Multi-modal Biomarkers to Discriminate Cognitive State
Abstract
Multimodal biomarkers based on behavioral, neurophysiological, and cognitive measurements have recently obtained increasing popularity in the detection of cognitive stress- and neurological-based disorders. Such conditions are significantly and adversely affecting human performance and quality of life for a large fraction of the worlds population. Example modalities used in detection of these conditions include voice, facial expression, physiology, eye tracking, gait, and EEG analysis. Toward the goal of finding simple, noninvasive means to detect, predict and monitor cognitive stress and neurological conditions, MIT Lincoln Laboratory is developing biomarkers that satisfy three criteria. First, we seek biomarkers that reflect core components of cognitive status such as working memory capacity, processing speed, attention, and arousal. Second, and as importantly, we seek biomarkers that reflect timing and coordination relations both within components of each modality and across different modalities.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 2015
- Accession Number
- AD1034474
Entities
People
- Brian S. Helfer
- Christopher J Smalt
- Daryush D. Mehta
- James R. Williamson
- Jeffrey S. Palmer
- Joey Perricone
- Joseph Moran
- Kristin J. Heaton
- Laura Brattain
- Marianna Eddy
- Tejash Patel
- Thomas F. Quatieri
Organizations
- MIT Lincoln Laboratory