopped.Change the end by clicking on the triangle. Select Or.Whenever one of the condition is met, the process can continue. To add an action between the statement, click on the End If.Select Add Action above.Navigate and find the Screen tab. Select the Action Screen On and click OK.When the conditions are met the tasker will enable the screen. Following similar steps at the second action that reduces the brightness of the screen to the lowest percentage.Add an additional action that resets and restarts the stopwatch that is being used in this automated process. This creates a loop. Follow similar steps and add an action that enables collection application.Select Applications. Select Launch Applications. Find and select the Data Collection application.Select Force new and click OK.Our process is complete. The trigger, the conditions, and the actions are set. Give a name to this process and select SAVE.Create a process that systematically enables the wifi of the smartwatch. Add a trigger to create a start point for the process. Select Device Events and select Screen On off.Select Screen On and click OK.Add an action by clicking the plus sign on the Action tab. Select the Conditions/Loops tab. Select the close.Add a condition by clicking the plus sign. Select the Connectivity tab. select Wifi State and choose Wifi Disabled.Click OK.Select OK.Click on the End If.Select Add Actionable. Select the Connectivity tab. Click on the Wifi Configured tab.Select Enable Wifi and click OK.Upon screen activation, and if the condition is met, the process activates the wifi. Add an additional action between the If statement that resets and restarts Stopwatch Two. This stopwatch is important for disabling the wifi after a few minutes.An action that is carried out by a different process in the protocol. Give a name to this process and select SAVE. Create a process that systematically locks event information.Click the plus sign on the Trigger tab. Select Date and Time. Select the regular interval.Don't use the reference time. Set the interval at five minutes and click OK.To add an action, click the plus sign On the action tab. Select Logging.Click on Log Event. Click the Ellipses Points tab. Find and select Wifi SSID.Select OK.By clicking again on the Ellipses Point tab and following the exact same steps, you can further add Wifi signal strength, device serial number, GPS coordinates, accuracy of GPS signal, as well as whether the smartwatch is charging or not. This action creates a log event with pre-specified variables relevant to the project. Give a name to this process and select SAVE.Before the smartwatch is given to a participant several important settings must be modified. Swipe the smartwatch screen to the left and navigate to the smartwatch settings function. Click on Settings.Select Sound, and disable all sounds by minimizing the volume levels of all individual settings. Swipe the screen to the right to return to the main setting screen. Scroll down and select the Connect function.Select GPS. Click on mode and set the GPS setting to high accuracy. Swipe the screen to the right to return to the main setting screen.Scroll down and select power saving function. Deactivate Standby intelligent power setting, and check that the battery saver is always turned off. Swipe the screen to the right to return to the main setting screen.Scroll down and select Date Time function. Disable the Automatic time zone tab. Scroll down and click on Select time zone and select the correct time zone and enable the 24-hour format.Scroll up and enable the Automatic time zone and check that the Automatic date time mode is set to use network-provided time. Swipe the screen to the right to return to the main setting screen. Scroll down and select More.Open the option Background Cleaner and disable the Battery Saver. Swipe the screen to the right to return to the More settings screen. Scroll down and select App Freeze.Click on Next. Scroll down and click on Google Play Store. Select Freeze.The app will automatically disable. Swipe the screen to the right to return to the More setting screen. Select Notifications.Select Google and block all notifications from this app. Depending on the device and operating system, other applications may also pop up notifications. Swipe the screen to the right to return to the More setting screen.Scroll down and select Data save. Disable the Data save. Swipe the screen to the right to return to the More setting screen.Select App settings. Scroll down and select Special access. Click on Battery optimization setting.Click on the triangle and select All apps. Scroll down and find the application locker and select Don't optimize. Find all relevant apps that are used in the smartwatch setup and select Don't optimize.The main applications that perform or support a must operate without any battery restrictions. After you finish with the setup, perform a check up of the settings that we have done in this step. Check again that you have minimized all sounds and vibrations, that the GPS mode is in high accuracy.Date and time settings are correct, and furthermore, make sure to disable any settings that interfere with the smooth operation of the apps in the background. Additionally, make sure that you have freezed any apps that may perform updates. Make sure that the main applications that perform or support a are operating without any battery restrictions.Participants were given specific instructions to charge the smartwatch every night and wear it during the day. The configuration of the device displayed in the protocol in combination with the automated procedures developed with the tasker, minimize any extra hassle for the participant. Here we provide exemplary results from a total of 17 participants from the asthma panel during spring 2020.The participants were equipped with the smartwatch and providing data two weeks before and after protocol implementation. Figure 7A presents a percentage of time with data for each participant separately, while Figure 7B presents the corresponding distributions of percentage of time with data for the whole group. An increase in percentage of time with data was observed.Protocol implementation led to a statistically significant increase in data completeness of approximately 15%Furthermore, Figure 8 and Figure 9 presents two different dates from a single AF patient participating in the live media study in spring 2020. Figure 8A and 9A presents the actual raw GPS signals. In Figure 8B and 9B, we have the implementation of the GPS data filling algorithm that allows replacing missing data with estimated values.Figure 8C and 9C present signals from the smartwatch connectivity with the Wi-Fi network. The algorithm performed reasonably well in Figure 8A compared with the network signals in 8C. However, in Figure 9, the algorithm alone did not accurately estimate all missing data, as it failed to capture that the participant also returned home for a period of about 90 minutes.The inclusion of a Wi-Fi connecting signal, as collected by the tasker application, can significantly prove the performance of the algorithm and minimize misclassification. This protocol was employed in spring 2020 and was used to set up smartwatches that were given to asthmatic children enrolled in the live media project. As a result, the children were equipped with the smartwatches during the first wave of the COVID 19 pandemic and this gave us the opportunity to objectively assess their compliance to COVID 19 lockdown measures.The results of that work were published previously Scientific Reports General and demonstrated that with escalating lockdown measures children increase their daily fraction of time spent at home and reduced their physical activity in both countries. In summary, this work provides a protocol which includes simple and cost-effective solutions to real life challenges in population studies employing consumer wearable devices. This approach can be easily replicated or adapted by researchers working with wearable devices in the fields of clinical research and public health.

Research

JoVE Journal

Bioengineering

Simple Microfluidic Devices for in vivo Imaging of C. elegans, Drosophila and Zebrafish

Simple Microfluidic Devices for in vivo Imaging of C. elegans, Drosophila and Zebrafish

Micro fabricated fluidic devices provide an accessible micro-environment for in vivo studies on small organisms. Simple fabrication processes are ...

Mass Cytometry: Protocol for Daily Tuning and Running Cell Samples on a CyTOF Mass Cytometer

In recent years, the rapid analysis of single cells has commonly been performed using flow cytometry and fluorescently-labeled antibodies. However, the ...

Millifluidics for Chemical Synthesis and Time-resolved Mechanistic Studies

Procedures utilizing millifluidic devices for chemical synthesis and time-resolved mechanistic studies are described by taking three examples. In the ...

Paper-based Devices for Isolation and Characterization of Extracellular Vesicles

Extracellular vesicles (EVs), membranous particles released from various types of cells, hold a great potential for clinical applications. They contain ...

Layer-by-layer Collagen Deposition in Microfluidic Devices for Microtissue Stabilization

Although microfluidics provides exquisite control of the cellular microenvironment, culturing cells within microfluidic devices can be challenging. 3D ...

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Recent advances in modular DNA assembly techniques have enabled synthetic biologists to test significantly more of the available &#34;design space&#34; ...

Polydimethylsiloxane-polycarbonate Microfluidic Devices for Cell Migration Studies Under Perpendicular Chemical and Oxygen Gradients

This paper reports a microfluidic device made of polydimethylsiloxane (PDMS) with an embedded polycarbonate (PC) thin film to study cell migration under ...

Construction and Setup of a Bench-scale Algal Photosynthetic Bioreactor with Temperature, Light, and pH Monitoring for Kinetic Growth Tests

The optimal design and operation of photosynthetic bioreactors (PBRs) for microalgal cultivation is essential for improving the environmental and economic ...

Advanced 3D Liver Models for In vitro Genotoxicity Testing Following Long-Term Nanomaterial Exposure

Due to the rapid development and implementation of a diverse array of engineered nanomaterials (ENM), exposure to ENM is inevitable and the development of ...

Electric-Field-Induced Neural Precursor Cell Differentiation in Microfluidic Devices

Physiological electric fields (EF) play vital roles in cell migration, differentiation, division, and death. This paper describes a microfluidic cell ...