Speech-derived Digital Biomarkers Study

Speech-derived Digital Biomarkers for Assessing Mild Cognitive Impairment and Alzheimer's Disease Diagnosis Accuracy

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.

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.

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
• For the control group: Without diagnosis of MCI or Alzheimer's or other types of dementia
• 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