Detecting Fatigue From Voice in Generalised Myasthenia Gravis (NCT07033559) | Clinical Trial Compass
Not Yet RecruitingNot Applicable
Detecting Fatigue From Voice in Generalised Myasthenia Gravis
240 participantsStarted 2026-02
Plain-language summary
The goal of this observational study is to learn if computer analysis of voice recordings can detect a type of exhaustion called "central fatigue" in adults with generalised myasthenia gravis.
The main questions it aims to answer are:
1. Can advanced voice analysis accurately tell when participants are experiencing deep exhaustion based on how they speak?
2. How easy and acceptable is voice-based fatigue monitoring for people with myasthenia gravis?
Participants will:
1. Record themselves reading short passages and answering questions out loud twice daily (morning and evening), twice a week, for 4 weeks.
2. Answer brief questionnaires about their energy levels, mood, and myasthenia gravis symptoms during each session.
3. Use their own devices (computer, tablet, or smartphone) to complete all study activities online from home.
Who can participate
Age range
18 Years
Sex
ALL
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Inclusion Criteria:
* Adults ≥18 years old
* Self-reported generalised Myasthenia Gravis diagnosis confirmed by healthcare provider for ≥6 months
* Disease stability for ≥6 months (no hospitalisations, medication changes, or significant symptom worsening)
* English as first language
* Residence in US or UK
* Vision adequate for screen reading (with aid or correction if necessary)
* Access to internet-connected device with compatible browser and microphone
* Adequate internet connectivity (≥5 Mbps download, ≥3 Mbps upload)
* Ability to complete twice-daily assessments during specified time windows
* Signed electronic informed consent
Exclusion Criteria:
* Pure ocular Myasthenia Gravis
* Diagnosed mild cognitive impairment or dyslexia
* Speech or hearing impairments affecting voice recording
* Unable to provide credible diagnostic information (healthcare provider diagnosis, antibody test results, current medications)
* Major inconsistencies in reported medical history
* Unsigned informed consent
Questions worth asking your doctor
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
1Based on my diagnosis and history, is this trial worth exploring for me — or is there a standard treatment we should try first?
2What does this trial's phase tell us about how much is already known about its safety and benefit?
3What would taking part actually involve for me — visits, tests, time, and travel?
4What are the known and possible risks or side effects I should weigh, and how would they be monitored?
5If this trial isn't the right fit, what other options or trials would you suggest I look into?
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
Questions for the trial coordinator
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
1What does taking part actually involve week to week — how many visits, where, and how long does each one take?
2What costs are covered by the study, and what might I have to pay for myself, including travel, parking, or time off work?
3What happens during screening, and what happens if the study team confirms I don't meet the criteria after those tests?
4Who pays for the scans, blood work, and other tests the trial requires — the study, my insurance, or me?
5How will being in the trial affect my regular care, and will my own doctor stay informed and involved?
6Can I leave the trial at any point if I change my mind, and what would happen to my care if I do?
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
What they're measuring
1
Accuracy of AI Model for Binary Central Fatigue Classification as Assessed by Voice Biomarker Analysis
Timeframe: Across 16 assessment sessions over 4 weeks from enrolment