Related Experiment Video
Updated: Sep 10, 2025
A Computerized Functional Skills Assessment and Training Program Targeting Technology Based Everyday Functional Skills
Published on: February 13, 2020
Personalized cognitive enhancement for older adults: An aging-friendly closed-loop human-machine interface framework
Sa Zhou1, Yang Liu1, Adam Turnbull1
1Department of Psychiatry and Behavioral Sciences, Stanford University, United States.
Abstract:
Emerging digitally delivered non-pharmacological interventions (dNPIs) offer scalable, low-risk solutions for enhancing cognitive function in older adults, yet their effectiveness remains inconsistent due to a lack of personalization and precise mechanisms of action. Generic, population-based designs often fail to predict individual gains, underscoring the need for more tailored approaches. To address this, we propose a closed-loop human-machine interface (HMI) framework for personalizing dNPIs by optimizing the engagement of neurocognitive resources for cognitive enhancement. Our framework tackles three major challenges: (1) comprehensive and effective neurobehavioral representations for cognitive decoding, (2) tailoring interventions for domain-specific cognitive processes, and (3) ensuring aging-friendly design on usability, validity, and reliability for long-term adherence. We provide reviews and perspectives to guide the development of closed-loop HMIs by outlining the operational details of three key components-sensor, controller, and external actuator-that monitor, analyze, and modulate neurobehavioral activities through real-time adaptive interventions. Centering on neurobehavioral characteristics of older adults, we propose to advance closed-loop HMIs toward (1) deploying multimodal sensor network that captures activities from both central and peripheral nervous systems, (2) artificial intelligence (AI)-powered cognitive decoding and modulation that integrates multi-modal easy-to-acquire neurobehavioral signals and predicts the cross-modal harder-to-acquire signals, and (3) targeting neurobehavioral processes via internal and/or external regulation. We envision that the proposed closed-loop HMI framework could provide personalized dNPI with enhanced effectiveness and scalability for cognitive enhancement in older adults, promoting brain resilience and healthy longevity in the aging population.
More Related Videos
11:21Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
10:13Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach
Published on: February 14, 2014
Related Concept Videos
01:30Cognitive Development During Adulthood
01:20Introduction to Cognitive Psychology
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
01:21Cognitive Learning
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
01:26Aging
Cellular Clock Theory
The cellular clock theory posits that the human lifespan is closely tied to the finite capacity of cells to divide, a phenomenon governed by telomeres, which are protective caps at the ends of...