Detecting Fatigue From Voice in Generalised Myasthenia Gravis

NCT07033559 | Not Yet Recruiting

• 1 other identifier: RWE1049
• Study Type: observational
• Target: 240
• Locations: 0 countries
• Sites: N/A

Brief 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. 1.Can advanced voice analysis accurately tell when participants are experiencing deep exhaustion based on how they speak?
2. 2.How easy and acceptable is voice-based fatigue monitoring for people with myasthenia gravis?
3. 3.Record themselves reading short passages and answering questions out loud twice daily (morning and evening), twice a week, for 4 weeks.
4. 4.Answer brief questionnaires about their energy levels, mood, and myasthenia gravis symptoms during each session.
5. 5.Use their own devices (computer, tablet, or smartphone) to complete all study activities online from home.

Conditions

Myasthenia Gravis Generalised

Keywords

myasthenia gravis; generalised myasthenia gravis; fatigue; voice biomarkers; digital health; speech analysis; artificial intelligence

Outcome Measures

Primary Outcomes (1)

• Accuracy of AI Model for Binary Central Fatigue Classification as Assessed by Voice Biomarker Analysis

  Binary classification performance (presence vs. absence of central fatigue) of the artificial intelligence-based system using voice biomarker analysis, with the subjective fatigue scale serving as ground truth. Performance will be measured using sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) metrics through cross-validation methods.

  Across 16 assessment sessions over 4 weeks from enrolment

Secondary Outcomes (5)

• Study Completion Rate Among Enrolled Participants

  From enrolment through completion of final assessment session at 4 weeks

• Individual Session Completion Rate Across All Participants

  From enrolment through completion of final assessment session at 4 weeks

• Adherence to Specified Assessment Time Windows

  From enrolment through completion of final assessment session at 4 weeks

• Participant Acceptability of Voice-Based Monitoring System

  At completion of final assessment session at 4 weeks

• Participant Withdrawal Patterns and Reasons

  From enrolment through 4 weeks or until participant withdrawal

Other Outcomes (2)

• Exploratory: Correlation Between Central and Peripheral Fatigue

  4 weeks

• Exploratory: Fatigue-Mood Relationship

  4 weeks

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population consists of a convenience sample of adults with generalised Myasthenia Gravis recruited through a decentralised, multi-channel approach across the United States and United Kingdom. This remote recruitment strategy leverages established myasthenia gravis patient networks, charities and digital platforms like social media groups to reach geographically dispersed participants. The decentralised methodology is particularly appropriate for studying a rare condition where patients may have limited mobility due to fatigue and muscle weakness.

You may qualify if:

• 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

You may not qualify if:

• 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

Sponsors & Collaborators

• Thymia Limited: lead
• UCB Pharma: collaborator

Related Publications (2)

• Regnault A, Habib AA, Creel K, Kaminski HJ, Morel T. Clinical meaningfulness and psychometric robustness of the MG Symptoms PRO scales in clinical trials in adults with myasthenia gravis. Front Neurol. 2024 Jun 24;15:1368525. doi: 10.3389/fneur.2024.1368525. eCollection 2024.

  PMID: 38978809 BACKGROUND

• Fara, S., Goria, S., Molimpakis, E., Cummins, N. (2022). Speech and the n-Back task as a lens into depression. How combining both may allow us to isolate different core symptoms of depression. Proc. INTERSPEECH 2022, 1911-1915.

  BACKGROUND

MeSH Terms

Conditions

Myasthenia Gravis; Fatigue

Condition Hierarchy (Ancestors)

Paraneoplastic Syndromes, Nervous System; Nervous System Neoplasms; Neoplasms by Site; Neoplasms; Paraneoplastic Syndromes; Autoimmune Diseases of the Nervous System; Nervous System Diseases; Neurodegenerative Diseases; Neuromuscular Junction Diseases; Neuromuscular Diseases; Autoimmune Diseases; Immune System Diseases; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Study Officials

• Alexandra L Georgescu, PhD

  Thymia Limited

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Alexandra L Georgescu, PhD

CONTACT

0044 7533848443; alexandra@thymia.ai

Emilia Molimpakis, PhD

CONTACT

0044 7541950731; emilia@thymia.ai

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: June 3, 2025
• First Posted: June 24, 2025
• Study Start: February 1, 2026
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): December 1, 2026
• Last Updated: January 28, 2026

Record last verified: 2026-01

Data Sharing

• IPD Sharing: Will not share