import numpy as np
from typing import Tuple

class SuddenSicknessDetector:
    """
    突发疾病检测器
    
    基于 PMC 综述框架:
    1. 感知: 多模态生理信号
    2. 分析: 疾病模式识别
    3. 决策: 紧急状态分级
    4. 干预: 安全停车+紧急呼叫
    """
    
    def __init__(self):
        self.state = 'normal'  # normal/warning/emergency
        self.alert_duration = 0
        
    def detect(
        self,
        head_pose: Tuple,        # (pitch, yaw, roll)
        eye_openness: Tuple,      # (left, right)
        body_motion: float,      # 身体运动幅度
        breathing_rate: float,   # 呼吸频率
        heart_rate: float,        # 心率
        skin_color: np.ndarray,   # 面部肤色
        seat_pressure: np.ndarray, # 座椅压力分布
        timestamp: float
    ) -> dict:
        """突发疾病检测"""
        
        # 癫痫检测：异常运动+意识丧失
        seizure_score = self._detect_seizure(body_motion, eye_openness)
        
        # 心脏骤停：心率骤变+呼吸停止
        cardiac_score = self._detect_cardiac_arrest(heart_rate, breathing_rate)
        
        # 中风检测：面部不对称
        stroke_score = self._detect_stroke(skin_color, head_pose)
        
        # 晕厥检测：头部下垂+闭眼+松垮
        syncope_score = self._detect_syncope(head_pose, eye_openness, seat_pressure)
        
        scores = {
            'seizure': seizure_score,
            'cardiac': cardiac_score,
            'stroke': stroke_score,
            'syncope': syncope_score
        }
        
        max_disease = max(scores, key=scores.get)
        max_score = scores[max_disease]
        
        # 状态分级
        if max_score > 0.8:
            self.state = 'emergency'
            self.alert_duration += 1
        elif max_score > 0.5:
            self.state = 'warning'
        else:
            self.state = 'normal'
            self.alert_duration = 0
        
        return {
            'state': self.state,
            'likely_condition': max_disease if max_score > 0.5 else 'none',
            'confidence': max_score,
            'all_scores': scores,
            'action': self._get_action()
        }
    
    def _detect_seizure(self, motion, eyes):
        # 癫痫：剧烈运动+闭眼
        motion_score = min(motion / 10, 1.0)
        eye_score = 1.0 - np.mean(eyes)
        return 0.6 * motion_score + 0.4 * eye_score
    
    def _detect_cardiac_arrest(self, hr, br):
        # 心脏骤停：心率异常+呼吸停止
        hr_score = 1.0 if hr < 30 or hr > 200 else 0.0
        br_score = 1.0 if br < 5 else 0.0
        return max(hr_score, br_score * 0.8)
    
    def _detect_stroke(self, skin, pose):
        # 中风：面部不对称
        # 简化：肤色变化+头部偏斜
        asymmetry = abs(pose[1])  # yaw偏斜
        return min(asymmetry / 30, 1.0)
    
    def _detect_syncope(self, pose, eyes, pressure):
        # 晕厥：头部下垂+闭眼+压力变化
        pitch_score = min(pose[0] / 45, 1.0)
        eye_score = 1.0 - np.mean(eyes)
        pressure_var = np.std(pressure)
        return 0.4*pitch_score + 0.3*eye_score + 0.3*min(pressure_var, 1.0)
    
    def _get_action(self):
        if self.state == 'emergency':
            return {
                'level': 3,
                'actions': ['自动靠边停车', '紧急呼叫', '车门解锁', 'ADAS介入']
            }
        elif self.state == 'warning':
            return {
                'level': 2,
                'actions': ['语音提示', '建议停车', '预紧急联系']
            }
        return {'level': 0, 'actions': []}


if __name__ == "__main__":
    detector = SuddenSicknessDetector()
    
    # 正常驾驶
    normal = detector.detect(
        head_pose=(0, 0, 0), eye_openness=(0.8, 0.8),
        body_motion=0.2, breathing_rate=16, heart_rate=72,
        skin_color=np.random.rand(3), seat_pressure=np.random.rand(16),
        timestamp=0
    )
    print(f"正常: {normal['state']}, {normal['likely_condition']}")
    
    # 模拟癫痫
    seizure = detector.detect(
        head_pose=(20, 5, 10), eye_openness=(0.1, 0.1),
        body_motion=8.5, breathing_rate=25, heart_rate=150,
        skin_color=np.random.rand(3), seat_pressure=np.random.rand(16),
        timestamp=1
    )
    print(f"癫痫: {seizure['state']}, {seizure['likely_condition']}, {seizure['action']}")