DementiaNCT06450418
Digital App for Speech & Health Monitoring
An observational study of Dementia and Motor Neuron Disease, run by University of Edinburgh at 1 site in United Kingdom.
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. Read more about this study
- Who is it for?
- Ages 16 years and olderHealthy volunteers can take part
- Conditions the study is for
- Dementia, Motor Neuron Disease, Multiple Sclerosis
- How many people
- 150 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 12 Jul 2024to Jun 2029
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 16 years and older
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: Participants with Neurodegenerative Disorders and their relatives or carers without a diagnosis of a Neurodegenerative disorder.
Who may be able to join
- 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.
Who cannot join
- 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).
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United Kingdom1 site, 1 recruiting
- Recruiting
NHS Lothian
Edinburgh
Suvankar Pal
About this study
Official title: Digital App for Speech & Health Monitoring in Neurodegenerative Disorders
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.
Read the detailed 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
- 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.
- 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.
- 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.
- Compare speech based digital outcome measures to current clinical standards to characterise and validate their clinimetric properties.
Secondary Objectives
- Assess the feasibility and acceptability of a digital outcome measure platform in people living with neurodegenerative conditions, for use in clinical care and research.
- To create a repository of well characterised acoustic voice samples for open access sharing/collaboration with research and industry partners.
- Conditions
- Dementia, Motor Neuron Disease, Multiple Sclerosis, Parkinson Disease
- Medical subject headings
- Dementia, Motor Neuron Disease, Multiple Sclerosis, Parkinson Disease
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Carers/Realtives/ Healthy - No Diagnosis of a Neurodegenerative Disorder | Not described | |
| Motor Neuron Disease | Not described | |
| Multiple Sclerosis | Not described | |
| Dementia | Not described | |
| Parkinson's Disease | Not described |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 24 months
Secondary outcomes (2)
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.
Measured: 24 months
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)
Measured: 24 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Jun 2024
- Study start12 Jul 2024
- Primary completion30 Jan 2029 (estimated)
- Study completionJun 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for DementiaStudies of the same condition, open and under way.
- More trials run by University of EdinburghThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 150 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Edinburgh
- Sponsor type
- University, hospital or other
- Collaborators
- NHS Lothian
- Responsible party
- Sponsor
- Investigators
- Suvankar Pal, Prof, Principal investigator, University of Edinburgh
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06450418
- Sponsor's protocol ID
- AC24003
- Status last verified
- Sep 2026
- First submitted
- 9 Feb 2024
- Last updated
- 10 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Tam J, Weaver C, Ihenacho A, Newton J, Virgo B, Barrett S, Neale J, Perry D, Smith A, Chandran S, Watts O, Pal S; DASH Consortium. Digital App for Speech and Health Monitoring Study (DASH): protocol for a prospective longitudinal case-control observational study for developing speech datasets in neurodegenerative disorders and dementia. BMJ Open. 2025 Dec 5;15(12):e100222. doi: 10.1136/bmjopen-2025-100222.
PubMed 41360452
Study at a glance
From the registry record, last updated by the sponsor on 10 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Digital App for Speech & Health Monitoring in Neurodegenerative Disorders
- ClinicalTrials.gov ID
- NCT06450418
- Acronym / sponsor ID
- AC24003
- Conditions
- Dementia, Motor Neuron Disease, Multiple Sclerosis, Parkinson Disease
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 150 participants (estimated)
- Lead sponsor
- University of EdinburghUniversity, hospital or other
- Collaborators
- NHS Lothian
- Study start
- 12 Jul 2024 (actual)
- Primary completion
- 30 Jan 2029 (estimated)
- Study completion
- Jun 2029 (estimated)
- First posted
- 10 Jun 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed 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
- 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.
- 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.
- 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.
- Compare speech based digital outcome measures to current clinical standards to characterise and validate their clinimetric properties.
Secondary Objectives
- Assess the feasibility and acceptability of a digital outcome measure platform in people living with neurodegenerative conditions, for use in clinical care and research.
- To create a repository of well characterised acoustic voice samples for open access sharing/collaboration with research and industry partners.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 5
| Arm | Type | Receives |
|---|---|---|
| Carers/Realtives/ Healthy - No Diagnosis of a Neurodegenerative Disorder | – | – |
| Motor Neuron Disease | – | – |
| Multiple Sclerosis | – | – |
| Dementia | – | – |
| Parkinson's Disease | – | – |
Who may qualify
- Ages
- 16 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Participants with Neurodegenerative Disorders and their relatives or carers without a diagnosis of a Neurodegenerative disorder.
Key inclusion criteria (3 listed)
- 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.
Key exclusion criteria (3 listed)
- 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).
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Primary outcome measures
Time frame: 24 months
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.
2 secondary outcomes
Secondary outcome measure
Time frame: 24 months
Secondary outcome measure
Time frame: 24 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 Sep 2026.
- Derived from this study: PubMed 41360452Tam J, Weaver C, Ihenacho A, Newton J, Virgo B, Barrett S, Neale J, Perry D, Smith A, Chandran S, Watts O, Pal S; DASH Consortium. Digital App for Speech and Health Monitoring Study (DASH): protocol for a prospective longitudinal case-control observational study for developing speech datasets in neurodegenerative disorders and dementia. BMJ Open. 2025 Dec 5;15(12):e100222. doi: 10.1136/bmjopen-2025-100222.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Suvankar Pal, Prof principal investigator
University of Edinburgh
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Dementia and Motor Neuron Disease, run by University of Edinburgh at 1 site in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 10 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Christine R Weaver, MSc (01314659512, cweaver@ed.ac.uk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Primary outcome measures (time frame: 24 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06450418, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 10 Sep 2026.