Cognitive Decline
Cognitive Decline screening by GIA®, powered by digitalhumanOS™, uses Voice AI, Computer Vision, and Speech Biomarkers to detect cognitive decline through a single patient conversation. Screening performance: 70.8% accuracy. Screening takes under 5 minutes with results in 60 seconds.
Subtle cognitive changes often go unnoticed, impacting communication and hindering rehabilitation.
Early detection of cognitive decline allows for tailored care plans in post-acute care. By understanding patient cognitive abilities, we can optimize therapy and improve outcomes.
Key Facts
- Screening Time
- Under 5 minutes
- Results
- 60 seconds
- Modalities
- Voice + Vision + Speech
- Registration
- 510(k)
- Status
- Live
About Cognitive Decline screening.
How does the system detect cognitive decline?
The system analyzes speech patterns, vocal characteristics, and cognitive tasks to assess cognitive function.
How can this information be used to improve patient care?
Identifying cognitive decline allows for adjustments to therapy techniques, communication strategies, and environmental modifications.
What is the accuracy rate for detecting cognitive decline?
The model achieves an accuracy rate of 70.8%.
The science behind Cognitive Decline screening.
Research published in The Lancet Regional Health, conducted with Japan's National Cerebral and Cardiovascular Center, confirms that voice biomarkers accurately detect Mild Cognitive Impairment.
Study Confirms Voice Biomarkers Accurately Detect Mild Cognitive Impairment — The Lancet Regional Health (2025-06) · Japan's National Cerebral and Cardiovascular Center (NCVC)Peer-reviewed research demonstrates that spontaneous conversational speech contains detectable biomarkers for Mild Cognitive Impairment — enabling screening without scripted prompts or clinical interviews.
Detecting Mild Cognitive Impairment using Vocal Biomarkers from Spontaneous Speech (2024-09)Clinical research establishes voice analysis as a validated approach to early MCI detection — addressing a condition missed by primary care physicians in 92% of cases.
Mild Cognitive Impairment (MCI) Detection via Voice Analysis (2023-01)A real-world health innovation study demonstrates that voice biomarker technology provides objective data for assessing cognitive wellness — improving patient outcomes in community health settings.
Wyoming Health Innovation Living Lab Case Study (2024-01)The Framingham Heart Study, analyzing over 4,000 voice recordings paired with MRI-derived brain data, found that vocal markers including jitter, articulation rate, and lexical diversity are significantly associated with structural changes in memory-related brain regions.
Framingham Heart Study — Voice and Brain Structure Correlation (2026-03) · NIH Bridge2AI-Voice Consortium, Boston University, Vanderbilt University Medical Center