Design of a Continuous Blood Pressure Measurement System Based on Pulse Wave and ECG Signals

Jian Qiang Li, Rui Li, Zhuang Zhuang Chen, Gen Qiang Deng, Huihui Wang, Constandinos X. Mavromoustakis, Houbing Song, Zhong Ming

Research output: Contribution to journalArticlepeer-review


With increasingly fierce competition for jobs, the pressures on people have risen in recent years, leading to lifestyle and diet disorders that result in significantly higher risks of cardiovascular disease. Hypertension is one of the common chronic cardiovascular diseases; however, mainstream blood pressure measurement devices are relatively heavy. When multiple measurements are required, the user experience and the measurement results may be unsatisfactory. In this paper, we describe the design of a signal collection module that collects pulse waves and electrocardiograph (ECG) signals. The collected signals are input into a signal processing module to filter the noise and amplify the useful physiological signals. Then, we use a wavelet transform to eliminate baseline drift noise and detect the feature points of the pulse waves and ECG signals. We propose the concept of detecting the wave shape associated with an instance, an approach that minimizes the impact of atypical pulse waves on blood pressure measurements. Finally, we propose an improved method for measuring blood pressure based on pulse wave velocity that improves the accuracy of blood pressure measurements by 58%. Moreover, the results meet the American medical instrument promotion association standards, which demonstrate the feasibility of our measurement system.

Original languageEnglish
Pages (from-to)1-14
Number of pages14
JournalIEEE Journal of Translational Engineering in Health and Medicine
Publication statusPublished - 17 Jan 2018


  • continuous blood pressure measurement
  • ECG
  • Pulse wave
  • wavelet transform


Dive into the research topics of 'Design of a Continuous Blood Pressure Measurement System Based on Pulse Wave and ECG Signals'. Together they form a unique fingerprint.

Cite this