P2‐316: WORK IN PROGRESS: AN INDUSTRY‐CLINICAL‐ACADEMIC PARTNERSHIP FOR DIGITAL AND PERSISTENT ASSESSMENT OF MOTOR AND COGNITIVE‐LINGUISTIC OUTCOMES

• DOI: 10.1016/j.jalz.2019.06.2723
• Publication Date: 2019-10-18T11:05:27Z
• Authors: Visar Berisha; Julie Liss; Daniel Jones; Shira Hahn; Seward Rutkove; Kerisa Shelton; Rhoda Au; Jeremy Shefner
• Keywords: Acquired brain injury

Remote and digital assessment of neurological health has the potential for earlier detection decline more sensitive tracking health. The implications this are considerable. More outcome measures can lead to tools early diagnosis or help power clinical trials with fewer samples. Speech is an important modality in context because it easy collect taxes both cognitive motor systems. Aural Analytics (A2) a platform monitoring cognitive-linguistic outcomes at-home in-clinic using automated speech analytics. In work we describe role that analysis plays as part complete brain highlight use-case from large-scale home-monitoring studies. Participants download application on their Android iOS devices guided through set speech-elicitation tasks. A suite back-end algorithms extracts collected samples generate battery clinically-interpretable related control, cognition, mood/affect. Constellations these features relevant different diseases. technology been validated contexts collaboration academic partners. This focuses ongoing studies Barrow Neurological Institute. Amyotrophic lateral sclerosis (ALS) patients without fronto-temporal dementia personal device provide periodic addition, they also evaluated clinically-standard cognition rating scales. We use generalized linear models (GLMs) evaluate relationship between measures. Preliminary GLM reveals strongly predictive ALS-functional scale. post-hoc changes precede clinically-detectable changes. results analytics robust means Current on-going include preclinical Alzheimer's disease centered identifying voice biomarkers.