In this project, we are developing methods to gather longitudinal voice data from people in their daily lives using a mobile app. This remote approach allows us to study how voices change naturally over time in a large, diverse sample. By analyzing these real-world voice samples, we hope to identify subtle acoustic markers of aging or health changes that might be missed in brief clinic visits. This work not only leverages AI and mobile technology to collect data at an unprecedented scale, but also ensures our insights are grounded in everyday voice use, leading to practical health monitoring tools in the future….

This project uses AI to analyze sleep sounds for early detection of breathing issues in midlife adults, enabling home-based, personalized health care….

This project explores an innovative approach to cognitive health screening using familiar brand logos as cues for memory and language. We have developed NEURO-logo (Neurological Screening via Logo Recognition), a tool that assesses naming and recognition of widely known logos to detect early signs of cognitive or linguistic impairment. Unlike tests that rely on faces, written words, or generic objects, logos offer a unique advantage in that they are culturally salient, visually distinctive, and semantically rich, thus engaging multiple cognitive domains such as visual recognition, semantic memory, language retrieval, and brand association. …

This retrospective study observes how an individual’s voice may shift as they age especially under the high demands of professional voice use….

This study explores how hormone therapy used to manage menopause affects women’s voices, a critical but overlooked aspect of health and quality of life…