NCS: Memory via Real-world Integration of Brain & IoT Perception

Project Overview

The NCS project explored how IoT sensing and neural measurements can be integrated to model human cognitive state in realistic environments, with emphasis on episodic memory and event boundaries.

It introduced a multi-task research framework spanning sensing/synchronization, semantic alignment of neural and environmental signals, and early concepts for memory-related stimulation workflows.

This project served as a predecessor platform for subsequent NIH efforts focused on scalable real-world data capture and translational memory applications.

The project also seeded Trustworthy Mixed Reality research on SLAM reliability and interpretable feature adaptation for human-centered sensing.

Key Capabilities

Portable sensor and neural-data synchronization workflows in real-world settings
Semantic alignment strategies connecting perceived context with neural dynamics
Prototype-ready design concepts for context-aware memory experimentation
Open and reproducible project artifacts for follow-on research programs
Foundational XR tracking reliability analysis methods for real-world cognitive studies

Example Use Cases

Building real-world cognitive-state datasets that combine brain and IoT signals
Analyzing memory-related neural responses under rich environmental context
Seeding follow-on work on adaptive memory support and neurotechnology safety
Developing trustworthy mixed-reality data pipelines that bridge IoT context and behavior