Pulse Transit Time-Pulse Wave Analysis Fusion Based on Wearable Wrist Ballistocardiogram for Cuff-Less Blood Pressure Trend Tracking

Peyman Yousefian; Sungtae Shin; Azin Sadat Mousavi; Ali Tivay; Chang-Sei Kim; Ramakrishna Mukkamala; Dae-Geun Jang; Byung Hoon Ko; Jongwook Lee; Ui-Kun Kwon; Youn Ho Kim; Jin-Oh Hahn

doi:10.1109/ACCESS.2020.3012384

IEEE Access (Jan 2020)

Pulse Transit Time-Pulse Wave Analysis Fusion Based on Wearable Wrist Ballistocardiogram for Cuff-Less Blood Pressure Trend Tracking

Peyman Yousefian,
Sungtae Shin,
Azin Sadat Mousavi,
Ali Tivay,
Chang-Sei Kim,
Ramakrishna Mukkamala,
Dae-Geun Jang,
Byung Hoon Ko,
Jongwook Lee,
Ui-Kun Kwon,
Youn Ho Kim,
Jin-Oh Hahn

Affiliations

Peyman Yousefian: ORCiD; Humana, Inc., Boston, MA, USA
Sungtae Shin: ORCiD; Department of Mechanical Engineering, Dong-A University, Busan, South~Korea
Azin Sadat Mousavi: ORCiD; Department of Mechanical Engineering, University of Maryland, College Park, MD, USA
Ali Tivay: Department of Mechanical Engineering, University of Maryland, College Park, MD, USA
Chang-Sei Kim: School of Mechanical Engineering, Chonnam National University, Gwangju, South Korea
Ramakrishna Mukkamala: ORCiD; Department of Bioengineering and Anesthesiology and Perioperative Medicine, University of Pittsburgh, Pittsburgh, PA, USA
Dae-Geun Jang: Healthcare Sensor Laboratory, Samsung Advanced Institute of Technology, Suwon, South~Korea
Byung Hoon Ko: Healthcare Sensor Laboratory, Samsung Advanced Institute of Technology, Suwon, South~Korea
Jongwook Lee: ORCiD; Healthcare Sensor Laboratory, Samsung Advanced Institute of Technology, Suwon, South~Korea
Ui-Kun Kwon: Healthcare Sensor Laboratory, Samsung Advanced Institute of Technology, Suwon, South~Korea
Youn Ho Kim: Healthcare Sensor Laboratory, Samsung Advanced Institute of Technology, Suwon, South~Korea
Jin-Oh Hahn: ORCiD; Department of Mechanical Engineering, University of Maryland, College Park, MD, USA

DOI: https://doi.org/10.1109/ACCESS.2020.3012384
Journal volume & issue: Vol. 8
pp. 138077 – 138087

Abstract

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The objective of this study was to investigate the efficacy of pulse transit time (PTT)-pulse wave analysis (PWA) fusion in cuff-less blood pressure (BP) trend tracking based on the wearable wrist ballistocardiogram (BCG). We constructed PTT and 36 candidate BCG PWA features based on the BCG and photoplethysmogram (PPG) signals acquired at the wrist. We performed a model-based analysis to select 6 candidate BCG PWA features most sensitive to BP. We aggregated the 6 BCG PWA features into novel predictors of diastolic, systolic, and pulse BP (DP, SP, and PP) orthogonal to PTT by covariance-maximizing dimensionality reduction. Then, we evaluated and compared the efficacy of BCG PTT and BCG PTT-PWA fusion in tracking the trend of DP, SP, and PP. Unique innovations of this study, generalizable to a range of physiological signals beyond the BCG, are (i) the systematic selection of PWA features based on model-based analysis and (ii) the development of PWA-based BP predictors orthogonal to PTT. Using the experimental wrist BCG and PPG signals collected from 23 human subjects, we demonstrated that (i) BCG PTT-PWA fusion may significantly outperform BCG PTT; (ii) PTT may play the primary role in tracking BP while BCG PWA features may still have an independent and complementary value (especially in tracking PP); and (iii) model-based selection of BCG PWA features can enhance the robustness of BP trend tracking based on BCG PTT-PWA fusion.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

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