PyrAmes Inc., Cupertino, CA 95014, USA.
Department of Geography & Atmospheric Science, University of Kansas, Lawrence, KS 66045, USA.
Sensors (Basel). 2021 Jun 22;21(13):4273. doi: 10.3390/s21134273.
This paper reviews recent advances in non-invasive blood pressure monitoring and highlights the added value of a novel algorithm-based blood pressure sensor which uses machine-learning techniques to extract blood pressure values from the shape of the pulse waveform. We report results from preliminary studies on a range of patient populations and discuss the accuracy and limitations of this capacitive-based technology and its potential application in hospitals and communities.
本文综述了无创血压监测技术的最新进展,并重点介绍了一种新型基于算法的血压传感器,该传感器利用机器学习技术从脉搏波的形态中提取血压值。我们报告了一系列患者人群的初步研究结果,并讨论了这种基于电容的技术的准确性和局限性及其在医院和社区中的潜在应用。