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.