Neural Interfaces

Overview

Neural Interfaces is a research project exploring how neural signals can be captured, interpreted, and mapped to interactive digital systems. The project focuses on the intersection of neuroscience, human–computer interaction, and real-time signal processing.

Rather than aiming for clinical applications, the work investigates neural input as an experimental interaction modality.

Research Motivation

As traditional input devices reach maturity, interest is growing in more direct and embodied forms of interaction. Neural interfaces offer the potential to bypass conventional controls, but introduce significant technical and cognitive challenges.

This project explores questions such as:

• How can noisy neural signals be transformed into usable interaction cues?
• What levels of latency and accuracy are acceptable for interactive use?
• How do users adapt to implicit, non-conscious input channels?

The goal is to understand feasibility rather than to optimize for precision.

Signal Processing Pipeline

The prototype is organized around a modular pipeline:

1. Signal Acquisition EEG data is captured using consumer-grade and research-grade devices.

2. Preprocessing Noise reduction, filtering, and normalization are applied in real time.

3. Feature Extraction Temporal and spectral features are derived from neural signals.

4. Interaction Mapping Extracted features are mapped to high-level interaction events.

Python is used for rapid experimentation and analysis.

Experiments

Experiments focused on simple interaction scenarios, including:

• Binary and continuous control signals
• Attention and relaxation-based interactions
• Adaptive thresholds based on user calibration

Evaluation emphasized robustness, learnability, and subjective user experience over raw signal accuracy.

Challenges & Observations

Key challenges identified include:

• High variability between users
• Signal instability over time
• Cognitive load and mental fatigue

Findings suggest that neural interfaces are best suited for augmenting, rather than replacing, traditional interaction methods.

Future Directions

Planned research directions include:

• Hybrid interfaces combining neural and physical input
• Adaptive models that learn from user behavior over time
• Integration with immersive XR environments
• Exploration of neural input for accessibility use cases

Neural Interfaces remains an exploratory research effort aimed at understanding the role of biosignals in interactive systems.