UNCLASSIFIED Background Neuroimaging technology has previously confined research to the laboratory setting, an environment that limits the generalizability of results to the real world. With the recent advent of high-density, wireless EEG technology, the promise of truly naturalistic neuroimaging research is closer than ever. This project presents a multi-aspect wearable neuroimaging system designed for use in daily life and tailored for studying stress. This system addresses several obstacles to collecting highly informative real-world neuroimaging data. First, neurophysiological data collected in a natural setting produces a rich dataset that is difficult to interpret without extensive contextual information. Our system provides this information from both user input and continuously collected physiological and actigraphy data. Second, the approach must minimally interfere with the user’s life in order to avoid altering natural behavior. Our fully wearable, light-weight design integrates multiple components to maximize user comfort, while burden on the user is minimized by the use of a typical Android-based cell phone for occasional, brief interaction and also as the sole integration center for the system. While this system is optimized for the study of stress, the advances of this approach could be applied to study other naturally occurring psychological phenomena. Tracy Jill Doty 1, W. David Hairston 1, Bret Kellihan 2, Jonroy Canady 2, Kelvin Oie 1, Kaleb McDowell 1 Developing a Wearable Real-World Neuroimaging System to Study Stress MARIN: Multi-Aspect Real-world Integrated Neuroimaging System Rich contextual information helps interpret neurological signals Maximizing comfort and minimizing burden is critical Physiological/Actigraphy Data Stream Neurophysiological Data Stream MINDO32 (MINDO) 32 channel wireless EEG system MINDO utilizes state-of-the-art dry sensors Context: User InputContext: Physiological and Actigraphy Data Sensor data are transmitted wirelessly via Bluetooth to the Android device for signal integration and synchronization with user provided information The user can indicate mode of conversation The user can log size of meal The user can report a stressful incident and will then be asked to rate their stress level 30 minutes of physiological and actigraphy data from one subject A rise in EDA not concurrent with a rise in movement. This period represents a potential stressful event that should be investigated in EEG (in this situation, the boss walked into the room). 4:14:19pm: User Reported Event on Phone – “Boss just moved box, was falling down.” A rise in EDA concurrent with a rise in movement (e.g., walking around). This event is likely not a stress-induced response, and the data associated with it are confounded by movement activity. PB-VAS: Perceived Burden Visual Analog Scale PC-VAS: Perceived Comfort Visual Analog Scale Perceived comfort ratings started high earlier in the day and dropped lower by the end of the 8 hour day, particularly for the MINDO system. We are currently investigating ways to prolong comfort over the 8 hour testing period. Future opportunities: A platform for the study of other psychological phenomena While the system presented here has been tailored to study stress specifically, its framework has been developed to be easily apapted for investigating other scientific questions. Inventories, physiological devices, and user interfaces could be chosen to optimize the system for the study of any of a number of psychological phenomena. Using this system as a prototype and utilizing its advancements will lead to a better understanding of neural activity in the real world, which ultimately will help develop better neurotechnology. Prototype interface for a system designed to study real-world symptoms of Parkinsonian movement disorders Perceived burden ratings collected at the end of an 8 hour day show that users were only moderately burdened by the experiment. As these data were collected on the first day of the experiment for the user, we anticipate that users will report less burden when returning for more testing, as they will be more familiar with the system and more efficient. 1 Translational Neuroscience Branch, HRED, U.S. Army Research Laboratory 2 Intelligent Systems Dept., DCS Corp. Alexandria, VA Devices integrated to maximize detection of stressful events Context can be derived on many levels In order to study natural behavior, a real-world neuroimaging system must have minimal interference in the user’s life.