Signal quality quantification and waveform reconstruction of arterial blood pressure recordings

Arterial blood pressure (ABP) is an important vital sign of the cardiovascular system. As with other physiological signals, its measurement can be corrupted by different sources of noise, interference, and artifact. Here, we present an algorithm for the quantification of signal quality and for the reconstruction of the ABP waveform in noise-corrupted segments of the measurement. The algorithm quantifies the quality of the ABP signal on a beat-by-beat basis by computing the normalized mean of successive differences of the ABP amplitude over each beat. In segments of poor signal quality, the ABP wavelets are then reconstructed on the basis of the expected cycle duration and envelope information derived from neighboring ABP wavelet segments. The algorithm was tested on two datasets of ABP waveform signals containing both invasive radial artery ABP and noninvasive ABP waveforms. Our results show that the approach is efficient in identifying the noisy segments (accuracy, sensitivity and specificity over 95%) and reliable in reconstructing beats that were artificially corrupted.