Ehlers Danlos Syndrome (EDS) is a heterogenous group of genetic disorders with 13 identified subtypes. Hypermobile EDS (hEDS), although the most common subtype of EDS, does not yet have an identified genetic mutation for diagnostic confirmation. Generalized joint hypermobility (GJH) is one of the hallmark features of hEDS. The scoring system used in measurement of GJH was described by Beighton. The Beighton score is calculated using a dichotomous scoring system to assess the extensibility of nine joints. Each joint is scored as either hypermobile (score = 1) or not hypermobile (score = 0). The total score (Beighton score) can vary between a minimum of 0 and a maximum of 9, with higher scores indicating greater joint laxity.

While there is moderate validity and inter-rater variability in using the Beighton score, there continue to be several challenges with its widespread and consistent application by clinicians. Some of the barriers reported in the literature include:

i) In open, non-standardized systems there can be significant variation in the method to perform these joint extensibility tests including assessing baseline measurements, ii) Determining consistent and standard measurement tools/methodology e.g. goniometer use can vary widely iii) Assessing the reliability of the cut off values and, iv) Performing full assessment prior to informing patients of possible classification of GJH positivity (low specificity and low positive predictive).

Inappropriate implementation of tests to assess GJH results in inaccurate identification of GJH and potentially unintended negative consequences of making the wrong diagnosis of EDS. The objective of this study is to create a more robust and valid method of joint mobility measurement and reduce error in the screening of EDS through use of a smartphone-based machine learning application systems for measurement of joint extensibility.

The project will:

i) Create a smart-phone enabled visual imaging app to assess the measurement of joint extensibility, ii) Assess the feasibility of using the smart-phone app in a clinical setting to screen potential EDS patients, iii) Determine the validity of the application in comparison to in person clinical assessment in a tertiary care academic EDS program. If successful, the smart-phone application could help standardize the care of potential EDS patients in an efficient and cost-effective manner.

Inclusion Criteria:

• All patients seen in the GoodHope EDS clinic at Toronto General are eligible for inclusion, regardless of their presenting diagnosis or the results of their assessments

Exclusion Criteria:

• Patients who do not consent to participate will not be included (participants may withdraw consent at any time)

The population being studied includes all patients referred to or seen in the GoodHope EDS clinic. The clinic accepts referrals from symptomatic adult patients (age > 18 years), with EDS, or suspected EDS. EDS is a connective tissue disorder with 100% penetrance, but variable in phenotypic expression, suspected cases of EDS or G-HSD may therefore include other hereditary or acquired connective tissue diseases/disorder, and/or complex chronic illnesses characterized by, or that feature, joint hypermobility, pain, and fatigue.

No IPD will be shared with other researchers.