用于胎儿心跳声音的动态参数模拟器
A Dynamic Parametric Simulator for Fetal Heart Sounds
AI总结：
本文提出了一种动态参数模拟器，用于生成长腹部胎儿心跳声音序列，通过结合事件合成与传输模块，实现可重复的fPCG处理方法评估。
摘要：
胎儿 Phonocardiogram（fPCG）的研究受到有限的腹部录音数量、显著的母体干扰以及明显的传输引起的信号衰减的挑战，这些因素使得可重复的基准测试变得困难。我们提出了一个可重复的动态参数模拟器，通过结合周期级胎儿S1/S2事件合成与卷积传输模块以及可配置的干扰和背景噪声，生成长腹部fPCG序列。模型参数从真实的腹部录音中按周期校准，以捕捉心拍间的变化，并定义数据驱动的可接受范围，用于可控的合成。生成的信号在基于包络的时域结构和频域特性方面与真实录音进行验证。该模拟器作为开源软件发布，以支持在受控采集条件下快速、可重复评估fPCG处理方法。
英文摘要：
Research on fetal phonocardiogram (fPCG) is challenged by the limited number of abdominal recordings, substantial maternal interference, and marked transmissioninduced signal attenuation that complicate reproducible benchmarking. We present a reproducible dynamic parametric simulator that generates long abdominal fPCG sequences by combining cycle-level fetal S1/S2 event synthesis with a convolutional transmission module and configurable interference and background noise. Model parameters are calibrated cyclewise from real abdominal recordings to capture beat-to-beat variability and to define data-driven admissible ranges for controllable synthesis. The generated signals are validated against real recordings in terms of envelope-based temporal structure and frequency-domain characteristics. The simulator is released as open software to support rapid, reproducible evaluation of fPCG processing methods under controlled acquisition conditions.
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