SBIR Phase II: A tool for estimating objective outcome measures in clinical speech applications

Aural Analytics, Inc., Scottsdale AZ

Investigators

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to introduce a set of powerful neurological health metrics for objective and reliable tracking of patient outcomes, clinician performance, and therapy efficacy. Significant societal benefits may be realized from the introduction of this technology in the clinical applications and clinical trials markets. The company's technology is easy to use, reliable, objective and cost-efficient. No other existing technology for tracking neurological health or patient outcomes shares this set of features. In the company's clinical application, the company can close the gap on current health disparities and access for 1) those in rural communities, 2) those living in urban islands with limited healthcare workforce, and 3) those too sick to travel. It enhances the practice of speech-language pathology, enabling rapid objective characterization of speech production to document treatment effects. In the clinical trials market, potential impact is enhanced by the aging of the global population, and the increasing prevalence of diseases such as Parkinson's and Alzheimer's disease. The company's technology holds promise for early detection and sensitive tracking of disease progression that provides the opportunity for global-scale impact in drug development for slowing or curing neurodegenerative disease. This Small Business Innovation Research (SBIR) Phase II project aims to address the serious challenge of tapping into brain health without expensive and invasive technologies by using speech analysis. Speaking is a deceptively complex task. Elaborate brain networks translate thoughts and ideas into sequences of movements that produce the sounds of speech. Any disturbance in these networks can lead to changes in how we speak and what we say. Research shows that subtle changes in speech precede diagnosis of many neurological diseases. Leveraging this research, the company built proprietary metrics that use speech to capture changes in neurological health. Here the company extends the analytics to detect changes in cognitive health as possible early indicators of Alzheimer's disease. The company will develop 1) a series of simple tasks to elicit speech from an individual using our app; 2) a custom speech recognition platform to automatically generate a transcript of what the person said; 3) algorithms to automatically analyze the transcript and output clinically interpretable measures of cognitive performance. Finally, the company will evaluate the validity/usability of the app in clinical settings. The product of this research is a platform ready to move toward commercialization to realize its maximum potential for health and societal impact. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.