PFI-TT: Interactive Block Games for Routine Cognitive Assessment of Mild Cognitive Impairment and Alzheimer's Disease

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The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project addresses the urgent social need of a low-cost, long-term solution for routine cognitive assessment of mild cognitive impairment (MCI) and Alzheimer's disease (AD). Early detection at the MCI stage is a key to delaying onset of this degenerative disease and slow worsening of the symptoms. This project will re-invent a novel, automated, game-based technology that can be used for routine cognitive assessment of older individuals who are at a high risk of developing AD. This technology-enabled method will significantly lower the cost associated with cognitive assessment and enable objective and accurate measurements of one's cognitive status, which will lead to early detection of cognitive declines associated with MCI and AD. This project also brings unique and valuable learning and training opportunities for the diverse students participating in the research and workshop activities. The proposed applied research will be tightly integrated with the training and mentoring of graduate students to become future leaders in technology innovation and entrepreneurship.The proposed project will develop a novel technology platform for automated, play-based routine cognitive assessment in older adults and demonstrate its commercial potential. This innovative system employs a set of highly instrumented cubes interfacing with computerized games. The cubes feature programmable visual, auditory, and tactile sensory feedback mechanisms and embedded motion sensors for user performance and behavior assessment via interactive play. The games will be designed to capture working memory, spatial reasoning, response time, and hand-eye coordination skills tailored for the target population. The integrated computational measures of play complexity will enable the system to automatic adjust the game difficulty based on the user performance. The system will not only automate the administration and data collection process, but also produce new types of behavioral data, such as hand tremor, repetitive or hyperactive motions, and manipulation speed. The proposed technology development and evaluation will take the co-design approach in order to effectively address user-specific requirements and technical improvements for potential commercialization. A partnership with a local continuing care retirement community (CCRC) will streamline and accelerate the complex co-design process via utilizing the living lab established in the partnering CCRC.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.