03/08/2024
Who has alzheimers? a few minute recording can tell a lot.
(remember to eat well, meditate, exercise and be mentally active to age well, a number of supplements can really help)
new AI based analysis of digital voice recordings are quite accurate in new research:
lexicalsemanticbiomarkers have significant value in the detection of amyloid-β status, and both lexical-semanticand acoustic biomarkers are sensitive to cognitive status, have higher diagnostic accuracy compared to Boston Naming Test, and may be sensitive in tracking AD progression in its early stages."
PAPER: Development of digital voice biomarkers and associations withcognition, cerebrospinal biomarkers, and neural representationin early Alzheimer’s disease
AbstractIntroduction: Advances in natural language processing (NLP), speech recognition, andmachine learning (ML) allow the exploration of linguistic and acoustic changes previouslydifficult to measure. We developed processes for deriving lexical-semantic andacousticmeasures as Alzheimer’s disease (AD) digital voice biomarkers.Methods: We collected connected speech, neuropsychological, neuroimaging, andcerebrospinal fluid (CSF) AD biomarker data from 92 cognitively unimpaired (40 Aβ+)and 114 impaired (63 Aβ+) participants. Acoustic and lexical-semantic features werederived from audio recordings using ML approaches.Results: Lexical-semantic (area under the curve [AUC] = 0.80) and acoustic (AUC =0.77) scores demonstrated higher diagnostic performance for detecting MCI comparedto Boston Naming Test (AUC = 0.66). Only lexical-semantic scores detectedamyloid-β status (p = 0.0003). Acoustic scores associated with hippocampal volume(p = 0.017) while lexical-semantic scores associated with CSF amyloid-β (p =0.007). Bothmeasures were significantly associated with 2-year disease progression.Discussion: These preliminary findings suggest that derived digital biomarkers mayidentify cognitive impairment in preclinical and prodromalAD, andmay predict diseaseprogression.
