Multimodal digital assessment for myasthenia gravis.
Construction of A Multimodal Digital Assessment Model for Myasthenia Gravis
This project will try a multimodal digital system using facial and eye-movement videos, speech and limb motion recordings, and physiological sensors to see if it can measure symptom severity in adults with myasthenia gravis.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 180 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Huashan Hospital Academic / other |
| Locations | 1 site (Shanghai) |
| Trial ID | NCT07146425 on ClinicalTrials.gov |
What this trial studies
This single-center, exploratory observational study at Huashan Hospital (Fudan University) will collect synchronized multimodal digital phenotypic data from adults with myasthenia gravis and matched healthy controls. Data collected will include physiological signals, facial and eye-movement videos, speech and limb movement recordings, clinical scales, and quality-of-life measures. Researchers will use descriptive subgroup analyses and machine learning to identify features linked to MG severity, then build and prospectively validate a digital evaluation model. The team will also develop a patient-facing remote evaluation system based on the model to support diagnosis, monitoring, and rehabilitation in real-world settings.
Who should consider this trial
Good fit: Ideal participants are adults (≥18) with a confirmed MG diagnosis (MGFA class I–IV or asymptomatic after treatment) who can provide consent and cooperate with digital testing, plus age-matched healthy volunteers as controls.
Not a fit: Patients in myasthenic crisis (MGFA V), those with severe cardiopulmonary disease, significant psychiatric or cognitive impairment, or other unstable medical conditions are excluded and unlikely to benefit from participation.
Why it matters
Potential benefit: If successful, the model could provide an objective, precise, and remote way to track MG symptoms and treatment response, improving clinical decision-making and patient self-monitoring.
How similar studies have performed: Multimodal digital phenotyping and AI-derived models have shown promise in other neurological disorders, but applying a comprehensive multimodal digital model specifically to myasthenia gravis is relatively novel and remains exploratory.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: For Patients with MG * Patients have a confirmed diagnosis of myasthenia gravis and be over 18 years old. * Patients have the clinical classification of Myasthenia Gravis Foundation of America (MGFA) within I-IV, or be asymptomatic after treatment. * Patients must sign the informed consent form and the privacy confidentiality agreement. For Healthy Participants * Age group matched with MG participants Exclusion Criteria: For Patients with MG * Patients are in the crisis stage of myasthenia gravis (MGFA class V) and unable to cooperate with scoring. * Patients are with severe cardiopulmonary diseases and unable to cooperate with the scoring. * Patients with any psychiatric disorder or cognitive dysfunction that, in the investigator's judgment, may interfere with their participation in the study. * Patients with any other unspecified unstable medical condition.
Where this trial is running
Shanghai
- Huashan Hospital, affiliated to Fudan University — Shanghai, China (Recruiting)
Study contacts
- Principal investigator: Chongbo Zhao, Ph.D. — Huashan Hospital
- Study coordinator: Yanan Miao, Ph.D.
- Email: himed@fudan.edu.cn
- Phone: 0086-021-52888780
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.