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5fe3e22 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 | import asyncio
import random
from typing import Dict, List, Any
import logging
class BCIConnector:
"""
Connecteur pour interfaces cerveau-machine
Simulation de lecture et d'interprétation de signaux cérébraux
"""
def __init__(self):
self.logger = logging.getLogger("bci_connector")
self.signal_quality = 0.0
self.mental_states = {}
self.brain_patterns = {}
async def initialize(self):
"""Initialise l'interface BCI"""
self.logger.info("🧠 Initialisation de l'interface cerveau-machine...")
try:
await self._calibrate_sensors()
await self._setup_pattern_recognition()
self.signal_quality = 0.85
self.logger.info("✅ Interface BCI initialisée")
return True
except Exception as e:
self.logger.error(f"❌ Erreur d'initialisation BCI: {e}")
return False
async def read_brain_signals(self) -> Dict[str, Any]:
"""Lit les signaux cérébraux en temps réel"""
try:
# Simulation de signaux cérébraux
signals = {
"eeg": {
"delta": random.uniform(0.1, 0.5),
"theta": random.uniform(0.1, 0.4),
"alpha": random.uniform(0.1, 0.6),
"beta": random.uniform(0.1, 0.8),
"gamma": random.uniform(0.1, 0.3)
},
"focus_level": random.uniform(0.3, 0.9),
"mental_workload": random.uniform(0.2, 0.8),
"emotional_state": random.choice(["calme", "concentré", "créatif", "attentif"]),
"signal_quality": self.signal_quality
}
return signals
except Exception as e:
self.logger.error(f"Erreur de lecture BCI: {e}")
return {"error": str(e)}
async def detect_mental_commands(self) -> List[Dict[str, Any]]:
"""Détecte les commandes mentales"""
commands = [
{"type": "focus", "intensity": random.uniform(0.5, 0.95), "confidence": 0.8},
{"type": "imagine", "content": "mouvement", "confidence": 0.7},
{"type": "emotion", "value": random.choice(["positive", "negative", "neutral"]), "confidence": 0.6}
]
return random.sample(commands, random.randint(1, 3))
async def send_neuro_feedback(self, feedback: Dict[str, Any]) -> bool:
"""Envoie un feedback neuro-cognitif"""
self.logger.info(f"📤 Envoi de feedback neuro: {feedback.get('type', 'inconnu')}")
return True
async def _calibrate_sensors(self):
"""Calibre les capteurs BCI"""
self.logger.info("🎯 Calibration des capteurs cérébraux...")
await asyncio.sleep(0.8)
self.signal_quality = random.uniform(0.7, 0.95)
self.logger.info(f"📊 Qualité du signal: {self.signal_quality:.3f}")
async def _setup_pattern_recognition(self):
"""Configure la reconnaissance de patterns cérébraux"""
self.brain_patterns = {
"focus_patterns": ["concentration_intense", "attention_soutenue"],
"creative_patterns": ["pensee_laterale", "association_libre"],
"relaxation_patterns": ["meditation", "detente_profonde"]
} |