Introduction
Back pain is one of the most common health problems, and an estimated
one-third of adults in the UK are affected each year. One condition that
causes chronic back pain is axial spondylarthritis (axSpA). This chronic
inflammatory disease primarily affects spinal joints, resulting in pain
and joint stiffness symptoms and altered posture. AxSpA affects
approximately 5 in 1,000 adults in the UK and is a condition that
encompasses both people with ankylosing spondylitis (AS), defined by
radiographic evidence of structural changes, and people with
non-radiographic axial spondyloarthritis. Inflammation of the axial
spine results in a clinical presentation of pain and reduced spinal
mobility which is often misdiagnosed or overlooked. Symptoms of axSpA
first present as inflammatory back pain in people during the third
decade of life, impacting on work, family and social commitments causing
both economic and humanistic burden. The clinical presentation requires
both drug and non-drug management with regular follow-up to optimise
therapy.
To clinically identify the pattern and severity of reduced joint
mobility, multiple tools have been developed to objectively assess these
restrictions in the axSpA population. The most common non-radiographic
clinical assessment tool is the Bath Ankylosing Spondylitis Metrology
Index (BASMI), an index of five simple clinical measurements to assess
the axial status. The Edmonton Ankylosing Spondylitis Metrology Index
(EDASMI) is an index of four similar clinical measurements that was
developed to be more responsive to change than the BASMI yet is less
widely used. In further effort to increase measurement precision of the
clinician-administered BASMI and EDASMI, the University of Cordoba
Ankylosing Spondylitis Metrology Index (UCOASMI) was developed to
measure by automated motion capture using four cameras and 33 reflective
markers placed on anatomical landmarks. More recently, inertial
measurement unit (IMU) sensor-based systems have been employed to
measure spinal mobility using five IMUs attached along the spine.
These tools and methods described require either a clinician for
measurement or specialised equipment, e.g., motion capture system or
IMUs and analytic expertise. Therefore, usability and acceptability are
a limitation that may prevent regular monitoring. More remote systems,
for example, markerless pose estimation using computer-vision, have
evolved with the potential to be used directly by patients to enhance
telerehabilitation. Computer-vision (CV) is a branch of artificial
intelligence that can be used to automate analysis of human movement
analysis from videos. By using CV-aided methods to analyse specific
functional movements captured on video, both clinicians and patients can
have access to a powerful tool that could bridge the gap between the
clinic and home. In addition to functional movement, postural deficits
are present in people with axSpA; therefore, monitoring posture with a
remote system using a surface topography tool could be important and
valuable. This CV-aided system may also have the potential to be a more
cost-effective method to evaluate and monitor people with axSpA compared
to an in-person clinician assessment. Remote and automated monitoring
technology has the potential to work alongside the clinical team by
identifying when there have been significant changes in joint mobility
and posture. Therefore, reducing clinician time and decreasing
unnecessary traveling, reducing health system pressures while at the
same time creating the opportunity for more frequent access and greater
accessibility to better management.
This study aimed to estimate the criterion validity of functional
movement and posture measurement using remote technology systems in
people with and without axSpA by comparing them to measurements
performed by a trained clinician. The secondary aims were to determine
the systems’ accuracy as a potential measure of functional activity, to
understand the feasibility of implementing remote technology systems in
the laboratory and home environments, and to estimate the cost
consequences of the remote technology systems compared to a face-to-face
clinical visit.