Wearable Impedance Pneumography

Abstract

Respiratory diseases are a leading cause of death worldwide. The prevalence of sleep apnea, its cardiovascular consequences, postoperative respiratory instability and severe respiratory syndromes further highlight the importance of respiratory monitoring. Typical methods, however, rely on obtrusive nasal cannulas and belts. Impedance pneumography (IP) is a promising bioimpedance application which aims to estimate respiratory parameters from the thorax impedance. Currently, IP configurations require large inter-electrode distances, diminishing its applicability in a wearable context. We propose an IP configuration with 55 mm spacing using our recently presented sensor patch. In a study including 10 healthy subjects, respiratory rate (RR) and flow are estimated in the supine, lateral and prone position. Using time-delay neural network regression, RR errors below 1 bpm, flow correlations of 0.81 and relative flow errors of 38 % with respect to a pneumotachometer reference were achieved. We conclude that high accuracy RR estimation is possible in a 55 mm IP configuration. Respiratory flow can be roughly estimated. Further research combining several biosignals for a more robust, wearable flow estimation is recommended.

Keywords

• impedance pneumography
• wearable respiratory monitoring
• respiratory rate
• respiratory flow
• sensor patch
• neural network
• bioimpedance