Virtual Spirometry and Activity Monitoring Using Multichannel Electrical Impedance Plethysmographs in Ambulatory Settings

Abstract

Continuous monitoring of respiratory patterns and physical activity levels can be useful for remote health management of patients with conditions such as heart disease and chronic obstructive pulmonary disease (COPD). In a clinical setting, spirometers serve as the gold-standard for monitoring respiratory patterns such as breathing-rate and changes in lung-volume. However, direct measurements using a spirometer requires placement of a sensor in the patient’s airway and is thus infeasible for continuous monitoring in non-clinical, ambulatory settings. Under these conditions, indirect respiration monitoring using electrical impedance plethysmographs (EIP) is more suitable but are susceptible to motion artifacts. In this paper we investigate whether multi-channel EIP can be used to perform virtual spirometry under ambulatory settings. The experiments presented in this paper are based on preliminary data collected from 19 adult human subjects under realistic ambulatory and non-ambulatory settings. We first highlight the salient features of the signal acquired from a standard spirometer. We then compare the performance of different bio-signal processing algorithms in estimating the spirometer signal using multiple EIP sensors and in the presence of motion artifacts and real-world interferences. We demonstrate that in addition to reliably determining different respiratory patterns and states, multi-channel EIP could also be used to reliably extract information regarding different patient physical activity states like bending or stretching.

Advances in Respiratory Monitoring: A Comprehensive Review of Wearable and Remote Technologies

“…To mitigate motion artifacts, a combined hardware and software solution was created using a band-pass filter and adaptive noise cancellation software implemented in the microcontroller's firmware. Khan et al [100] compared electrical impedance plethysmography (EIP) with spirometry. The objective was accurate spirometer output estimation using EIP channel outputs.…”