capturing key mg-symptoms using smartphone recordings.

Conditions: Myasthenia Gravis; Fatigue

Summary: this study will make use of a cross-sectional design of mg patients and non-mg participants to quantitatively assess key mg symptoms, and to explore the applicability of machine learning algorithms to their measurement.

due to the cross-sectional design, participants will only have to visit leiden university medical center (lumc) once. for patients already treated in the lumc, we will try to align this visit with a standard clinical appointment. after inclusion, all baseline data, consisting of demographics, clinical history and a number of questionnaires (four for mg participants, three for non-mg participants), will be collected. the symptom-specific assessments are performed in a standard order, with the most fatiguing task (i.e. proximal arm fatigue static assessment) last. we estimate the visit will take a total of 60 minutes. this study is considered to be low risk. withholding pyridostigmine for a limited period is part of standard care of mg (before investigations or clinical assessments) and does not affect long term clinical outcome. mg participants will consent to withhold pyridostigmine for 12 hours prior to the study visit if they are on this treatment and restart it after the visit. as this is a non-interventional, observational study where only questionnaire-based and non-contact digital data are being collected, the only source of marginal risk relates to data protection and confidentiality, including arrangements for the transfer and storage of data. given it would not be possible to deidentify the digital audio or video data while maintaining the requisite integrity for data analysis, we will seek explicit consent for the sharing of this information in this identifiable format.

Eligibility criteria:
inclusion criteria: 1. age ≥ 18 years 2. ability to understand the requirements of the study and provide written informed consent. inclusion criteria for mg participants only: 1. a clinical diagnosis of myasthenia gravis (ocular or generalized) with the typical fluctuating muscle weakness and at least one of the following: * a positive serologic test for achr or musk antibodies; * an abnormal electrodiagnostic test: repetitive nerve stimulation (rns) or single-fiber electromyography (sfemg). 2. mgfa clinical classification of disease severity i-iv. 3. subjects have at least one of the symptoms of interest (namely dysarthria, dysphonia, proximal arm fatigue and/or ptosis). inclusion criteria for non-mg participants only 1. subjects are not diagnosed with and have no clinical suspicion of mg. 2. subjects do not have a medical history of any of the symptoms of interest (namely dysarthria, dysphonia, proximal arm fatigue and/or ptosis). exclusion criteria: 1. not willing to be audio-recorded for the study assessments. 2. not willing to be video-recorded for the study assessments. 3. subjects currently taking part in a clinical trial of an investigational medicinal product. 4. subjects who have used an immediate release pyridostigmine-based medication in the 12 hours prior to their participation and participants on prolonged release pyridostigmine. 5. subjects have cognitive or physical limitations that, in the opinion of the investigator, limits the subject's ability to complete study procedures/ exclusion criteria for mg participants only: 1. subjects with an upper-limb amputation or who are non-verbal. 2. subjects with a diagnosed neurological disease resulting in muscle weakness, other than mg. exclusion criteria for non-mg participants only: 1. limitation of upper limb mobility or speech impairment of any cause.

Keywords: myasthenia gravis fatigue digital features machine learning algorithms dysarthria dysphonia proximal arm fatigue ptosis