An Open Source Validation System for Continuous Arterial Blood Pressure Measuring Sensors

The advancement of sensor technologies enables the measurement of high-quality continuous blood pressure signals, which has become an important area in healthcare. The development of such application-specific sensors can be time-consuming, expensive, and difficult to test or validate with known and consistent waveforms. In this manuscript, an open-source blood pressure waveform simulator with a Python validation package is described. The core part, a 3D-printed cam, can be generated based on real blood pressure waveforms. The validation software framework compares in detail the waveform used to design the cam with the time series from the sensor being validated. The simulator was validated using a 3D force sensor. The RMSE of accuracy was 1.94 (44)-2.74 (63)%, and the Pearson correlation with the nominal signal was 99.84 (13)-99.39 (18)%. As for precision, the RMSE of the repeatability of cam rotations was 1.53 (71)-2.13 (116)% and the Pearson correlation was 99.85 (16)-99.59 (57)%. The presented simulator proved to be robust and accurate in short- and long-term use, as it produced the signal waveform reliably and with high fidelity. It reduces development costs for early-stage sensor development and research, offering a solution that is easy to manufacture yet capable of continuously outputting human arterial blood pressure waveforms spanning multiple consecutive cardiac cycles.