Instrumentation & Measurement Magazine 24-6 - 72

Scalability of Systems and Data Management
Systems designed to manage and collect data from homebased
passive and wearable sensors should be developed with
the concept of flexibility in mind. The architecture of the data
processing and storage system needs to be scalable and employ
standardized data structures that will remain compatible
and up to date with ongoing advancements in hardware and
software technology. This is essential to integrate and support
new sensors and remain relevant as new technology is inevitably
developed. System flexibility also allows for data collection
on multiple different physical and health-related domains so
that a system is not necessarily restricted to one area, such as
aging in place. Different sensors using the same backend data
collection system could be employed to assess changes in relevant
health domains for many different diseases and patient
populations. The ability to incorporate and support new sensors
is essential for systems to remain relevant and further
reinforces the need for standardized methods to validate digital
biomarkers derived from sensor data. The CART platform
was designed to allow the incorporation of multiple different
devices and sensor types using software that is agnostic
to the hardware. This was achieved in part with the development
of an abstraction layer that supports data collection
through multiple different standard wireless communication
protocols (Bluetooth, ZigBee, Wi-Fi) to allow incorporation of
varied new sensor types [30]. For many of the new sensors and
technologies incorporated into the CART platform, testing in a
smaller sample of participants prior to deployment in the entire
set of homes was performed to review sensor performance
and the reliability of the collected data. The CART platform
backend is currently maintained at the Oregon Health and Science
University's Advanced Computing Center; however, it
was designed to be able to run on a cloud provider if desired.
Standards for Data Collection and Security
Standards for digital technology will not only need to address
the accuracy and validity of sensor-derived data but also the
methods for data management and storage. The CART platform
has employed standardized schemas to store data that
help to streamline data sharing with other researchers. When
possible (e.g., steps recorded by a wearable) the CART platform
utilized Open mHealth (https://www.openmhealth.
org/) schemas for serializing data. mHealth encompasses the
use of mobile and wireless technologies that support medicine
and public health objectives. However, many data streams
available from the CART platform (e.g., PIR motion sensor
data) do not have pre-determined schemas available in Open
mHealth and needed to be designed by the CART team. With
more importance now being placed on transparency and data
sharing and the large amounts of data produced by high-frequency
data collection, having standards in place can help
facilitate collaboration. This will improve the efficiency of
research that involves digital technology and allow for potential
downstream uses of the data collected. The development
of these standards will require input and agreement from researchers,
industry, and regulatory bodies to gain widespread
72
acceptance and implementation. The Clinical Trials Transformation
Initiative (CTTI) is an example of a public-private
partnership that has created a set of recommendations and
resources to help improve the use of mobile technology in clinical
trials ((http://feasibility-studies.ctti-clinicaltrials.org) [1],
with a goal to improve trial quality and efficiency. This builds
upon a framework issued by the US Food and Drug Administration
(FDA) about the use of digital technologies specifically
in clinical trials (https://www.fda.gov/NewsEvents/Newsroom/FDAInBrief/ucm626166.htm).
Additional
safeguards need to be considered when dealing
with participants who may have cognitive impairment which
may impact their insight and judgment. This may include
training about safe computer and internet usage and ensuring
privacy and security safeguards are in place related to any
usage or interaction with technology. For all participants, systems
using digital technologies require reliable and secure
methods for the collection, transfer, and storage of participant
data. Statutes and regulations currently in place encompass
methods for data usage and collection using digital technology
within the FDA regulations on Good Clinical Practices.
Home-based sensor platforms require methods to ensure that
software and hardware associated with sensors and system
components are regularly updated to avoid potential security
breaches. The CART platform was developed to ensure
data security during transfer and storage. Modifications to the
operating systems and configurations were monitored and
reverted with the latest security patches installed on a daily
basis. An encrypted VPN was implemented to ensure all data
leaving the hub was encrypted while in transit and a Federal
Information Processing Standard (FIPS) compliant encryption
module was used to encrypt data while at rest on the servers.
Data integrity in transit was maintained through the use of
message digests.
Technical Issues with Sensors and the Data
Acquisition and Management System
Technical issues that arose with the development of the CART
platform were generally associated with the integration of
new technologies into the platform. Ensuring reliable data collection
requires sensors that are functioning correctly and the
knowledge that sensor data is being collected, transferred, and
stored. The ability to deploy the platform in hundreds or thousands
of homes requires this process to be automated. For the
CART platform, a weekly home data report program was created
that reviews the functional status of each sensor in a home
and the data being collected by these sensors. A weekly report
is generated for each home, providing technical staff with
early identification of problems that arise that could otherwise
result in loss of data (Fig. 3).
Collaboration outside of a single site requires consideration
of technical issues that arise with deployment of the
sensor platform in different locations. The time stamp associated
with sensor data provides accurate knowledge of exactly
when an event occurred. However, when the data storage and
management servers are located in one region, there must be
IEEE Instrumentation & Measurement Magazine
September 2021
http://feasibility-studies.ctti-clinicaltrials.org https://www.fda.gov/NewsEvents/Newsroom/FDAInBrief/ucm626166.htm https://www.fda.gov/NewsEvents/Newsroom/FDAInBrief/ucm626166.htm https://www.openmhealth.org/ https://www.openmhealth.org/
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