Digital App for Speech & Health Monitoring

Multiple Sclerosis Clinical Trial

Official title:

Digital App for Speech & Health Monitoring in Neurodegenerative Disorders

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT06450418
• Other study ID #: AC24003
• Status: Not yet recruiting
• Start date: June 2024
• Est. completion date: June 2026

Study information

• Verified date: January 2024
• Source: University of Edinburgh
• Contact: Christine R Weaver, MSc
• Phone: 01314659512
• Email: cweaver[@]ed.ac.uk
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Many people living with neurodegenerative conditions like dementia, motor neuron disease (MND), multiple sclerosis (MS), and Parkinson's disease (PD), suffer from speech problems. Using common digital technologies such as smartphone apps, the investigators can record and analyse speech in detail to provide new information for people living with these conditions, researchers, and healthcare professionals. This study will investigate the use of these digital speech recordings to help diagnose and monitor these conditions.

To take part, participants will have either a diagnosis of dementia, motor neuron disease, Parkinson's disease or Multiple Sclerosis, OR they will have no diagnosis of a neurological condition. Researchers will compare people with a diagnosis of a Neurological condition to those without.

Description:

This project aims to create novel speech-based solutions for: 1) Early detection, 2) Monitoring and 3) Stratification of neurodegenerative disorders including dementia, motor neuron disease (MND), Parkinson's disease (PD), and multiple sclerosis(MS). The investigators will develop and validate proof of concept and early-stage algorithms derived from acoustic data, which will be scaled and tested in deeply-phenotyped population.

2.2 Objectives Primary Objectives

1. To deploy and iterate a digital platform, co-produced with people living with neurodegenerative disorders, for acquisition of speech data from well characterised cohorts of people living with neurodegenerative disorders (dementia, motor neuron disease, multiple sclerosis, Parkinson's disease), and a healthy control cohort (comprising relatives/carers and volunteers without a neurological diagnosis), linked to our highly curated clinical registries at the Anne Rowling Regenerative Neurology Clinic.

2. To collect a large body of acoustic speech data from well characterised cohorts of people living with neurodegenerative disorders (dementia, MND/ALS, multiple sclerosis, Parkinson's disease), and a healthy control cohort (comprising relatives/carers and volunteers without a neurological diagnosis), linked to highly curated clinical registries.

3. To apply machine learning approaches directly to acoustic and linguistic signals from voices from people with dementia, MND, MS, Parkinson's, and healthy controls (comprising relatives/carers and volunteers without a neurological diagnosis), and to characterise prosodic patterns (rhythm, intonation, and fluency) without explicit reference to the text which is spoken, providing powerful cues about the health of the speaker.

4. Compare speech based digital outcome measures to current clinical standards to characterise and validate their clinimetric properties.

Secondary Objectives

1. Assess the feasibility and acceptability of a digital outcome measure platform in people living with neurodegenerative conditions, for use in clinical care and research.

2. To create a repository of well characterised acoustic voice samples for open access sharing/collaboration with research and industry partners.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 150
• Est. completion date: June 2026
• Est. primary completion date: June 2026
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 16 Years and older

Eligibility

Inclusion Criteria - Any one of the following:

• A person with a diagnosis of Motor Neuron Disease, Dementia, Multiple Sclerosis, or Parkinson's Disease.

• A relative or carer of the above who does not report to have a neurological condition.

• A healthy volunteer who does not report to have a neurological condition.

Exclusion Criteria:

• Age <16 years

• Significant and uncorrected visual or hearing impairment (precluding use of the App).

• Lack capacity to consent to project due to cognitive impairment (precluding understanding of the study and use of the App).

Related Conditions & MeSH terms

• Amyotrophic Lateral Sclerosis
• Dementia
• Motor Neuron Disease
• Multiple Sclerosis
• Parkinson Disease

Locations

Country	Name	City	State
n/a

Sponsors (2)

Lead Sponsor	Collaborator
University of Edinburgh	NHS Lothian

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Primary outcome measures	Area under the curve (AUC) of the receiver operating characteristic (ROC) curve for each of the 4 binary classifiers distinguishing between a disease-positive group and a healthy control group.	24 months
Secondary	Secondary outcome measure	Sensitivity, specificity, positive and negative predictive values for each of the 4 binary classifiers distinguishing between a disease-positive group and a healthy control group.	24 months
Secondary	Secondary outcome measure	Mean squared error of 4 regression models making predictions of condition-specific clinical rating scores (ACE-III, ALSFRS-R, EDSS, MDS-UPDRS)	24 months