A Wearable Multimodal Sensing System for Tracking Changes in Pulmonary Fluid Status, Lung Sounds, and Respiratory Markers

• Type of Material: Article
• Authors: Jesus A Sanchez-Perez, Georgia Institute of Technology; John A Berkebile, Georgia Institute of Technology; Brandi N Nevius, Georgia Institute of Technology; Goktug C Ozmen, Georgia Institute of Technology; Christopher J Nichols, Emory University; Venu G Ganti, Georgia Institute of Technology; Samer A Mabrouk, Georgia Institute of Technology; Gari Clifford, Emory University; Rishikesan Kamaleswaran, Emory University; David Wright, Emory University; Omer T Inan, Georgia Institute of Technology
• Language: English
• Date: 2022-02-01
• Publisher: MDPI
• Publication Version: Final Published Version
• Copyright Statement: © 2022 by the authors.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.3390/s22031130
• Title of Journal or Parent Work: SENSORS
• Volume: 22
• Issue: 3
• Grant/Funding Information: This research was funded by the National Institutes of Health (NIH), grant number R01EB023808.
• Keywords: Technology; impedance pneumography; Instruments & Instrumentation; fluid status; cardiorespiratory monitoring; FLOW; Science & Technology; CONGESTION; HOSPITALIZATION; VARIABILITY; HEART-FAILURE; heart failure; CHEYNE-STOKES RESPIRATION; lung sounds; Chemistry; Chemistry, Analytical; Engineering; sensor fusion; Engineering, Electrical & Electronic; bioimpedance spectroscopy; Physical Sciences; wearable sensing
• Research Categories: Engineering, Mechanical; Engineering, Biomedical

Abstract

Heart failure (HF) exacerbations, characterized by pulmonary congestion and breathless-ness, require frequent hospitalizations, often resulting in poor outcomes. Current methods for tracking lung fluid and respiratory distress are unable to produce continuous, holistic measures of cardiopulmonary health. We present a multimodal sensing system that captures bioimpedance spectroscopy (BIS), multi-channel lung sounds from four contact microphones, multi-frequency impedance pneumography (IP), temperature, and kinematics to track changes in cardiopulmonary status. We first validated the system on healthy subjects (n = 10) and then conducted a feasibility study on patients (n = 14) with HF in clinical settings. Three measurements were taken throughout the course of hospitalization, and parameters relevant to lung fluid status—the ratio of the resistances at 5 kHz to those at 150 kHz (K)—and respiratory timings (e.g., respiratory rate) were extracted. We found a statistically significant increase in K (p < 0.05) from admission to discharge and observed respiratory timings in physiologically plausible ranges. The IP-derived respiratory signals and lung sounds were sensitive enough to detect abnormal respiratory patterns (Cheyne–Stokes) and inspiratory crackles from patient recordings, respectively. We demonstrated that the proposed system is suita-ble for detecting changes in pulmonary fluid status and capturing high-quality respiratory signals and lung sounds in a clinical setting.