Method for AI-based animal EEG analysis and language implementation

A communication device that translates pet emotions into language using non-invasive EEG and reinforcement learning AI

This technology is an animal EEG analysis and language implementation system that uses electrodes attached to an animal's head to non-invasively measure brain waves. An AI neural network interprets emotions and intentions from these patterns, converting them into human-readable text or speech.

Existing methods for understanding pets rely on subjective interpretations of outward behaviors like barking or body language, often missing subtle emotions like pain or anxiety. Furthermore, animal EEG research has historically relied on invasive laboratory equipment, making it difficult to use in everyday settings.

This technology consists of a data collection module (EEG/ECG sensors, amplifier, A/D converter, noise filter, and wireless transmitter), a neural network-based signal analysis module, an NLP language conversion module, and an output module. A continuous learning module refines the deep learning model through feedback. It can be applied to pet wearables, veterinary stress assessment, and smart home services, allowing owners to understand their pet's emotions in real-time with increasing accuracy over time.

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Key Features:

• A data collection module consisting of sensors and hardware that non-invasively captures animal EEG signals without surgical intervention.
• A signal analysis module that processes acquired EEG data using AI algorithms and interprets emotions and intentions via pre-trained neural networks.
• A language conversion module that translates analysis results into human language and generates sentences tailored to the emotional state and intent using NLP.
• A continuous learning module that uses feedback from the analysis results to perform reinforcement learning, improving accuracy through data accumulation.

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