Clinical trial NCT06994767: Speech-derived Digital Biomarkers Study
Official title: Speech-derived Digital Biomarkers for Assessing Mild Cognitive Impairment and Alzheimer's Disease Diagnosis Accuracy
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Mild Cognitive Impairment (MCI)
Alzheimer Disease
Keywords: Vocal biomarkers
Mild Cognitive Impairment
Alzheimer's Disease
Deep machine learning
Artificial Intelligence application
Lead sponsor: Hackensack Meridian Health
Sponsor class: OTHER
Collaborators: name: Canary Speech Inc.
First posted: 2025-05-29
Enrollment: 100
Sex: ALL
Minimum age (years): 50
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NON_RANDOMIZED
Intervention model: PARALLEL
Primary purpose: HEALTH_SERVICES_RESEARCH

Brief summary: The goal is to assess the accuracy of an application that analyzes voice characteristics to diagnose patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). The main question is whether the application's diagnosis is the same as the clinician's for MCI and AD patients.

Detailed description: The study aims to assess the sensitivity and specificity of an application that uses vocal biomarkers to diagnose patients with mild cognitive impairment (MCI) and Alzheimer's disease. The application will use clinically validated survey instruments and voice recordings to determine the disease status of patients with MCI and Alzheimer's disease. The diagnosis developed by the application is the primary outcome variable. To determine the sensitivity and specificity, the application diagnosis will be compared against the physician's clinical diagnosis.

Eligibility criteria: Inclusion Criteria:

* Males and females between the ages of 50 and above
* Willing and capable of participating in all aspects of the study
* Willing and capable of giving informed consent
* Diagnosis of MCI or Alzheimer's by the physician
* Subjects are free of any medical condition(s) that, according to exclusion criteria, might audibly affect voice characteristics
* Subject must be able to speak and read with fluency in the English language.

Exclusion Criteria:

* All participants below 50 years
* Failure to provide informed consent
* Individuals with the following medical conditions will be excluded:

  i) Parkinson's disease ii) Huntington's disease iii) Cancer and active cancer treatments
* Persons with speech characteristics (heavy accents, slurring, stuttering, etc.) that would interfere with voice recording or voice analysis

Primary outcomes:
measure: The primary objective of the study is to assess the sensitivity biomarkers in patients with MCI and AD diagnosis
timeFrame: Upon enrollment
measure: The primary objective of the study is to assess the specificity of vocal biomarkers in patients with MCI and AD diagnosis
timeFrame: Upon enrollment
Secondary outcomes:
Other outcomes:
Locations:
city: Hackensack
country: United States
facility: Hackensack University Medical Center
state: New Jersey
Study officials:
affiliation: Hackensack Meridian Health
name: Sakshi Jain, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Martinez-Sanchez F, Meilan JJG, Carro J, Ivanova O. A Prototype for the Voice Analysis Diagnosis of Alzheimer's Disease. J Alzheimers Dis. 2018;64(2):473-481. doi: 10.3233/JAD-180037.
citation: Mueller KD, Hermann B, Mecollari J, Turkstra LS. Connected speech and language in mild cognitive impairment and Alzheimer's disease: A review of picture description tasks. J Clin Exp Neuropsychol. 2018 Nov;40(9):917-939. doi: 10.1080/13803395.2018.1446513. Epub 2018 Apr 19.
citation: Garcia AM, de Leon J, Tee BL, Blasi DE, Gorno-Tempini ML. Speech and language markers of neurodegeneration: a call for global equity. Brain. 2023 Dec 1;146(12):4870-4879. doi: 10.1093/brain/awad253.
citation: Sanborn V, Ostrand R, Ciesla J, Gunstad J. Automated assessment of speech production and prediction of MCI in older adults. Appl Neuropsychol Adult. 2022 Sep-Oct;29(5):1250-1257. doi: 10.1080/23279095.2020.1864733. Epub 2020 Dec 30.
citation: Vinod Subramanian, Namhee Kwon, Raymond Brueckner, Nate Blaylock, Henry O'Connell,