Feasibility, Validation and Application of Digital Tools for the Follow-up of Neuromuscular Patient Mobility in Daily Living

Brief Summary

The low prevalence of rare diseases hinders the design of clinical studies with sufficient statistical power to demonstrate the efficacy of new drugs. This can only be achieved by setting up international multicentre studies, which is challenging due to a lack of objective, universal outcome measures that generate high-quality, reproducible data. One of the hurdles in attaining universal outcome measures for clinical trials is the difficulty to capture and distinguish ambulatory from non-ambulatory, autonomous and assistive or involuntary movements. This makes a trial assessing the ambulatory phase very challenging at this moment. Excluding many participants from trials and many patients from access to medication. Integration and validation of the technology in trials, research and patients' lives is essential in overcoming this hurdle. For example, in dystrophinopathies separate outcome measures exist for ambulant and non-ambulant participants, but the relation between these outcome measures or a transitional outcome measure/end point is largely missing. Following an exhaustive literature review, several tools have been selected to remotely follow various symptoms of neuromuscular patients including weakness, pain, fatigue, cognitive defects, motor impairments (including loss of dexterity, ataxia...), metabolic, respiratory and cardiac troubles, contractures, tremor, falls, hypo or hypersomnia... The toolbox includes common measures for all patients but may include additional measures specific to the patient's symptoms (hence in turn to the patients' disease). The measurements are designed to not be invasive, intrusive or burdensome for the patient. DT4RD is going to leverage state-of-the art technology, clinical rating scales and psychometric/data analysis to deliver fit for purpose remote clinical assessments of mobility to ensure maximum patient benefit, specifically: * Compare face to face clinical data collected in hospital with Patient Generated Data recorded remotely * Examine how sensors can enhance measurement potentially at home and during clinical visits * Promote a clear focus on user centered design and the integration of technology * Use reliability and validity analyses to equate any common measures (those with the same or a similar construct) * Demonstrate a proof-of-concept model into which different measures can be interchangeable

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