Abstract
In recent years, respiratory monitoring has gained attention due to the high prevalence and severe consequences of sleep apnea, post-anesthesia respiratory instability and respiratory diseases. Nevertheless, respiratory monitoring oftentimes relies on obtrusive masks and belts, which are unsuitable for wearable, long-term monitoring. Impedance pneumography (IP) is a bioimpedance method aiming to assess respiratory parameters unobtrusively. However, most IP configurations require far-spaced electrodes. Based on our recent work on wearable IP, we propose a dual-lead, wearable IP setup with 55 mm electrode spacing to estimate respiratory flow and rate (RR). Using our recently presented multimodal patch stethoscope as well as commercial systems, we conducted a study including 10 healthy subjects which were recorded in the supine, lateral and prone position. Using time-delay neural networks, we achieved RR estimation errors below 0.6 breaths per minute and flow correlations of 0.88 with relative errors of 25 % to a pneumotachometer reference. We conclude that dual-lead IP increases the performance of respiratory signal estimation compared to a single lead and recommend research in the area of subject position dependency and movement artefacts.
© 2020 by Walter de Gruyter Berlin/Boston
This work is licensed under the Creative Commons Attribution 4.0 International License.
