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Using everyday devices to measure axial spondyloarthritis

Investigating computer vision and wearable-based measurement of disease metrics in axial spondyloarthritis

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ISRCTN
Registry ID
ISRCTN13250379
Enrollment
30
Registered
2026-07-29
Start date
2026-08-03
Completion date
Unknown
Last updated
2026-08-10

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Axial spondyloarthritis Musculoskeletal Diseases

Interventions

Participants are adults with axial spondyloarthritis attending the residential self-management course at the Royal National Hospital for Rheumatic Diseases (Royal United Hospital, Bath). Nothing is ad
the study observes them while they undergo assessments already part of the course, plus two brief additions. At three time points — course entry (day 1), midpoint (day 5) and course exit (day 10) — e
all contain inertial measurement units recording acceleration and orientation (all devices' audio and microphone functions are not used). Two tripod-mounted iPhones record video from two angles so a p
the sock and floor tasks are repeated three times. The PI times ea

Sponsors

University of Bath
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 999 Years

Inclusion criteria

Inclusion criteria: 1. Adults aged 18 years and over 2. Diagnosed with axial spondyloarthritis 3. Attending a residential self-management programme at the Royal National Hospital for Rheumatic Diseases 4. Have the capacity for providing informed consent for participation 5. Sufficient communicative ability to participate in the research, and follow verbal or written instructions for the study procedures (must be able to communicate in English)

Exclusion criteria

Exclusion criteria: 1. Those who would be unable to perform study procedures without psychological or physical discomfort, beyond that which they would experience on the self-management course 2. Previous spinal surgery 3. Significant degenerative spinal disease 4. Vertebral fractures 5. Known malignancy 6. Total spinal ankylosis

Design outcomes

Primary

MeasureTime frame
Level of agreement between machine-learning estimates (from wearable and/or vision data) and clinically measured BASMI, BASFI and ASPI measured using Bland–Altman analysis (bias and 95% limits of agreement) at day 1, 5, and 10 of the RNHRD AxSpA self management course

Countries

England, United Kingdom

Contacts

Public ContactGregory;Christopher Knowles;Clarke

;

grk24@bath.ac.uk;cjc234@bath.ac.uk+44 (0)1225 388388;+44 (0)1225 388388

Outcome results

None listed

Source: ISRCTN (via WHO ICTRP) · Data processed: Aug 25, 2026