Computerized cognitive training (CCT) is a scalable, well-tolerated intervention that has promise for slowing cognitive decline. The effectiveness of CCT is often affected by a lack of effective engagement. Factors like Mental fatigue and reaction time are the primary factors for compromising effective engagement in CCT, particularly in older adults at risk for dementia. There is a need for scalable, automated measures that can constantly monitor and reliably detect mental fatigue and reactions during CCT. Our research uses recent advances in computer vision and AI to detect and predict these factors from multi-sensory data and provide feedback to the CCT tools for real-time personalization of the sessions.