Pinheiro Eduardo C, Postolache Octavian A, Girão Pedro S
Instituto Superior Técnico (IST, Technical University of Lisbon), Portugal.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:939-42. doi: 10.1109/IEMBS.2010.5627539.
When recording the pressure oscillations of a seated subject two distinct effects are assessed, ample vibrations due to the person's movement, and periodic oscillations of small amplitude due to cardiopulmonary activity, expressed by the ballistocardiogram (BCG). Embedding a pressure sensor in a chair's back or seat allows unobtrusive monitoring of the BCG. However, inconspicuously acquired signals are affected by numerous artifacts, often generated by the subject's forgetfulness, and posture changes due to lack of constrains. Moreover, the signal changes considerably its shape from person to person, and when the seating posture, or conversely, sensor position, is different. For real-time continuous monitoring, it is still to be found a method which, without introducing significant delays, can deal with such volatility. Thus, tailored calibration of peak detectors and other algorithms is recurrent, and even so, the neighboring samples of artifacts are possibly untreatable. This work evaluates the advantages of Empirical Mode Decomposition, as well as a coarser demodulation approach of the BCG signal, as dependable methods to allow real-time heart rate estimation on unstable BCG records. An analysis of the Fourier transform of the demodulated signals is the method used to provide and compare robustness of heart rate estimates.
在记录坐姿受试者的压力振荡时，会评估两种不同的效应：一种是由于人体运动产生的大量振动，另一种是由心冲击图（BCG）表示的由于心肺活动引起的小幅度周期性振荡。将压力传感器嵌入椅子的靠背或座位中，可以对BCG进行不引人注意的监测。然而，以不显眼方式获取的信号会受到许多伪影的影响，这些伪影通常是由受试者的遗忘以及由于缺乏约束导致的姿势变化所产生的。此外，信号的形状在人与人之间、以及坐姿或相反地传感器位置不同时会有很大变化。对于实时连续监测而言，仍有待找到一种方法，该方法在不引入显著延迟的情况下能够应对这种波动性。因此，对峰值检测器和其他算法进行定制校准是常有的事，即便如此，伪影的相邻样本可能仍无法处理。这项工作评估了经验模态分解的优势，以及BCG信号的一种更粗略的解调方法，将其作为在不稳定的BCG记录上进行实时心率估计的可靠方法。对解调信号进行傅里叶变换分析是用于提供和比较心率估计稳健性的方法。
