Abstract
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.
Highlights
Respiratory diseases are the third leading cause of death amongst the noncommunicable diseases worldwide [1]
Most ECG configurations span a large section of the thorax and a significant portion of the injected current will be influenced by the lung
While there has been work on optimizing impedance pneumography (IP) electrode configurations [7], its focus mainly was on preserving a linear relationship between the IP signal and respiratory volume [8]
Summary
Respiratory diseases are the third leading cause of death amongst the noncommunicable diseases worldwide [1]. The high prevalence of obstructive sleep apnea with an estimated 936 million people affected worldwide [2] and its association with increased risk of cardiovascular diseases [3] further underline the importance of respiratory monitoring. Most ECG configurations span a large section of the thorax and a significant portion of the injected current will be influenced by the lung. Large electrode distances are suboptimal for wearable monitors, while minimizing electrode distances reduces the current density in proximity to the lungs. Most studies on wearable IP setups rely on electrode positions close to known linearly behaving sets [9] and only very few use nonlinear regression approaches [10]. We presented 8 cm short distance IP [12]
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