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Automating the measurement of arterial blood pressure (ABP) remains an ongoing challenge. In a recent paper, a proposal is presented to automate the measurement of PSA based on the pulse transit time or (PTT), measured between the electrocardiographic (ECG) R-peaks and the peaks maximum slope of the oscillometric signal. In this research the method was evaluated; noticing loss of information regarding the pulse amplitude, increased distortion of the envelope and rising measurement system. However, it provides a reference to the ECG signal so that it is proposed to integrate with other methods of measuring PSA greater degree of robustness to motion artifacts such as CITLO method as fiducial mark. [ABSTRACT FROM AUTHOR]

Objective: To improve the identification of peaks and feet in photoplethysmographic (PPG) pulses deformed by myokinetic noise, through the implementation of a modified fingertip and applying adaptive filtering. Method: PPG signals were recorded from 10 healthy volunteers using two photoplethysmography systems placed on the index finger of each hand. Recordings lasted three minutes andwere done as follows: during the first minute, both handswere at rest, and for the lasting two minutes only the left hand was allowed to make quasi-periodicmovementsin order to add myokinetic noise. Two methodologies were employed to process the signals off-line. One consisted on using an adaptive filter based onthe Least Mean Square (LMS) algorithm, and the other includeda preprocessing stage in addition to the same LMS filter. Both filtering methods were compared and the one with the lowest error was chosen to assess the improvement in the identification of peaks and feet from PPG pulses. Results: Average percentage errors obtained wereof 22.94% with the first filtering methodology, and 3.72% withthe second one. On identifying peaks and feet from PPG pulsesbefore filtering, error percentages obtained were of 24.26% and 48.39%, respectively, and once filtered error percentageslowered to 2.02% for peaks and 3.77% for feet. Conclusions: The attenuation of myokinetic noise in PPG pulses through LMS filtering, plusa preprocessing stage, allows increasingthe effectiveness onthe identification of peaks and feet from PPG pulses, which are of great importance for medical assessment. [ABSTRACT FROM AUTHOR]