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AI & Signal Processing Logic
FluentPlay converts thought into speech support through real-time EEG decoding and intelligent signal processing. Our proprietary pipeline detects intention-to-speak states and fluency disruptions, delivering precision-timed cues that guide the user back to fluent control.
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Feature Extraction
The cleaned signal is segmented and mined for fluency-relevant neural features:
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Power Spectral Density (PSD): mental effort & speech planning
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Event-Related Potentials (ERP): intention-to-speak detection
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Phase-Amplitude Coupling (PAC): timing of speech onset
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Real-Time Preprocessing Pipeline
Each EEG stream is filtered, cleaned, and prepared within milliseconds to enable accurate interpretation:
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Noise Filtering
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Bandpass: 0.5–40 Hz
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Notch: 50/60 Hz powerline filter
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Artifact Rejection
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ICA + supervised Machine Learning for eye blinks, motion, and muscle artifacts
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Normalization
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Z-score standardization across channels and users
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Speech Synchronization Algorithm
When FluentPlay detects a fluent or blocked state, it initiates a cue to assist timing:
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Cue Types: Auditory, Haptic, or Visual
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Timing: ±150 ms alignment with cortical readiness
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Learning: Adaptive loop reduces cue reliance over time
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AI Classification Engine
Our AI model classifies brain states and predicts fluency outcomes in real-time.
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Architecture: Hybrid CNN + LSTM
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Output: Probability of fluent vs. blocked state
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Latency: <300 ms from signal to decision
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Neural Signal Acquisition
FluentPlay uses the Emotiv EEG headset to capture high-fidelity brainwave activity from speech-related regions.
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Sampling Rate: 128 Hz – 256 Hz
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Signal Types: Delta, Theta, Alpha, Beta, Gamma
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Key Electrode Sites:
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Frontal: speech initiation
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Temporal: auditory feedback
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Central: motor coordination
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