ISLAMABAD, MAY 29 (ONLINE): Without AI, trying to analyze a person\u2019s speech for clues about cognitive decline was time-consuming and hard to parse, according to one study author.Getty Images<\/p>\n
Advanced AI analysis may be able to spot subtle features in a person\u2019s speech that could help doctors detect Alzheimer\u2019s disease years before symptoms of mental decline appear.<\/p>\n
That\u2019s according to recent research published in the Alzheimer\u2019s Association journal Diagnosis, Assessment and Disease Monitoring, which found that natural language processing (NLP), speech recognition, and machine learning could be used to identify difficult-to-measure voice changes that correspond with specific biomarkers linked to Alzheimer\u2019s disease, including levels of the protein amyloid-beta, which scientists have likened to \u201cseeds\u201d that may later grow to become Alzheimer\u2019s.<\/p>\n
\u201cPrior to the development of machine learning and NLP, the detailed study of speech patterns in patients was extremely labor intensive and often not successful, because the changes in the early stages [of Alzheimer\u2019s] are frequently undetectable to the human ear,\u201d said lead study author Ihab Hajjar, MD, a professor of neurology at UT Southwestern\u2019s Peter O\u2019Donnell Jr. Brain Institute, in a news release.<\/p>\n
\u201cThis novel method of testing performed well in detecting those with mild cognitive impairment and more specifically in identifying patients with evidence of Alzheimer\u2019s disease \u2014 even when it cannot be easily detected using standard cognitive assessments.\u201d<\/p>\n
Dr. Hajjar and his collaborators collected data on 206 people aged 50 and older, 114 who met the criteria for mild cognitive decline and 92 who were cognitively unimpaired. Each person\u2019s cognitive status was determined through standard testing.<\/p>\n
Study subjects were also recorded as they gave a one- to two-minute description of a colorful circus procession.<\/p>\n
Subtle Speech Features May Signal Alzheimer Risk
\nUsing sophisticated computer analysis of these recordings, scientists could determine and evaluate specific types of speech features, including:
\n\u2022\thow fast a person talks
\n\u2022\tpitch
\n\u2022\tvoicing of vowel and consonant sounds
\n\u2022\tgrammatical complexity
\n\u2022\tspeech motor control
\n\u2022\tidea density<\/p>\n
The research team also examined cerebral spinal fluid samples for amyloid beta protein. One form called amyloid beta peptide 42, for example, is especially toxic, according to the National Institute on Aging, and plays a significant role in Alzheimer\u2019s disease. A total of 40 cognitively unimpaired and 63 impaired individuals were found to be amyloid-positive.<\/p>\n
7 Tips for Communicating With Someone Who Has Alzheimer\u2019s
\nIn addition, scientists reviewed MRI brain scans, which can provide measures of hippocampus volume. In the early stages of AD, the hippocampus \u2014 which plays a significant role in memory and learning \u2014 shows rapid loss of its tissue, according to research.<\/p>\n
By comparing all these tests, the study authors discovered that specific speech characteristics, including loudness, corresponded with the presence of amyloids and hippocampus size.<\/p>\n
Melissa Lee, PhD, a program officer for the Alzheimer\u2019s Drug Discovery Foundation\u2019s program for biomarker development, notes that the researchers were able to identify specific speech patterns in both the impaired and unimpaired individuals who had biological indicators of Alzheimer\u2019s.<\/p>\n
\u201cIt\u2019s interesting and really exciting that the researchers could see the speech patterns in the cognitively unimpaired group with amyloid beta present, because individuals who have amyloid beta protein present are the ones that are more likely to go on and develop this disease,\u201d says Dr. Lee.<\/p>\n","protected":false},"excerpt":{"rendered":"
ISLAMABAD, MAY 29 (ONLINE): Without AI, trying to analyze a person\u2019s speech for clues about cognitive decline was time-consuming and hard to parse, according to one study author.Getty Images Advanced AI analysis may be able to spot subtle features in a person\u2019s speech that could […]<\/p>\n
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