diff --git a/energy_based_recorder.py b/energy_based_recorder.py
index f8e4477..535e493 100644
--- a/energy_based_recorder.py
+++ b/energy_based_recorder.py
@@ -29,6 +29,7 @@ class EnergyBasedRecorder:
         self.silence_threshold = silence_threshold  # 静音阈值，低于此值持续多久认为结束
         self.min_recording_time = min_recording_time  # 最小录音时间
         self.max_recording_time = max_recording_time  # 最大录音时间
+        self.pre_record_duration = 2.0  # 预录音时长（秒）
         
         # 状态变量
         self.audio = None
@@ -41,6 +42,10 @@ class EnergyBasedRecorder:
         self.energy_history = []  # 能量历史
         self.max_energy_history = 50  # 最大能量历史记录
         
+        # 预录音缓冲区
+        self.pre_record_buffer = []  # 预录音缓冲区
+        self.pre_record_max_frames = int(self.pre_record_duration * self.RATE / self.CHUNK_SIZE)  # 最大预录音帧数
+        
         # 性能监控
         self.frame_count = 0
         self.start_time = time.time()
@@ -201,11 +206,26 @@ class EnergyBasedRecorder:
         except Exception as e:
             print(f"❌ 系统播放器也失败: {e}")
     
+    def update_pre_record_buffer(self, audio_data):
+        """更新预录音缓冲区"""
+        self.pre_record_buffer.append(audio_data)
+        
+        # 保持缓冲区大小
+        if len(self.pre_record_buffer) > self.pre_record_max_frames:
+            self.pre_record_buffer.pop(0)
+    
     def start_recording(self):
         """开始录音"""
         print("🎙️ 检测到声音，开始录音...")
         self.recording = True
         self.recorded_frames = []
+        
+        # 将预录音缓冲区的内容添加到录音中
+        self.recorded_frames.extend(self.pre_record_buffer)
+        
+        # 清空预录音缓冲区
+        self.pre_record_buffer = []
+        
         self.recording_start_time = time.time()
         self.last_sound_time = time.time()
         self.energy_history = []  # 重置能量历史
@@ -215,7 +235,12 @@ class EnergyBasedRecorder:
         if len(self.recorded_frames) > 0:
             audio_data = b''.join(self.recorded_frames)
             duration = len(audio_data) / (self.RATE * 2)  # 16位音频，每样本2字节
-            print(f"📝 录音完成，时长: {duration:.2f}秒")
+            
+            # 计算实际录音时长和预录音时长
+            actual_duration = duration
+            pre_record_duration = min(duration, self.pre_record_duration)
+            
+            print(f"📝 录音完成，时长: {actual_duration:.2f}秒 (包含预录音 {pre_record_duration:.1f}秒)")
             
             # 保存录音
             success, filename = self.save_recording(audio_data)
@@ -275,6 +300,8 @@ class EnergyBasedRecorder:
         print("- 动态阈值调整（基于背景噪音）")
         print("- 零交叉率检测（区分语音和噪音）")
         print("- 实时显示ZCR和背景能量")
+        print("- 预录音功能（包含声音开始前2秒）")
+        print("- 环形缓冲区防止丢失开头音频")
         print("=" * 50)
         
         try:
@@ -315,21 +342,26 @@ class EnergyBasedRecorder:
                         print(f"\n⏰ 达到最大录音时间 {self.max_recording_time}秒")
                         self.stop_recording()
                     
-                    # 显示录音状态
+                    # 显示录音状态（包含预录音信息）
+                    pre_duration = len(self.pre_record_buffer) * self.CHUNK_SIZE / self.RATE
                     bg_energy = np.median(self.energy_history[-10:]) if len(self.energy_history) >= 10 else 0
                     status = f"录音中... {recording_duration:.1f}s | 能量: {energy:.0f} | ZCR: {zcr:.0f} | 背景: {bg_energy:.0f}"
                     print(f"\r{status}", end='', flush=True)
                 
                 else:
-                    # 监听模式 - 使用高级检测
+                    # 监听模式 - 更新预录音缓冲区
+                    self.update_pre_record_buffer(data)
+                    
+                    # 使用高级检测
                     if self.is_voice_active_advanced(energy, zcr):
                         # 检测到声音，开始录音
                         self.start_recording()
                     else:
-                        # 显示监听状态
+                        # 显示监听状态（包含缓冲区信息）
                         avg_energy = self.get_average_energy()
                         bg_energy = np.median(self.energy_history[-10:]) if len(self.energy_history) >= 10 else 0
-                        status = f"监听中... 能量: {energy:.0f} | ZCR: {zcr:.0f} | 背景: {bg_energy:.0f}"
+                        buffer_usage = len(self.pre_record_buffer) / self.pre_record_max_frames * 100
+                        status = f"监听中... 能量: {energy:.0f} | ZCR: {zcr:.0f} | 背景: {bg_energy:.0f} | 缓冲: {buffer_usage:.0f}%"
                         print(f"\r{status}", end='', flush=True)
                 
                 # 减少CPU使用