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Prediction of Non-motor Symptoms in Fully Ambulatory MS Patients Using Vocal Biomarkers

Prediction of Non-motor Symptoms in Fully Ambulatory MS Patients Using Vocal Biomarkers

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05561621
Acronym
COMMITMENT
Enrollment
70
Registered
2022-09-30
Start date
2022-07-15
Completion date
2022-12-20
Last updated
2023-06-15

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Multiple Sclerosis

Keywords

Multiple Sclerosis, Digital Biomarker, Non-Motor symptoms, Fatigue, Cognition, Depression, Voice Analysis

Brief summary

The investigator will set up a study evaluating vocal biomarkers in people with MS in order to identify persons with non-motor symptoms: depression, cognitive deterioration, and fatigue. Up to now, to the best of the investigator's knowledge, there is no study reporting the use of vocal biomarkers to predict these three non-motor symptoms in people with MS.

Interventions

OTHERVoice analysis

Voice analysis

Sponsors

Audeering GMBH
CollaboratorINDUSTRY
Biogen
CollaboratorINDUSTRY
Insel Gruppe AG, University Hospital Bern
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 60 Years
Healthy volunteers
Yes

Inclusion criteria

* Relapsing MS * Age over 18 * EDSS \< 4.0 * Capability of written informed consent

Exclusion criteria

* Not fluent in german language * Relapse or Steroids per os/intra venous \< 4 weeks prior to examination * KM enhancing lesion in MRI \< 4 weeks prior to examination * Other previous disease affecting the speech * Pregnant patients * Mental disability and not able to understand the protocol and study tasks in german languagePatients with greater physical and cognitive disability or history of major depressive disorder and suicide attempt/suicidal thoughts * Patients with sleep disorders and comorbidities associated with extreme fatigue (e.g., fibromyalgia)

Design outcomes

Primary

MeasureTime frame
Identification of a voice signature that separates between pwMS with and without fatigueOne year

Secondary

MeasureTime frame
Identification of a voice signature that separates between pwMS with and without cognitive impairmentOne year
Identification of a voice signature that separates between pwMS with and without depressionOne year

Countries

Switzerland

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026