Digital human could allow for better early dementia detection
Researchers are developing AI that can ask screening questions, while observing facial expressions, to evaluate patients for signs of apathy, an early indicator of dementia.
Apathy can be an early indicator of dementia. Texas A&M researchers are building a digital human that combines screening questions with facial expression analysis and biometric monitoring to identify subtle signals, including apathy.
Researchers are developing an AI‑powered digital human that could transform how clinicians detect early signs of dementia, using screening questions with facial expression analysis and biometric monitoring to uncover subtle indicators often missed in traditional screenings.
Funded by the Texas A&M Health Dementia and Alzheimer’s Research Initiative (DARI), the project aims to address one of the field’s biggest challenges: reliable, early‑stage testing. The project is led by Dr. Mark Benden, professor of environmental and occupational health at the School of Public Health.
Apathy as a key early indicator of neurodegenerative disease
By combining a virtual interviewer while monitoring patient biomarkers, the team hopes to create a more sensitive and scalable way to identify apathy, one of the earliest and most telling neurological warning signs.
Apathy can appear even before cognitive decline. Its characteristics include reduced initiation, motivation and emotional engagement; when onset of these symptoms seem sudden, it could be an early indicator of dementia “Because apathy frequently precedes more visible impairment, identifying it early offers a crucial chance for proactive intervention,” Benden said.
One established clinical tool is an apathy test, in which patients answer questions that are scored with tools such as the Apathy Evaluation Scale and the Lille Apathy Rating Scale.
But Benden said today’s methods rely heavily on subjective self‑report scales. “These approaches present limitations, including recall and wording biases, and are not well-suited for detecting subtle differences in severity or tracking changes in large populations,” he said. “While newer tools like the computerized Philadelphia Apathy Computerized Task (PACT) provide behavioral measures, they lack validated individual-level cut‑off points, limiting their diagnostic utility.”
A virtual interviewer guides the patient through apathy-related questions, while monitoring biomarkers, observing facial expressions and measuring response time.
Replacing subjective tests with objective data
Benden’s project centers on building a score rooted in behavioral, cognitive and emotional dimensions.
Rather than relying on subjective self-reporting, the team is developing a system that measures objective data during a computer‑based interaction with a digital human. As the virtual interviewer guides the patient through apathy‑related questions, the system simultaneously monitors biomarkers, observes facial expressions and measures response time.
“These additional objective findings may make comparisons both between people and across individuals over time more valuable for predicting illness,” Benden said.
Creating a standardized Digital Apathy Signature
The goal, Benden said, is to develop and validate a “Digital Apathy Signature” that can distinguish nuanced levels of apathy severity, reducing reliance on subjective surveys and improving sensitivity in detecting early dementia risk. “By grounding the assessment in real‑time behavioral, emotional and cognitive data, the scale aims to differentiate apathy from similar conditions and better support diagnosis, monitoring and treatment evaluation,” he said.
Benden emphasized that a standardized, biomarker‑derived apathy risk score could make assessment more consistent, enabling clinicians to make decisions at the individual level, provide appropriate referrals and track progression over time in ways existing tools cannot accommodate.
The Texas A&M Health Dementia and Alzheimer’s Research Initiative (DARI) represents a bold and strategic commitment to advancing research, education and innovation aimed at preventing, detecting and treating neurodegenerative diseases. Alzheimer’s disease and related dementias affect millions of individuals and families, placing a growing burden on health care systems and communities. As a leading health research institution, Texas A&M Health is uniquely positioned to address this urgent public health challenge by leveraging strengths across disciplines and engaging collaborators across the university and beyond. For more information, visit health.tamu.edu/dari.
