Feasibility of video-based joint hypermobility assessment in individuals with suspected Ehlers-Danlos syndromes/generalised hypermobility spectrum disorders: a single-site observational study protocol

Introduction Ehlers-Danlos syndromes (EDS)/generalised hypermobility spectrum disorders (G-HSD) affect the connective tissue of the body and present with a heterogeneous set of symptoms that pose a challenge for diagnosis. One of the main diagnostic criteria of EDS/G-HSD is generalised joint hypermobility, which is currently assessed by clinicians during a physical exam. However, the practice for measuring joint hypermobility is inconsistent between clinicians, leading to high inter-rater variability. Often patients are misdiagnosed with EDS/G-HSD based on an incorrect hypermobility assessment, leading to increased referral rates and resource utilisation at specialised EDS clinics that results in unnecessary emotional distress for patients. An objective, validated and scalable method for assessing hypermobility might mitigate these issues and result in improved EDS/G-HSD patient care.Methods and analysis This study will examine the use of videos obtained using a smartphone camera to assess the range of motion (ROM) and hypermobility of the joints assessed in Beighton score and more (spine, shoulders, elbows, knees, ankles, thumbs and fifth fingers) in individuals with suspected EDS/G-HSD. Short videos of participants will be captured as they undergo a formal assessment of joint hypermobility at the GoodHope EDS Clinic at Toronto General Hospital. Clinicians will measure the ROM at each joint using a clinical-grade goniometer to establish ground truth measurements. Open-source human pose-estimation libraries will be used to extract the locations of key joints from the videos. Deterministic and machine learning systems will be developed and evaluated for estimating the ROM at each joint. Results will be analysed separately for each joint and human pose-estimation library.Ethics and dissemination This study was approved by the Research Ethics Board of the University Health Network in Toronto on 26 April 2022. Participants will provide written informed consent. Findings from this study will be published in peer-reviewed journals and presented at conferences.

Automated summary

This study aims to use videos captured by a smartphone camera to assess the range of motion and hypermobility in individuals suspected of having EDS/G-HSD. The locations of key joints will be extracted from the videos using open-source human pose-estimation libraries. Deterministic and machine learning systems will be developed and evaluated for estimating the ROM at each joint.