Comparison of the Correlation of Different Pulse Transit Time Parameters to Blood Pressure

  • Wan-Hua Lin
  • Oluwarotimi Williams Samuel
  • Qing Liu
  • Yuan-Ting Zhang
  • Guanglin LiEmail author
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 64)


Estimation of blood pressure (BP) based on pulse transit time (PTT) is of great interest since it can estimate BP continuously and cufflessly. In previous studies, different character points were available in ECG and in photoplethysmogram (PPG) for calculating PTT. The present study aimed at comparing the correlation of BP to different PTT parameters calculated using different character points of ECG and PPG. PTT parameters were calculated as the time interval from R peak, Q valley, or S valley of ECG to the peak or valley of the first derivative of the PPG. Correlations of beat-to-beat BP to the different beat-to-beat PTT parameters were calculated for the selected 13 datasets with a total of 3910 heart beats data. The results showed that the PTT as the time interval from Q valley of the ECG to the peak of the first derivative of the PPG gave the best parameter which correlates with both the systolic blood pressure (SBP, r = −0.62 ± 0.14) and the diastolic blood pressure (DBP, r = −0.45 ± 0.18). Therefore, this method of determining PTT would be useful to improve the accuracy of estimating BP continuously and cufflessly.



The work was supported in part by the National Key Basic Research Program of China (NO. 2013CB329505), the National Natural Science Foundation of China under Grants (NO. 61135004, NO. 61203209), the Shenzhen Governmental Basic Research Grant (NO. JCYJ20130402113127532), and the External Cooperation Program of Chinese Academy of Sciences (NO. GJHZ1212).

Conflict of Interest

The authors declare that they have no conflict of interest.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Wan-Hua Lin
    • 1
    • 2
  • Oluwarotimi Williams Samuel
    • 1
    • 2
  • Qing Liu
    • 3
  • Yuan-Ting Zhang
    • 3
    • 4
  • Guanglin Li
    • 1
    Email author
  1. 1.Key Laboratory of Human-Machine Intelligence-Synergy SystemsShenzhen Institutes of Advanced Technology, Chinese Academy of SciencesShenzhenChina
  2. 2.Shenzhen College of Advanced TechnologyUniversity of Chinese Academy of SciencesShenzhenChina
  3. 3.Joint Research Center for Biomedical EngineeringThe Chinese University of Hong KongShatinHong Kong
  4. 4.Apple Inc.Silicon ValleyUSA

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